The Unwritten Book is Finally Written!
An in-depth analysis of: The sacrifice bunt, batter/pitcher matchups, the intentional base on balls, optimizing a batting lineup, hot and cold streaks, clutch performance, platooning strategies, and much more. Read Excerpts & Customer Reviews
If you have an ipod touch, I think it would work fine(?). I doubt you'd have any luck integrating the in-ipod stopwatch into your scorekeeping, as you can't easily flip between apps. But if you had one in your hand, you could type in the time as a note for later retrieval. That's probably the best you could do w/ it for now.
If I was doing anything official, I'd definitely bring a scorebook as a backup. At least that fights the power loss/malfunction issue. As for data loss...you can back up after every game.
If you're mid-game and something happens, you're right, this could be bad. Seems pretty reliable, though. Might be worth checking the support forum to see what issues have occurred with the software. They do have some preventive measure suggestions, like clearing out your ram by doing a hard reboot prior to a game (some other apps don't clear out of memory like they should, which can cause a memory crisis for iscore).
-j
Yeah, that was something that really stuck out to me as I was doing it. I'd say that most of my balls in play are right at fielders, in the gaps, or on the lines. Distance-wise, it's either warning track, infield grass, or "medium." Its still useful info, but I'm sure I'm plus/minus 20 feet at best.
The other thing I noticed is an explanation for why 90% of all balls hit into play are "medium." Unless it's hit REALLY hard, to the warning track, or is a weak infield hit of some sort, I rarely feel justified marking a ball as anything but hit "medium." I remember Shane Jensen joking in a video seminar once that the batted ball speed data they purchased were just like this. Need that stopwatch data...
-j
Oliver and CHONE's fielding projections include minor league data, so I'm not sure that this is true.
Also, while it's spread over a bunch of seasons, we have almost a full season's of MLB innings on Torres, and his career UZR/150 across all outfield positions is +22 runs (+20 in CF, where a bit more than half of his innings have been). McCutchen has a similar MLB innings totals, but his career UZR/150 is -6 runs (admittedly all in CF).
If I were picking players, I'd certainly take McCutchen over Torres. But Torres might be a poor man's Franklin Gutierrez. Or maybe not so poor man's--both rate as +14 run players vs. other CF's.
-j
Sky/7,
All of the projections are supposed to match the park environment of the hitter. That's why I park-adjusted the offense RAA numbers.
BrianK/6,
Torres' line is all fielding. Depending on how real you think it is, it can push his value up or down a lot.
As for Gonzalez, that's a screw-up. I don't know how it happened. Complete user error. He is at +41 runs in my spreadsheet, right behind Fielder, 3rd among NL 1B's. I must have accidentally pushed him into the AL group somehow--maybe in anticipation of a trade? :)
-j
Aging is part of how we predict future performance. My goal here is to pick the best players. Past performance is part of it. But it needs to be interpreted, regressed, etc. That's what using a rest of season projection does for us.
Re: UZR--I'm going to re-do this with Steve's uzr projections for NL tonight, and will use them for AL projections too.
-j
Yeah, I don't know how much I "care" about the All Star game. But it's always a good opportunity to take a moment and reflect on the current best players in baseball. So on that level, I like it.
I should have caught the Zimmerman fielding thing, but missed it. Caught it for Kelly Johnson. I'm ultimately just not a huge fan of the Oliver/CHONE fielding stats, but they are probably close more often than they completely miss it. Something's better than nothing. Maybe I should pester Steve for his UZR projections. :)
-j
Regarding application to fantasy: I had no idea how true this was until I started playing fantasy this year for the first time in over a decade. I'm amazed at the number of people who try to play hot streaks and cold streaks on a consistent basis. That, and people who choose who to start based on historical performance against individual teams. Those two things account for about a third of the conversations you see on discussion boards or hear on fantasy podcasts. For the most part, people are just chasing randomness.
I assigned several chapters from the book this past year for my baseball class: clutch hitting, hot/cold streaks, and lineups. Most students seemed to do pretty well with it, which says something for how accessible much of it is. These were freshman college students, and often students with little math background.
-j
Mike/6,
I'm using essentially an 8 win difference in the BtB power rankings. I boost AL teams by ~4 wins per year and penalize NL teams by ~4 wins per year. As Tango pointed out above, it's actually conservative relative to recent history (~12 win difference), but it makes a big enough difference that I have a hard time boosting it any higher. I get enough hell about it as it is. :)
-j
I'm not a game theory expert by any means. But I produced a very simple game theory model looking at this question to help guide the discussion in my baseball class when we read MGL's fangraphs article on game theory & pitch selection.
The model found that with optimal pitch selection, all pitch run values tend to be very similar, but not necessarily identical. Sometimes, it's worth it to occasionally correct throw in an occasional "bad" pitch--even if it's of inferior run value to the worst-case scenario for a "good" pitch--because it makes the good pitch that much better the next time around. It's a marginal effect, and depends on some assumptions. ... but I couldn't get away from it.
I try to get it written up as soon as I can so you guys can tell me what's wrong with it.
-j
If you use putouts, C's and 1B's will break whatever you try to do. And without putouts, outfielders are nearly worthless. I don't think it's workable.
-j
Hi,
I just used these linear weights:
http://www.tangotiger.net/bsrexpl.html
I'm using lwts_RC column since I'm doing things in absolute runs.
Since a single is an AB+H, and a double is an AB+H+2B, some combining of these stats is necessary so that the totals come out right. Here are the "combined" linear weight values I'm using, followed by the rounded point values for each term:
Event lwts_rc Pts
AB -0.1 -1
H 0.563 6
2B 0.287 3
3B 0.57 6
HR 0.939 9
SB 0.193 2
CS -0.282 -3
BB 0.3 3
Hope that helps.
-j
Found it!
http://web.archive.org/web/20080112135748/mvn.com/mlb-stats/2008/01/06/on-the-reliability-of-pitching-stats/
Now someone go make tRA* for me, k? :)
-j
Sky,
Here's Pizza's hitter article:
http://web.archive.org/web/20080102094412/http://mvn.com/mlb-stats/2007/11/14/525600-minutes-how-do-you-measure-a-player-in-a-year/
Assigned it for my class last week.
Don't have the pitcher one, though, and that's probably what we need. Easiest way is to find someone who linked to it so we can get the old URL--that makes it easy to find on archive.org. But I haven't had any luck with that.
-j
Lee also had me read a few sections a while back, especially on catcher defense. I skimmed the rest as well, though, and found it to be a nice, general primer that will get you up to speed on a lot of modern sabermetric work--especially player valuation. Good for him in getting it done!
-j
I've been fussing with this literally all day and finally came to something I'm somewhat comfortable with. Since others might be doing the same thing, I thought I'd report back.
Here is ultimately what I came up with for pitchers:
IP +5
K +2
BB -3
HR -13
SV +6
HD +2
I didn't set out to have those numbers match up to the coefficients in the FIP equation. I started with linear weights and went through a process that was as much guesswork as it was sensical. My plan was to create a DIPSy adjustment of absolute-runs linear weights....but those numbers started out too low, so in desperation I started increasing the positive terms, eliminating anything related to hits...and the result was suddenly something that looks a lot like the FIP equation (whether by coincidence or not). Seems to work pretty well--the rankings of players seem intuitive to me--though I don't think my methods would hold up to much scrutiny.
The saves issue is tricky. I hate saves with a passion, but we have nothing else to work with that relates to reliever leverage. This gets elite closers in 2009 equivalent in value to starters like Aaron Harang, Johnny Cueto, Brad Penny, etc. That feels about right to me. I'm throwing setup guys a bone with the +2 holds, but it will take a lot of holds to get anywhere close to a closer's value. ::shrug::
Anyway, the system has good pitchers at 800+ points, great pitchers at 1000+ points, and elite pitchers at 1250+ points. This matches up pretty well with the hitter scoring, which more or less is wRC*10. Based on the number of slots for pitchers (8) vs. position players (9) in my league, I'm crudely estimating a 55%/45% split between hitters and pitchers in terms of team point totals. Not quite the 60/40 Tango's system provides, but it feels close enough to me.
What I like about the wRCish system I'm employing is that negative players are hard to come by, so it's always better to have an active player in the lineup than someone who isn't playing at all. Managers in the league will essentially create a replacement baseline by plugging in the best talent they can when their starters go down. And we're still, at least with hitters, tied to something that is somewhat similar to reality.
-j
I'm starting a fantasy league along similar lines.
I was going to use Tango's point system, but the problem with them is that since they are set to replacement level without a position adjustment, a number of starting SS's and C's show up as negative value players...meaning that, as a fantasy manager, it's more productive to plug in an injured player or demoted AAA player into that slot than start some of these guys.
I've decided that the best way to address this is to use a point system that is more set to an absolute runs baseline than a replacement-level baseline. This way, it's the league market that sets up what will be our "replacement level", and it's incumbent on the manager to find players at or above replacement level when they have a player go down to injury (not doing so will have very bad consequences).
This was pretty easy to do for hitters. Here are Tango's replacement level points:
AB -2
H +6
2B +3
3B +5
HR +8
SB +2
CS -4
BB +3
Here they are in absolute runs-based points (they are just rounded absolute linear weights):
AB -1
H +6
2B +3
3B +6
HR +9
SB +2
CS -3
BB +3
There are rounding issues that throw things off, but this more or less will give you points = wRC*10 for hitters. The main difference is an adjustment of the value of an out from -2 to -1 points (this is also seen with the CS). I'm not sure why my triples and HR's also are getting an extra point here--I tried to replicate Tango's work but was getting these same values in those cases as well.
Anyway, my problem is that I'm having trouble figuring out how to convert Tango's pitching points into something that mirrors wRC. Here are Tango's points:
IP +2
H -0.5
BB -2
K 1
HR -3
2B -0.5
3B -0.5
SV +2
Hold +1
Any ideas how to make this a good approximation for absolute runs? I could probably bump up the point value for innings pitched from +2 to +3 (or should it be +4?), but I'm not sure if that would really do what I want it to. Part of it is that I'm not entirely sure how Tango came up with his framework, so I can't reconstruct it. Advice welcome!
Thanks,
Justin
P.S. If you're interested in my league, there are still ~5 slots open:
http://www.redreporter.com/2010/2/12/1308231/sabermetric-fantasy-baseball-anyone
Send me an e-mail so I have your contact info if interested. It probably won't be quite as hardcore as ShaneM's (autopick draft, transactions set to weekly), but my hope is that we have a nice balance between competitiveness and time commitments.
I don't think what I'm doing is necessarily wrong, given that, for example, I'm using DIPS-based pitching. It could be that the slash line is misleading because of BABIP or something and what I'm doing is more indicative of actual performance.
It is the case that I'm not applying park factors consistently, because I don't think you can use the same park factors on a DIPS stat as on an overall RC stat like wRC. I'm applying park factors to components going into tRA (or FIP), whereas I'm just doing an overall runs adjustment to the wRC data. It's a fair critique, but I preferred to just use wRC since it was available rather than deal with my own linear weights.
Fielding: no regression, but I do average together two fielding estimates. UZR had Seattle at +85 runs, whereas THT's batted ball team fielding stat had them at +61 runs. Average is 73, plus 7 runs for plus catching. So yeah, if you just use UZR + catching (no THT), you save 12 more runs.
As for pitchers, I think I'm pretty close to the mark:
Actual runs allowed for Seattle was 692. If you park adjust it (again, using PF = 0.98), it moves to 706. Then, add back in the fielding estimate above (+73 runs) and that gives an estimated park neutralish 779 RA by pitchers alone.
"My" FIP-Runs estimates 783 RA. Pretty much dead on. I know we're trying to not be wed to runs allowed here, but on average we should do a good job of estimating them. I'm not getting a massive disparity between RA and eRA here with respect to pitcher performance.
So, maybe I'm missing on fielding. I think the pitcher estimate is pretty close.
My hunch is that another part of this is that the Mariners had two forms of luck cancel here. They allowed a "lucky"-low number of hits allowed (which FIP doesn't track but the slash line does). But that the hits they allowed translated into an "unlucky" number of runs. So, maybe the slash line misleads a little bit too. Just a guess, but it helps explain our disparity here.
-j
Peter/12,
Mostly because I also like to look at how teams stack up against one another in the component stats--offense vs. pitching vs. fielding. I agree that if all I was interested in doing was estimating team winning percentage, it wouldn't make much sense to do park adjustments.
That said, you could argue that DIPSy stats are inherently park adjusted by themselves (they usually assume a neutral BABIP environment), so perhaps it is worth it to park adjust everything to (try to) make sure everything's compared in a neutral park context.
-j
Ed/10,
Pythagorean record basically tells you the winning percentage you'd expect to get based on your team's actual runs scored and runs allowed. It's basically a model of how runs scored and allowed typically convert to wins. Looking at it is a way of getting past some of the timing of when runs are scored that are what ultimately cause differences between actual and pythagorean w%. Many of those timing events are random, though some (like when good relievers are leveraged) probably are not.
A component-based approach like Tango, Dave, etc are advocating takes another step back and looks at how well a team performed based on their component statistics. Tango reported slash lines--how we evaluate hitters--at the team level to evaluate offense relative to defense. This gets away from even more of the timing events, like clutch hitting, that affect how components are converted into runs. But again, most of those timing events are fairly random. The result is arguably a better view of how well a team performed than straight-up pythagorean records, much less winning percentage, provide.
-j
Whoops, FIP should have read 4.48. And for some reason, looking back at my spreadsheet, it's now reporting 4.51. I think they're different because I'm now using 2009 HR park factor numbers from Patriot to adjust HR rate, whereas before I was using 2008.
Anyway, just wanted to say that if I use the FIP number instead of tRA to figure estimated runs allowed, I get:
783 - 80 runs (fielding) = 703 eRA (I got 731 eRA using tRA & fielding).
That's compared to an estimated runs scored of 665 based on wRC and EqBRR (removing steals), with park adjustments. Still puts them a few wins below 0.500, though obviously it puts them closer.
I don't know why the slash line you cited wouldn't agree with what I'm doing. Maybe I'm not giving credit for fielding, or there were some "luck" factors that feed into the defensive slash line that aren't accounted for with a DIPS/Fielding approach...? Or it's internal weighting issues within OBP and SLG that aren't borne out in wRC.
-j
Tango/7,
I'm not sure if that was a response to me or not. But just in case, to be clear, the number I cited is based on park adjusted wRC, BPro baserunning, a DIPSy pitching stat, and fielding (including catchers). No actual runs scored or allowed are used; it's all component-based estimates of RS and RA fed into Pythagenpat. Ultimately, what you're talking about is the entire motivation behind that power ranking project.
Offense (park adjusted, including EqBRR baserunning) I have SEA at wOBA = 0.319. By tERA I have pitchers at 4.66 (though FIP = 4.38--I do some park adjustments on FIP so it may differ from fangraphs...next year I'll probably use xFIP instead of this home brew tRA of mine because I trust it more). Fielding, including catching, I have at +80 runs, which is way over the 2nd-ranked Reds at +59 runs.
-j
I had them as a 0.461 team based on component winning percentage last season:
http://www.beyondtheboxscore.com/2009/10/11/1079698/btb-power-rankings-end-of-2009
(Converting Runs to Wins table)
Adding in the league adjustment put them at 0.487.
2nd worst offense in the AL, 3rd worst pitching, but easily the best fielding. If I would have used FIP instead of tRA, pitching would instead have come in 7th-worst in the AL.
-j
Mike/25,
Egg on my face, I guess. I completely forgot that you nominated it, and in retrospect I probably should have seconded it since no one else did. I think I ultimately didn't because I was trying to avoid doing nominations or seconds in categories in which we already had large numbers of nominations. At the time it was submitted, we already had 11 (though one was the cheeseburger thing and we opted to omit it, and two were for Allen and we made him pick one), and I was hoping to keep the number around 10 to keep things manageable.
But it was deserving of a nomination. Good work by Peter.
Again, the main point is that the gameday work gives us a check on the BIS data, which is a really valuable thing to have. If Colin's work goes well and his metric seems to behave well--and given his track record, odds are good that it will--then I'll be very happy to average his numbers with UZR (and maybe TZ and Fans) to get a nice composite fielding estimate for players.
-j
Nick/23,
Yes, Peter is the main person I was referencing who has used gameday to build a fielding metric (and come to think of it, why didn't we get that project nominated for a Saber??).
My point was that Colin's project, once complete, will presumably be implemented in BPro's statistics pages to give us up to date data on players throughout future seasons. Given the massive differences between sUZR and bUZR (and thus our awareness of how massively those two data sources differ), having another good-quality fielding metric available like this for all current players that uses a third data source will be very helpful.
-j
I'm pretty late here, but I just wanted to say that the primary benefit I'm seeing in Colin doing all of this is that we'll ultimately have another data source to compare to the BIS-based data. If we use the ZR conversions as well, then we'd have BIS, Gameday, STATS Inc, and Fan Scouting for any given player. This would go a long way in helping us smooth out problems with the data sources. I know others have used Gameday for fielding before Colin, but it's not something that's easily accessible for all players like bUZR currently is. Looking forward to seeing this get put together.
-j
This past weekend, my wife and I used the H&R Block software (cd, not online), as we got it from her dad who stumbled upon it for cheap somewhere a few weeks ago. We've always used turbotax in the past, and wouldn't have changed except that this was free. The HR Block software imported last year's turbotax data fine and seemed to do a good job. Our taxes aren't insanely complicated, but we did have child care tax credits, homeowner's insurance, interest on a mortgage, and an energy tax credit (new windows) to deal with. No problems incorporating any of those things into the return.
-j
It was an extremely close vote both internally and externally, but congrats to Victor Wang for winning this category. Very important work for those of us who like to judge player moves by the big clubs.
Not to take anything away from Victor (or any of the other nominees), but upon revisiting the top placers for the write-up, I have to say that I was also extremely impressed with Josh Kalk's Injury Zone article. It's one of things that might not currently "work," but has exciting promise and could potentially save careers. I love the idea of a laptop in the dugout that starts flashing warnings when a pitcher's arm starts to encounter trouble. :)
-j
There's a good, readable summary of this sort of work in the Psychology of Baseball by Stadler. Less current (though only a few years old), but talks about the competing models. Link to the book in my name.
-j
Just wanted to say that a big part of the reason that I proposed the sabermetric awards at BtB (results are in, awards write-ups are in progress and should be out next week) was directly related to my feeble efforts to assemble a library of sorts for this baseball class I was prepping for. I was struck at how difficult this was to do. We rarely as a community seem to make a concerted effort to compile our best work, and so I thought an annual "awards" thing of sorts might be a good way to encourage us to do that. Naming a "winner" was always a very secondary goal, but it does make it a bit more fun and gets people interested.
This year, my plan is to make monthly posts to help us take note of our favorite studies throughout the year--I think a lot of us had trouble remembering many of the great studies we'd seen over 12 months, so hopefully people will be willing to share their favorites. We could then mine these lists for next years' awards thing.
Also, I have added a great deal to my list of sabermetric studies since I originally posted this thread:
http://www.beyondtheboxscore.com/2009/12/17/1200459/want-to-help-me-plan-my-baseball
I keep it in a google wave right now, but I can post it as a resource somewhere if folks would like me to.
-j
Definitely looks to be a tight race. Currently there are 45 ballots submitted for the first category, and despite the "vote for as many as you like" framework, no study has appeared on more than 26% of the ballots. In fact, there are six studies that are named on between 22-26% of ballots.
So yes, I'm not expecting a consensus on several of these categories. But that's ok. We'll still probably crown a "winner," but we'll include all the major vote-getters in the category write-up after voting is complete.
Also, folks can continue to use the original project announcement post as a hub (click on my name). I'll add voting threads as they are released.
-j
I'm interested in folks' perceptions on the Aroldis Chapman signing. It's been hard to get a clear breakdown on the contract, but I THINK it's a for 5 yrs/$25M with a 6th yr/$5 M option. And there are also reports that there are numerous incentives to bring it even higher. Furthermore, at least some parts of the contract will be deferred as far back as 2020.
A lot may have to do with how well he ranks as a prospect. Top-10? Top-5? Top-2?
-j
I don't want to go over 10 nominations, except maybe for the best writer award where it may be as much a popularity contest as anything else. I think we're ok in most categories, though I'd prefer to have more than four choices as much as possible.
Cheers,
Justin
Today is the last day to submit & second nominations. Here's a hub post for the day.
http://www.beyondtheboxscore.com/2010/1/11/1245198/last-call-for-btb-sabermetric
Thanks again for the link.
-j
Obviously it's a very different course than mine, but it's helpful to see what other people are doing. Nice set of links to quality studies that still could be useful for my stuff.
-j
LJ/14,
What I see is BPro realizing that they were becoming irrelevant, and throwing resources behind an effort to bring in some of the best saber talent around. That many of the new hires were on statspeak is a testament to how special that place was for a while. I think BPro should be commended for this move--to me, these guys (Tommy Bennett too) are a major draw. They're getting my subscription money again after the holidays are over.
-j
Brian, given the lack of SS in the system (unless one believes in Cozart's bat), I tend to think that Frazier would still be at SS (where he started) if the Reds thought he would be anything but a disaster over there. He hasn't played SS above high-A ball. You're using position-specific MLE's on the fielding numbers right?
Valaika's still at SS, for example, and few think he will be able to play there. I think Frazier's always been considered a poorer fielder than Valaika--or at best, they are equals.
And Bruce isn't half bad in the field. He's not a CF, but he's above average in the corner slot. Both the Fans and UZR said so! :) If he ever figures out how to hit like we thought he would, he'd have a ton of value...
-j
Brian/171,
League-average defense at SS from Frazier might be a stretch based on scouting data: the Reds don't seem to think that he's a viable option at SS. At 2B or 3B, though, I think he's got a shot to be solid enough. He's also apparently fine in a corner outfield slot. I think of him as an average fielder overall: below average at SS, average at 2B/3B, above-average at LF/RF.
Francisco...I'd certainly be delighted if he could be an effective player for us, but I'm extremely skeptical despite your projections. I wonder how well a projection system can work on a player as extreme as he is. I honestly expect MLB pitchers to exploit the heck out of his tendency to literally swing at just about anything. As you said, even Frenchy has a higher walk rate--and Frenchy gets a lot more balls in play than Francisco ever has (~13%K rate vs. 25% k-rates if I remember right). He's fascinating, but I'm not banking on much coming from him.
-j
The only internal option I see as being viably better than replacement at 3B come 2011 is Todd Frazier, and there's a good chance that he may end up as our LF next year instead. And even if he doesn't, having a better-than-replacement internal option is a good thing when you're working with an injury-prone starter like Rolen. There will be lots of opportunities for bench players to impact games.
The other internal person that people are talking about Juan Francisco. But a) he's reputedly not a good defensive 3B range-wise, and b) I doubt he'll hit in the majors. Anyone have a good comp of a player with a 4% walk rate and a 25% K rate in the minors who went on to be a successful big league hitter? Best I've found is Wily Mo Pena, and he walked 6% of the time in the minors!
-j
Seth/166,
I have it as somewhere around a 2 WAR surplus for the Reds over the life of the extension.
http://www.redreporter.com/2009/12/19/1209173/the-rolen-extension-by-the-numbers
Depending on what you do with fielding, this can move up or down a bit. But I think it's certainly no worse than market-even.
-j
Yeah, I'd love to be able to offer an interdisciplinary sabermetrics minor some day. :) I actually think it could be a big draw from the university (we're small, so a few extra students a year is a big deal). Might have some trouble getting it approved by my chair, however--something about them hiring me in to teach biology, not baseball. :)
The reading list is obviously much too big for one class. My goal in making it, however, is to be able to give a topic list to the students early in the semester and allow them to choose which specific topics they'd most like to target. The reading list will let me quickly generate a reading assignment from those selections without having to do much background research at that moment. Semesters get busy, and I want this class to be awesome...hence the planning.
Thanks for the link!
-j
@Nick/5,
I think my comment was more a counter to the argument that is being made elsewhere that, because something is peer reviewed, it's of high quality. All too often, I'll read a paper from my field that has been peer-reviewed by people within my field and I'll end up asking "how the heck did this get published?" I'm sure it's the same in economics. I think it's disingenuous for any academic to hold up the process of peer review as a shield against criticism, because we all know that it's nothing more than an imperfect filter.
-j
Not much to add to the paper critiques.
But regarding peer review: it's an important process in academia, and it does, on balance, do a good job of improving papers and keeping some of the worst stuff out of press. My most recent submission, for example, received a lot of very constructive but nonetheless damaging criticism that, if it doesn't kill it, will make the paper much stronger the next time I submit it for publication.
But it's nonetheless the case that a lot of crap gets through the filter. Most journal clubs I've been a part of are basically about tearing papers to shreds. The fact that something has been peer reviewed doesn't mean that it's perfect, nor that it's beyond reproach. Really, it just means that you got at least one of the two referees, plus the editor, to buy into the paper.
As has been pointed out many times on this blog and elsewhere, the serious amateur baseball research community can do a superb job of peer review. It's different in flavor to what happens in academia, but from where I sit it sometimes works even better.
-j
Hanigan's also a heck of a defensive player, based on 2009, so yes, I'd rate him above Hernandez on the depth chart.
You need more than one catcher, though. Hanigan's a fine player, but most catchers won't be 85% players. I'd prefer that Hanigan play more than Hernandez, but you can do worse than a Hanigan/Hernandez tandem.
-j
Fairly minor move, but the Reds re-sign Ramon Hernandez for $3M in 2010. Option for $3.25 in 2011 if he's a 74% playing time guy in 2010, which seems unlikely. They also had to pay a $1M buyout to get out of his last contract, so effectively they're paying $4M in 2010, which is worth somewhere around 0.9 wins.
Hitting: Rally has him at -9 RAA/150G, but 54% playing time. Pro-rated, that's -0.6 wins or so. ZiPS is similar in both rate stats and playing time.
Fielding: Fans have him straight-up average. Catching stat based on SB/PB/WP/E rates puts him right about average as well based on the last three years of data. I call him average.
Position adjustment + replacement is +1.25 wins and +2.25 wins (I think Rally's baseline is 2.25 wins across the board compared to his R150 number..?). Prorated, that's +1.9 wins.
So: -0.6 + 0 + 1.6 = +1-1.5 WAR in 2010. Seems somewhere between fair and a modest bargain for the Reds.
-j
Something interesting with SS's.
http://www.tangotiger.net/scout/index6.php?prim_fld_cd=6
Jack Wilson was rated by both PIT and SEA fans. Average scores as you're reporting them are 4.38 & 4.36.
Orlando Cabrera was rated by both OAK and MIN fans. Average scores as you're reporting them are 3.33 & 3.28.
In both cases, they show up right next to each other in the overall SS rankings. And their individual skill ratings track extremely well (e.g. Jack Wilson's sprint speed vs. catching scores).
So, either we have the same fans voting on each player twice, or the FSR is apparently quite repeatable on individual players (or at least these individual SS's).
-j
No question that real-world knowledge of projected playing time are a huge part of success here.
As far as systems using some kind of algorithm to forecast playing time, though...is CHONE showing up the best of those, at least in the head-to-head competitions? It looks that way to me, though I don't know all of the systems.
-j
And, generally speaking, catchers with reputations for great arms (e.g. I-Rod as a young catcher) have awesome runs saved numbers, despite the fact that "no one" ran on them. It seems to work well, at least qualitatively.
-j
@Aaron/4, slyde (at redreporter) and chuckb (at BtB) did this earlier this summer, referring to it as "rep runs." I've never been comfortable with it, though. If a team is running on a catcher, but they're not being successful above the break-even point, it's actually to the catcher's team's advantage that this team is running. Running or not running is sort of irrelevant in my view, the question is whether they are successful or not when they do run.
I'm willing to be wrong about this, but so far I haven't seen an argument for reputation runs saved that makes sense to me.
-j
I think the formula devil fingers was using in that case came from my post:
http://www.basement-dwellers.com/2007/11/player-value-part-3c-fielding-catchers.html
I agree that it's sort of an odd way to present it--when I went back to this recently to implement the method for another project I did a double-take. I thought I had worked out at the time that the math was equivalent, though, and thus saved a step vs. working it out separately for SB's and CS's.
I don't really have time to look into it now to see what I did to verify this, but Tango's check suggests that it's not equivalent. If so, I'm happy to do it the other way. Makes no real difference to me.
-j
In that case, they need to at least report that subsets of the data were not significant, and demonstrate that the problem was statistical power (which can be specifically reported), not the direction or size of the effect. -j
I'm not in drug testing. But the general guideline according to my training (I'm a biologist) is to decide before the study begins what data you will release in the publication. You don't let the data determine what goes into the paper. Now, it's often the case that things happen and you have to add alternative analyses to address unexpected confounds or surprises. And sometimes it becomes necessary to drop less informative parts of a study for the sake of space or focus in the paper.
But I'm not sure that this is the same thing as happened in this paper. It sounds like their data were noisy, and they chose the analysis that showed the most significant-looking results. That is NEVER supposed to be what determines how you analyse your data. Transformations, model fitting, parametric vs. nonparametric, etc, are all data-driven decisions. But you can't choose which dataset to use based on which one shows the most significant results!
-j
That didn't make sense. Here's what I mean:
Cliff Floyd was paid a $350k premium for being a great clubhouse guy, which is the value of less than a 10th of a win. If he's the best-case premium, that's a lot less of an adjustment than the hit that teams are apparently willing to take to avoid the bad clubhouse guy based on Bradley/Bonds.
-j
I'm reminded of Tango's post on Cliff Floyd earlier this year:
http://www.insidethebook.com/ee/index.php/site/comments/measuring_the_immeasurable/
So, is positive presence worth less than negative presence?
-j
Tango,
Agreed. I'm sure they have mechanisms to put together a "number" or a few "numbers" for a given player. In fact, I'd be surprised if Dan Fox does not generate estimates of overall player value in wins, surplus dollars, etc.
Maybe what Huntington ultimately works with at the end of the day isn't one specific number. But in order to perform well in a trade market--and the Pirates generally seem to--they must have a pretty well developed mechanism of assessing player value...even if it's not as sterile in the end as "surplus $."
-j
So, brainstorming causes of differences:
* WSAB uses a higher baseline, so WAR will give more credit for playing time than WSAB.
* Fielding metrics. This could be huge.
* Position adjustments. I have no idea how WS does this, but I'm sure it's not based on fielding talent disparities.
* Team wins vs. hypothetical wins?
Others?
-j
I'll say "take more often"...because what I do (or would do if I could play, which I can't) is pick one specific location and pitch type and zero in on it, with the exclusion of other potentially hittable pitches. In this case, I'll probably pick a fastball down the middle and take anything else.
-j
David,
Thanks for that! I might have never seen it. I'll give it a read and probably will do a quick write-up on it, as it's old enough that I think most of us will have never seen it.
-j
There's a piece in this month's Baseball Digest in which one of the Atlanta catchers makes exactly this claim--being a catcher, with all of its physical rigors, has a negative effect on your hitting. I remember seeing an interview with Joe Mauer a few years back, I think at BPro, where he makes the same claim.
It's something I'd like to see further research on. For example, does the gap between catcher hitting and other position hitting get worse in the hotter months? Does the gap get larger later in the game (as catchers get tired)? This is on my list to look at. But if someone wants to run with it before I am able to--which might be months/years from now--be my guest. I just want to see the results.
I wonder how good of a hitter Mauer would be if he wasn't catching. :)
-j
Either someone's out to get you... or someone in the IT department just bought some list of common distraction sites or something.
I like the former hypothesis, but I'm the paranoid type.
-j
Time to buy that shiny new domain I've been thinking about.. :)
I'm pretty sure that there are comment feeds as well via blogspot, but that gets clunky.
-j
That is, if a park adds +.01 HR, 3B, 2B, 1B, BB per PA, the net effect is not half as many runs as a park that adds +.02 of those events per PA.
So, only for runs per game do you actually want to use the multiplicative method. For the component stats, the additive method is better.
Well, crap.
So, your recommendation would be to either
a) use additive component factors, plus some kind of adjustment for PA's in hitter vs. pitcher parks.
or
b) convert RAA data to absolute runs, apply the multiplicative park factor, and then convert back to RAA?
Just trying to figure out how to do this in an acceptable way.
-j
Also speaks to Pizza Cutter's semi-recent article about using sabermetrics to influence players on the field. Bannister tried to increase his strikeout rates last year, and succeeded...but the bottom line--runs per 9 innings--wasn't there.
-j
I've long assumed that platoon advantage is a big part of why relievers do better than starters, and thought I'd read confirmation of this, but I don't remember where. I guess the prediction is that this effect would be weakest for long relievers and closers, and largest for middle relief and setup guys...
-j
I might have missed it (or don't remember if it was covered in The Book), but to what extent does the platoon advantage impact the effect Rally documented? Relievers--especially LOOGY's--must be more likely to have a platoon advantage than starters, right?
-j
On the issue of skin tone...why not just measure skin tone directly?
The head-shot photos taken of major league players aren't completely consistent in their exposure, lighting, etc. But my impression is that they're reasonably close. You could sample a 5-pixel by 5-pixel spot on every player's forehead from their headshot, and then just report the average brightness of those pixels. This could be done in Photoshop, GIMP, or I imagine one of you codewizards could put together a quick program to made it reasonably automated. You can find "facepacks" of MLB player faces on some of the baseball sim sites, like those for out of the park baseball. Historical packs are even available, though the consistency of photography of older images will vary a lot.
This won't answer the ethnicity question, but it would give you a quantitative description that has at least something to do with what we perceive as skin tone. I've used similar methods to document the brightness of visual signals in animals.
-j
I try not to get too worked up about it, but my Reds often bat two of their three worst hitting position players in the #1 and #2 slots.
Our manager has stated already this year that when Jerry Hairston isn't in the lineup, we will see Willy Taveras leading off, followed by Alex Gonzalez hitting #2. Otherwise, Hairston hits second.
Way to write off the first inning and maximize PA's for poor hitters.
Like I said, I try not to get too worked up about it given the relatively modest differences over a season. It's astonishing to me, though, that a company spending the amount of money that any ballclub spends on players can be so obviously inefficient.
-j
I love the WBC for many reasons. I love the huge talent differences across clubs, because you get to see teams like the Netherlands pulling massive upsets despite AAA-level (at best) talent. I love that it's a way to learn more about the personal backgrounds of all the players we follow in MLB. And I love the nationalism of the event.
I completely reject the idea that nationalism (actually, I think patriotism is probably a better word for what we're seeing) on the level shown in the WBC is evil. The WBC is all about pride in your country. There's nothing wrong, and a lot right, about that. I wrote when Obama was elected that I felt a genuine since of pride in my country for the first time in a long time. It's made a tangible difference in my attitude toward team USA this go-around. Maybe that's shallow, but that's where I'm at.
I also love to see the patriotism exhibited by the players and fans of other countries. It helps me remember that there is far more to this world than this tiny part of our country where I closet myself. Fans and players of other teams are proud of their own countries, and they should be.
The kind of nationalism we're seeing in this event is not, or at least does not have to be, the same thing as isolationism or exclusionism. It does not mean that you don't respect and admire other countries. It just means you're proud of your own country and the players representing it.
-j
^edit out the "an approach" above. I always regret not proofreading before hitting submit.
Also, if you're interested in seeing more results using that approach, I independently came to virtually the same catcher evaluation procedure here and used that in my WAR stuff I posted all last year:
http://jinaz-reds.blogspot.com/2007/11/player-value-part-3c-fielding-catchers.html
-j
Rally'll have to confirm, but I'm pretty sure that for the WAR stuff, he uses an approach this approach:
http://www.baseballthinkfactory.org/files/primate_studies/discussion/tweaking_zone_rating/
It assesses things that must matter...but leaves a lot of other things that may matter on the sidelines that WOWY would measure.
-j
The Reds are famous for doing it way too late:
Ken Griffey Jr. played CF through the 2006 despite being historically bad there from at least 2004 onward. The move to RF for 2007 has to be one of the most overdue such moves in history. His defense essentially negated his offense for many of his last 4 years with the Reds.
Edwin Encarnacion is still scheduled to be the Reds' starting third baseman despite 3.5 seasons of being somewhere between bad and terrible there. They have the opportunity to move him to left field this season, but they will not.
The Reds also had a great opportunity to move Adam Dunn to 1B for the 2006 season, but didn't in order to get Scott Hatteberg in the lineup. Hatteberg did have a pair of excellent years with the Reds, but at the time it seemed beyond crazy...
-j
So he's also going to use SFR? That's a big improvement over DT's. Still not as good as what we can do at fangraphs now with wOBA and UZR. But it'll make a huge difference in the arguments we see from BPro fans. Really great news.
-j
It's possible to both respect (or even be in awe of) Bill James as baseball's Darwin, while at the same time be unexcited about and unimpressed with his most recent work.
-j
In Humphrey's study, he tried to get both Shane and MGL to use the same engine as best he could. Probably wasn't perfect, but it was close. I agree, this is a tighter comparison, but I think it's been pretty clear for a while now that STATS and BIS have massive disagreements.
In any case, at least now if there were any doubts before, they surely must be placated with this new comparison.
I'm just going to keep on averaging--but now I can use Fangraphs' UZR data instead of RZR, which is really nice. Say "bye bye" to the OOZ denominator problem.
I also completely support the bUZR and sUZR notation.
-j
Let me add to the chorus of "thank you"'s to MGL for working to get this integrated to Fangraphs. And also to David Appleman for continuing to produce such an innovative and important site. Now he just needs to start calculating WAR based on his linear weights and UZR fielding values!
I will say that I'm surprised at the apparent surprise here of a lack of agreement between BIS and STATS. Michael Humphreys found this same thing in 2007, with MGL and David Pinto's help:
http://www.hardballtimes.com/main/article/ghosts-in-the-outfield/
And my quick'n'dirty correlation matrix between different fielding systems had similar findings:
http://jinaz-reds.blogspot.com/2007/10/player-value-part-3b-comparing-of.html
FWIW, Fans Scouting Report agreed with BIS statistics slightly better than it agreed with STATS statistics. And in Humphrey's study, his own stat, DRA, correlated better to BIS data than STATS data. So I think we'd be justified in favoring the BIS data.
Nevertheless, I continue think that our best bet, as Rally has advocated for a long time, is to average statistics from at least these two sources (using the best engine we can in each case--now it's UZR for BIS data and probably also for STATS data).
-j
I think the big assumption here is that Silver is, in fact, running a fair and accurate transcript of the conversation. He states that there were a few ad hominum exchanges that he excised. I just wonder if their inclusion would change our perspective on the interview (even if they are vulgar). I also wonder whether Nate is being accurate in depicting the way he asked his specific questions. For example, is it possible that Ziegler's being accurately quoted (by most accounts, he's a major ass), but that Silver himself isn't?
The problem here is that, even though I generally agree with him most of the time, Silver is not an unbiased reporter in this case. He is part of the dispute, clearly on one side of the matter and not the other. As such, just providing a text transcript, rather than a recording or something, makes me uncomfortable...especially given that it makes the guy look so terrible. Not saying that Nate is being dishonest here--my guess is that he is not--but still, it makes me uncomfortable.
I also agree with MGL that the senator questions at the end were in poor taste and unfortunately indicate a specific agenda on Nate's part that again suggests bias.
-j
Frankly, my brain's not up to that stuff tonight, so I might be missing something. I'll try to find time to read through the other thread tomorrow.
But I used outs as my denominator when calculating runs per game. I then compare a player's runs per game to a baseline (average or some fraction of average for replacement level--it varies by league) to calculate RAA or RAR.
I use outs because I was using absolute linear weights and not relative linear weights. They do not include the full impact of outs, and therefore it's important to measure playing time in terms of outs instead of PA's. I'm not sure if that's what you're referring to or not, Colin, because I didn't keep up with that prior discussion. But I was under the impression that this was the correct methodology...PA's are never actually used in my estimations of R/G, RAA, or RAR.
So in tango's question above, 100 absolute BsR (as I calculate them) in 400 outs would result in 100 / 400 * 26.25 outs/g = 6.6 runs per game. And 100 absolute BsR in 350 outs would result in 100 / 350 * 26.25 outs/g = 7.5 runs per game.
To convert those to RAR, I do this:
(6.6 r/g - K * Lg) / 26.25 * outs = RAR
where K = your replacement level coefficient (I use 0.72 for the AL and 0.77 for the NL IIRC) and Lg = league average runs per game. For Lg, I use league average for all position players rather than overall r/g because I don't like to compare my position player hitters to a group that includes pitcher hitters.
-j
@terpsfan, I'm using Patriot's spreadsheet but not his base runs equation. I used Tango's base runs equation (variables culled a bit to match my dataset), plugged it into Patriot's spreadsheet, and then forced the base runs equation to match 2003-2007 MLB totals. The main reason I use his spreadsheet is that it makes extracting the linear weights from the base runs equation automatic.
I do not include SF's except to increase the number of batted outs above what AB's would suggest. GDP's are included, though I see your point on opportunities...I'll think on it, though I like knowing that additional outs were created. That would seem important to getting league-wide numbers to match up to reality.
As for different equations for different leagues, while it may be "better," in my experience it doesn't matter much. It's sort of like using team-specific linear weights--there are minor differences in terms of the actual results. And, when I was setting this up, I judged that it just wasn't worth the effort to use different equations for different leagues. I do, however, have an adjustment to replacement level depending on league.
One can argue on these same lines that I shouldn't bother doing custom linear weights at all. But given that I'm using a different dataset than Tango used, and especially that I have different variables and perhaps a slightly different model (again, not including things like ROE's and such), I thought it was worth doing. Besides, as an intellectual exercise, it was good for me to learn how to do it so that I understood what was going on under the hood.
The specific equations I'm using are laid out in the post linked in my name, if you're interested. As far as I can remember, those are the equations I currently am using in my spreadsheet.
@Tango, I'm not sure what you mean by offensive numbers. You mean lwts? r/g? RAR? I'm guessing you mean RAR, because that's what Sky described as offense? In any case, I'll have to get back to you on it because I need to run. The equations I'm using are in the link, though, if you want to see what I'm doing.
Thanks,
Justin
Methods:
I use Patriot's base runs spreadsheet to force a base runs equation that uses Tango's coefficients (Base runs explained) to match 2003-2007 MLB data (it adjusts the B terms up or down to match the numbers). Those equations are directly used for pitchers. For hitters, I extract linear weights from that base runs equation (again, using Patriot's spreadsheet, which uses calculus instead of the +1 method to do this).
I actually don't do team-level linear weights, because a) I'm interested in comparing players across teams and therefore it makes more sense to me to use league-level linear weights, and b) it just doesn't make enough of a difference to be worth the massive increased complexity in the spreadsheet to have team-dependent linear weights. We're talking fractions of runs, at worst.
The resulting linear weights typically have larger values for individual offensive events (single = 0.51 runs instead of 0.46), and larger values for outs (-0.099 runs vs. -0.098...I'm using lwts_RC) than are reported in Tango's base runs table. I've always figured this was due to some combination of a higher runs environment over the past several years (2003-2007) as well as the fact that I'm not including all the terms in my model that Tango does (THT doesn't report ROE's, for example), and so the missing terms' effects are generated via up-weighting correlated offensive events).
The reason I don't go with B-Ref's data, which does report ROE's, is that THT's fielding data is nicely detailed (in addition to being the only source of RZR data) and is easier to pull into a spreadsheet than B-ref's. And so I use their hitting data because the names all match up perfectly. The only source I use other than THT is ESPN for the ZR data, and there are occasional issues with names not matching up between the two datasets.
-j
@MGL, yes, each position at which a player plays is pro-rated for the position adjustments, based on innings. This unfortunately has the exception of DH's, for which I don't even get games played as DH info from my main source (Hardball Times data pages). This messes up a few guys, like Jack Cust, pretty severely. I don't have a good way around it aside from manual intervention.
But if a guy spends 100 innings at 1B, 300 innings at SS, and 500 innings at 2B, those position adjustments will be assigned based on innings each position and then summed up to get the overall position adjustment you see displayed in those tables.
Also, I do list primary position on the original data tables that Sky is pulling from. Click on my name to get to that spreadsheet. I probably could include all the other positions, but that's a relatively low priority item for me compared to some of the other adjustments I want to make. And given that it's all excel based, it might be a bit of a pain to get automated (though I have some idea about how to do it...).
-j
Just thought I'd say thanks to Sky for running this series. I had planned to do something similar for a while and publish it at THT, but I'm still buried by work and such. Sky's series gave the data a proper vetting (and good visibility to boot). And he did a nice job of pointing out places where the data were likely misleading or prone to misinterpretation.
One thing I will say in response to Tango's comments: part of the reason for only showing the columns we did was that further detail (e.g. showing park factors, league adjustments, etc) is that it might blind people with numbers. Keeping it as simple as possible -- offense + fielding + posadj -- helps keep this approachable. If anyone wants the spreadsheet so they can pick apart the methods, I have no problem sharing it (with minor conditions). Just fire me an e-mail. Methods were also laid out on my blog in my player value series last offseason, and I've tried to stick to those as much as possible. They're built upon Patriot's and Tango's work, mostly.
-j
I hadn't even noticed that Prop 8 passed until now. Like a lot of you, I'm pretty surprised and a bit dismayed. But I guess social politics haven't really changed--it's really just the economy that has changed.
I think that the goal for those of us who think that homosexuals are deserving of decency should be securing specific rights for same-sex couples. Hospital visitation, inheritance, custody, tax benefits, health insurance benefits, etc.
The country clearly isn't ready to condone the word "marriage." And that sucks. But at least we can work toward securing specific rights for same-sex couples to gain some measure of equality. It may be "separate but equal," and therefore not truly equal. But it may serve as a stop-gap until, as Craig implied, the opposition either changes their minds or dies off.
-j
Also FWIW, Rally, I read it this morning and saved it in bloglines for a subsequent link dump (whenever I get around to doing one). It's nice work, and would give me an opportunity to plug your essentially one of a kind defensive projections as well.
As for the comments on your moneyball piece, I think you can blame studes and his link at THT for that! :)
-j
wow, that last sentence didn't make much sense. Should read:
though I imagine it’s based on some combination of past usage of the specific player and the historical usage of comparable players...with some manual tweaking if needed.
Also, 4/mgl, while I don't know about specifics, PECOTA (at least) does include an adjustment based on whether a player was pitching in the past as a starter or reliever. It was implemented and discussed a few years back (maybe in the 2006 BPro annual?). Not sure what's used for the projections, though I imagine it's based on some combination of past using of the specific player and the history usage of comparable players...with some manual tweaking if needed.
-j
Hi Tango,
Thanks for thinking about this problem, as it is something that I essentially punted on. Yours is a nice workaround, and I agree is much better than just forcing someone into one category or another.
I'll probably try to institute this adjustment next time I post my numbers. It could potentially make a big difference for someone who had a substantial number of starts and yet still fell below my starting pitcher criteria (15 starts or 50%+ of games as a starter iirc).
-j
Part of it's personal preference. I don't like dealing in numbers where the range of values for most players is 1-5 or so. I find it easier to think about a compare players using numbers that vary from 10-50. Small headed, I guess.
Also, the conversion from runs to wins is just an approximation in my methods (everything would be converted to runs first, and then to wins), and therefore just adds another layer of uncertainty. People have enough trouble understanding where I'm getting the runs data from, especially (for whatever reason) with fielding. Explaining the 1 win equals average total runs per game approximation just makes it more complicated, and arguably makes the meaning of the data less precise. So I personally just prefer to just use runs.
You can always divide by 10 in your head to convert to wins, of course. :)
-j
Thanks for the link, Tango--there's little I've had time to do lately, but at the least I can post these data. I'm sure the methods behind them aren't perfect, but I think they're pretty good.
It does seem that I have DH's too high--they were rated at -15 runs/season. I'll switch to -17.5 runs in the next update. Not that big of a difference. I still have some other things to do as well before I consider these things "final," like using custom linear weights that include the 2008 season, and using patriot's park factors.
-j
Well, it all comes down to the average plays per unit estimate of opportunities, where unit is either BIZ or innings. You (or I, at least) calculate this separately for each position, so the decreased number of chances for a 2B will be reflected in the decreased average plays per unit no matter which unit I use.
My rationale for using BIZ has always been that it seemed more likely to reflect the gb/fb or left/right peculiarities of a team's pitching staff than simply using innings played. But it also might be the case that you get an inverse correlation, because a ball in zone will no longer be available to be a ball out of zone (if that makes sense).
-j
Good stuff, Colin. I haven't noticed too much of a difference between what I post (which uses OOZ/BIZ) and what Rally posts (OOZ/Inn), but maybe I haven't checked closely enough. If both you and he favor that approach, it might be time for me to switch over to Rally's approach for individual fielders.
-j
I'm not sure where else to put this, but Sal's version of Marcel appeared in an article in the Cincinnati Enquirer today to try to understand what (if anything) we can take from Chris Dickerson's performance.
http://news.cincinnati.com/apps/pbcs.dll/article?AID=/20080906/SPT04/809060374/1071
It's perhaps not the best use of the system...Dickerson's minor league numbers tell us that his performance with the Reds this year is way out of line with his talent.
But still, Marcel mentioned in the paper...
-j
Question about free agent compensation, following on the discussion in #52, #54, and #60...
Griffey's contract has an option for 2009, and therefore the White Sox will (you would think) buy that out at $4 million this offseason. So that's a loss for the White Sox.
However, if they buy out the contract, will they also get the opportunity to offer arbitration and therefore get the free agent compensation? Griffey qualified as a class-A free agent last year according to Elias's widsom (though not by much--click my name for link). But if he's a class-A free agent again this offseason, then the free agent picks would be carry the $10 million value discussed above. The Sox negate a fair bit of that with a signing bonus (right?), but it might help the Sox's cause here... -j
Playing time? Sal's spreadsheet forecasts 654 PA's (based on ytd usage), which he hasn't done since 1999. He's been healthy so far, but he's not a sure bet to last the rest of the season.
-j
Ok, my understanding (still lots of research to do) is that the Reds are sending Griffey + $4 million (the remainder of his 2008 salary) in exchange for two guys who are at best C-level prospects.
So, essentially, the Reds are sending him away to avoid paying his $4 million buyout in 2009. That $4 million should be worth almost a win on the free agent market. Griffey would produce no wins above replacement, with the team or off the team, and his option year is worth $16.5 million. So not paying the option year is the best outcome for the Reds. That they got two scrubbish players (I know nothing about them) is a bonus.
So, at first blush anyway, this is a win for the Reds.
-Justin
Reds fans are holding their breath and hoping this doesn't fall apart. #63 isn't even factoring in Griffey's pro-rated salary over the past few months. Assuming that goes with Griffey....wow.
Word 'round the campfire is that they might get Lance Broadway for him. A 24-year old pitcher who might work as a #5 starter next year is a better return than I could have imagined.
-j
It's more or less irrelevant to your main point (that one person's opinion on someone's defense doesn't matter), but Dunn's fielding numbers have been up a bit this season. I have him as +0.7 runs by ZR, and -4.5 runs by RZR. Taking the average of the two gives -1.9 runs. I've heard anecdotal commentary from people who watch more games than I do indicating that they think he's running a bit better too. I'd like to have some stopwatch data on that, but I'd like a lot of things. He did have a "clean out"-type knee surgery last offseason, so maybe there's something to it.
Anyway, I'll be interested to see how the Fans rate him this fall. I'm still they'll still say he sucks...but perhaps not as much as the past few years? We'll see.
-j
It seems like it's relevant to link to Sal Baxamusa's article on rolling Marcel projections:
http://www.hardballtimes.com/main/article/the-running-of-the-monkeys/
That's probably the best available mechanism by which one can use 2008 stats as part of your analysis of player talent...at least among those that I've seen.
I'd love to see a site like THT or B-Ref formally incorporate his methodology (or Tango's, who has a similar approach as I recall) into a line on their player pages. It would be extremely helpful to see that during the season.
It does look like B-Ref has (with subscription) an "Over past 365 days" split, which is about as close as we can get right now. I'd have to fiddle around and see if I can get it to post all players' stats on one sheet for easy copy 'n pasting.
-j
I hate to say this, but as a Reds fan, I can only sit and hope that TB does this. But, like you, I doubt they will. It would be hard to find a worse value in baseball than Griffey. I'm sure there must be other players out there that are as bad of a value (maybe Schilling this year?), but his combination of terrible defense and declining offensive skills makes him hard to beat.
If the Reds aren't able to trade him this season, I do expect them to let him walk. Problem is, they have to eat a $4 million buyout to do that. But paying $4 million + $400k for a replacement player is better than paying $16.5 million for a replacement player.
-j
Wrote this at ballhype, but I thought I'd copy it here as well...
Neat article, MGL, looking forward to the next part.
Minor comment: seems as though another factor to consider is the quality of the pitcher. I'd guess that the average pitcher in your "runner on 2nd and 3rd, one out" situations is worse than the average pitcher overall, simply because good pitchers don't get into that situation as often. This might be another reason that you're seeing the higher-than-expected wOBA after the intentional walk. And it's another reason to be careful about comparing actual rates to average rates in this situation.
-j
Trev, your instructor should be distributing handouts of her/his powerpoint slides in advance so that people don't have to copy them down. Talk about a waste of class time! Not to mention a massive disruption to any sense of flow or conversation. S/he could be using that time to lead discussions, have students work through problems, etc...
And if you distribute the slides ahead of time, note-taking becomes much more about writing brief comments or jotting down occasional words or phrases to help your understanding and recapture what is said in lecture. And lecture becomes much of an engaging experience where you have time to listen, think, and discuss.
I'd also add that I have no idea how people using laptops can take replicate illustrations on the board...which, at least in a biology class, are frequent and essential. :)
That all said, if I had a student like you who felt his/her ability to learn was being particularly negatively affected by my laptop ban (and I haven't had anyone voice such concerns yet, though I admittedly only adopted this rule this past semester), I'd probably be willing to be flexible...with the understanding that if it gets to be a problem (e.g. I see other people's eyes fixated on that person's screen for minutes at a time), things will have to change. Sitting in the back row might be an option...
-j
Well, in my classes, I don't permit laptops, at least not just for note-taking. Call me a power-monger, or whatever, but I'm pretty firm on this. Here's my rationale:
If the effect of a person surfing the web or what have you was limited to the particular student in question, then I wouldn't care. The student would only be hurting themselves. This is why I don't care about attendance in lecture either.
The problem is that it doesn't just affect that one student. It affects everyone who can see that student's computer screen. If 10% of the student population is surfing the web during class, then it's affecting almost everyone in the classroom. And this, in turn, can cause major problems for any attempts to cultivate a dynamic and engaging learning environment within the classroom. It's disruptive, and like any other disruptive behavior, is completely unacceptable because it impairs the ability of other students to gain what they want to from a class.
Teaching done right is not just about having people pay attention to you. It's about directly engaging the class, cultivating a dialog between you and them, and probably most importantly getting them to think along with you.
This is a hard thing to do. It requires buy-in on the part of the students. And getting this buy-in becomes quite a bit harder when students see other students so obviously not engaged.
Classrooms aren't democracies. And education isn't entertainment. Students are paying money for the opportunity to learn and achieve, and I am not going to permit one student to impair the experience of another student if I can help it.
If it were a less frequent issue, banning laptops wouldn't be necessary. But my experience is that roughly 2/3 of laptop users in classrooms are engaged in activities not related to the lecture/discussion at hand. And, at least in my experience, banning laptops has resulted in a much better learning environment within the classroom. Call me a power-monger if you will. But from my vantage point, cultivating that learning environment is probably the most important part of my job.
And, of course, if students don't like it, they don't have to attend...
-j
I finally figured out the difference between my and Beamer's data--it was a second case in which I just didn't understand how to use his spreadsheet. My results now match is perfectly. So, at some point here, I'm going to go back and re-do the Baker study and see how things fall out.
-j
I'm also seeing this rather late (thanks for the tip, studes, I missed this entire thread). Amazing findings. I had one small question: why did you use OPS? Is it just because it's the only composite statistic reported by all of these systems?
It would be possible to calculate wOBA from data for PECOTA, Marcel, and CHONE (at least). Given how close all of these systems are, I guess it probably doesn't matter. I just hesitate to use OPS given how often folks tend to argue against its use for precision jobs like this.
-j
Great. Looks like I'm doing something wrong with my setup. I wonder if I somehow screwed up the spreadsheet when fiddling around with it over the past few months.
I won't be around much today, but I'll start with the original spreadsheet and try to reconstruct my results with a fresh version. I don't really see what else I could be doing wrong, but clearly there's an issue. -j
Well, I can't test the user issue, but John Beamer will be able to. :) I've sent him copies of my input page, so if I'm screwing up something he'll be able to catch it.
Here's my attempt to replicate your table 63 using the Markov. I used 2007 NL splits by batting position, so the "pitcher" spot includes pinch hitters and Tony LaRussa's #9 hitters. The expectation from that would be that the difference between the best and worst lineup would be less than you found, because "pitchers" are better hitters in this case.
Here are the data. When the pitcher hits 7th, the original #7 and #8 hitters hit 8 & 9 respectively.
No idea what to make of pitchers doing well in the 1 & 2 holes, but the maximum difference between these lineups was 0.055 runs per game. Also, the model is missing high by ~0.3 runs per game. This latter finding is consistent within '07 NL teams as well.
Here's the above work repeated, this time using b-ref's 2007 NL pitcher hitting splits in the pitcher spot, with all other positions the same as above. I expected that the max difference between spots would be closer to what was in your (tango's) study because pitchers are so incompetent in this lineup:
Again, 0.056 difference between the best (pitcher hits #2, for whatever reason) and worst (pitcher hits #3) lineups.
At this point I'm going to step back and see what Beamer finds--if there is a problem with the model itself, then I can't be of much help.
-j
I can copy over run expectancy matrices and state frequency matrices for any lineup I feed into the thing if that helps. I just don't really know what to look for at this point. Beamer has said that he did a fair bit of testing of his model against '07 data. Maybe the first thing to do is ask him replicate what I just did (using your data) and make sure that I'm (again) not doing something patently wrong. We chatted about it last night, though, so I'm pretty confident that I'm doing it properly...
I may also try to use 2007 NL totals for each lineup slot and see how the model does with those totals. That would get away from any peculiarities with these particular players, and SHOULD match up pretty well. Don't have time to do that right now, though...
Any in-depth analysis of the Markov's inner workings is probably going to have to be done by Beamer...though he has offered to send me the "source code" version of the spreadsheet and walk me through it, so maybe I can help at some point after I figure out how it all works. My time's kind of limited though...been spending too much time on this the past few days as it is.
I know there are some things that it doesn't include (like handedness), but I still wouldn't expect the Markov to be as different from your sim as it is. It's a complicated model, and Beamer did a nice job of trying to include a lot of small details in it. Ultimately, it should converge on the sim results (assuming your sim is accurate, and I believe you that you've tested it extensively), especially with a fairly standard set of players. Hopefully we can figure this out, as it would be a great tool to be able to toy around with.
-j
Reposted from my blog:
----------
Ok, I've run MGL's projections through the model. And I'm sure I'm now using the model correctly.
Those projections are much worse than the PECOTAs! But the rank order from this model has Baker actually coming out on top. Here are the results, listed in the same order you listed them:
Baker OD: 4.41 r/g, 715 r/sea
Old Top 3:
Bluzer OD: 4.32 r/g, 700 r/sea, -16 above Baker
Chris-OD2: 4.34 r/g, 703 r/sea, -12 above baker
Pickoff-OD: 4.36 r/g, 706 r/sea, -9 above Baker
Old Bottom 3 (bottom first):
redmanrick-OD: 4.26 r/g, 691 r/sea, -24 above Baker
Brad-OD2: 4.30 r/g, 697 r/sea, -18 above baker
fareast-OD: 4.33 r/g, 701 r/sea, -14 above baker
Mine:
jinaz-OD: 4.39 r/g, 711 r/sea, -4 above Baker
jinaz-OD-exploit: 4.33 r/g, 701 r/sea, -14 above baker
I'm using 2007 #9-slot hitting totals now, which come to a 0.170/0.216/0.250 hitting line. Before I was using pitchers only, but this helps account for the late-inning pinch hitters.
So...Still disagreements between the two systems. These come out much lower than yours (using the same projections, mostly), and with a different rank order. And the range is a bit higher as well, with ~24 runs between the worst and best in the Markov and ~11 runs between the best and worst in your sim.
The rank order differences are just bizarre though. Baker's lineup comes out on top in this Markov, but is doing terribly in your sim. And the worst lineup according to this Markov is the best in your sim...it's almost like they're inverted!
????
-Justin
John Beamer discovered an error in my usage of the model tonight. I'm re-doing the lineups with those modifications, and made it through the opening day lineups this evening. It isn't changing the principle findings thus far, and if anything is resulting in larger gaps between the lineups...
I'm also going to take MGL's projections and run them through the Markov. It will be interesting to see if the differences between the two systems remain.
As far as speed numbers goes, it's restricted to SB rates. GDP numbers are included, but they are estimates based solely on PECOTA projected BIP rates as PECOTA did not actually forecast GDP. In the version of the spreadsheet that Beamer released, all baserunning aside from stolen bases is a constant across all ballplayers...though you can manipulate the heck out of what happens in each situation (I'm leaving it at the default settings).
And no, no differences between LHP and RHP are entered into the model in its present form.
-j
Eric,
I tend to prefer my own numbers to those someone else has calculated...and in the case of FIP, that's particularly the case because I haven't been able to reproduce THT's FIP using their stated equations. One should be able to back-calculate their additive constant and have it be the same across players (at least within a team), but the times I've tried it hasn't worked out. So I'm not honestly sure how they get to their FIP numbers, though mine are usually close to theirs (as they are in this case).
My numbers on Carmona are from my piece on the Indians last year:
http://jinaz-reds.blogspot.com/2007/09/postseason-profile-cleveland-indians.html
I used the FIP equation published on THT's website, and I calculated the coefficient to force FIP=ERA (probably MLB ERA in this case, 'cause I get sloppy by league differences at times). I sometimes also do a park factor correction on the HR totals, but I don't think I did that in this case.
As for Carmona, I think "definitely" is a bit too strong. But in general I agree--as I said, if Marcel knew about DIPS, he would probably be a bit more pessimistic about Carmona than he is. Still, there's only so much you can teach a monkey, eh?
-j
One thing about Carmona: his FIP last year was (by my numbers) 3.83, which may indicate that he got a bit lucky with his 3.03 ERA. BABIP wasn't overly bad at 0.284.
But still...If Marcel understood FIP, he might forecast Carmona a bit more pessimistically. But without running the numbers, I imagine this still works out as, at best, a break-even for Carmona. The Indians know what they're doing...
-j
I'd love to do it, but there's no way I can post once a day. Heck, I'm struggling to post once a week at this point.. Dusty Baker study has been half-written for about a week. Damn dissertation keeps getting in the way of my blogging!
-j
Wow, that's different. Refreshing even. Hell, I'm not even sure if I'm allowed to post pictures to my blog, even if I take them myself at a MLB game:
http://www.red-hot-mama.com/2008/03/04/were-here-were-consuming-information-get-used-to-it/
-j
Should be done by the weekend...
What's interesting, preliminarily, is that it's remarkably hard to beat Dusty Baker's lineup with his players. If you start swapping in Jay Bruce and Joey Votto, you can do it. But Markov rates lineup pretty favorably. It might not be "perfectly" optimized, but somehow the interactions between players seems to work well under Markov. Despite Corey Patterson in the leadoff slot.
-j
I wonder if the titles on the two scoreboards at fangraphs should be reconsidered. As it is, it might give the impression that it's a question of whether Tom Tango's "better" or "smarter" than the fans...which isn't really the point.
I'd suggest "Clutch hitters" vs. "Top hitters" or something like that.
Anyway, just a suggestion.
-Justin
One thing I took from reading the Neyer/James Guide to Pitchers was that the words that pitchers use to describe what they do can be very unreliable in terms of predicting the behavior of those pitches. Pitchers also often seem to throw multiple kinds of individual pitches (like, say, a curve ball). So I wonder how much establishing groups of pitches ahead of time would really be helpful to discrimination...
-j
Here's what I wrote in response to David's post. I think it's relevant to your response as well, which is why I'm reposting here. -j
---
Hi David,
Thanks for the link and thoughts.
I think my critique of the term isn't that it's a made-up word, per se. It's that the term sounds to me, as I put it in my post, a bit "pompous and half-baked." I think this is especially true for those who are disinclined to listen to us. Frankly, I think the term serves to isolate us and our work from the rest of the baseball community (both professional and amateur), which isn't a good thing.
I will say that I certainly don't intend to make a habit of running around the internets critiquing people over the use of this term. It's not THAT big of a deal to me. And I have no illusions that the term is likely to go away, particularly not in response to my little post. But it's something I've been thinking about for several years now, and I decided that it was time to share my opinion on it. Take it for what it's worth.
-Justin
Looking great! If you don't get much Reds traffic, let me know and I'll try to stir up some more. I don't know if there's anyone with a more "unclutch" reputation than Adam Dunn, at least among local fans, so I'd think lots of folks would be ready to vote "against" him, no matter who they're voting for.
...while this won't really matter (no one's going to pick him), Corey Patterson is probably going to be the Reds' centerfielder for at least half of this season. Might be worth adding him if that can be done without difficulty.
Also, when's the deadline for voting? Prior to opening day?
Cheers,
Justin
MGL, I mean inconsistent in how he produces his 15-20 RAR. :) Fans, at least Cincinnati fans, absolutely hated Lohse last year because he pulled a Jekyll and Hyde routine. He pitched some amazing games, but also pitched some miserable ones. Fans just couldn't stand it.
Of course, as Sal B. and David Gassko showed at THT (and I often commented upon last year with respect to Lohse on my blog), inconsistency in a starting pitcher often results in slightly better wins value from his 15-20 RAR than if he'd been perfectly consistent. But apparently most people would rather just have the same result every time out. Or, like you indicated, they see him doing well in some games and can't fathom why he can't do well all of the time.
-j
To be fair to Costas (which we don't really need to be), there is an awful lot of crap out there. A lot of the top-hyped sports articles on Ballhype are often from blogs that focus on sports babes, rumor mongering, etc. And the comments sections attached to local papers often are filled with the rants of the ridiculous.
But the quality stuff isn't rare nor difficult to find. And the best quality stuff is very, very high quality--certainly on par with what you see in peer-reviewed academic journals, much less mainstream media. Costas clearly hasn't looked very deeply into this...and therefore really shouldn't be ripping on something that he hasn't taken the time to even begin to understand.
-j
Not hurt. Apparently, it's a case where he and Boras tried to wait out the market, and the market just moved on. Or something. I just can't believe that someone wouldn't give him at least $6 million for one year.
I wouldn't have minded having him back with the Reds this year. .... though he was inconsistent enough that I doubt many Reds fans would agree with me. -j
I think it's even worse than Costas realizes. Some of these pathetic get-a-life losers are actually getting FEATURED in the local papers, and not just in the comments sections.
Recently
and
Last Summer
Talk about a disaster. Why can't we go back to the day when the only people who could write about a team were card-carrying members of the Baseball Writers Association of America.
-j
Very interesting summary. The growing value disparity between young players and veterans is the biggest thing I've started to come to grips with this offseason. It's a very different game than it was even 10 years ago. Your point about minimum in the NHL is pretty interesting. I'm surprised that this wasn't a bigger issue in the most recent CBA.
....
I know the thread is now de-stickied, but I'd love to hear your thoughts on Kyle Lohse at 4.25/1 yr. Seems like a major negotiation screw-up on Lohse/Boras's part to me, and a small coup by the Cards. ...especially given what happened with Silva a few months back.
-j
I am admittedly just basing it on his 2-year MLB averages, and I am ignoring his terrible 2005 minor league performance. I have him as +2-2.5 WAR hitting, +1 fielding, no position adjustment, and ignoring baserunning aside from stolen bases.
Marcel has him at 0.339 wOBA in 610 PA's, or a dead-on average hitter. So if he plays most of a season, and NL replacement level is -2 WAR, he's essentially a +2 WAR hitter next year. Unless I'm missing something, I might be a tad high, but I don't think I'm crazy-high.
Looking at your numbers, it looks like the difference lies in the fielding estimates. Fans like him, as do BIS-based stats (PMR thinks he was a god last year). STATS Inc stats don't seem to like him as much (at least not ZR), nor do retrosheet-based systems. I tend to side with the Fans when there's a disagreement.
-j
Reports are that Phillips got 4yrs/$27 million, plus an option year.
I had Phillips (post #410) at 3.5 WAR next season, without aging. If we go slightly more pessimistic and assume 0.5 WAR per season aging, that projects him as:
2008: 3.0 WAR
2009: 2.5 WAR
2010: 2.0 WAR
2011: 1.5 WAR
That puts him at 9 WAR over the guaranteed part of his contract. Assuming 10% inflation in $ per WAR ($4.4 million this season), and 40%, 60%, and 80% of free agent value in his three years of arbitration, I get a total predicted contract value of $29.9 million over four years.
To quote Tom Tango, bingo!
-j
I'll echo #6 as something I'd love to see, though Rally's excellent retrosheet fielding numbers make this not quite as important as it would have been a few months back.
Possible related project idea as a #12: historical position adjustments, based on either your or Rally's retrosheet fielding data. I'd be very interested to know the extent to which changes in defensive skill among positions has tracked changes in offensive performance among positions. You could do it decade-by-decade and have fabulous samples to work from.
This would be a real boon for folks like me who are starting to dabble in historical player valuation . It'd also be nice just to have the position adjustments calculated on a system other that UZR, in case UZR handles some positions differently than others. ... I could do this too at some point, but the night class I'm teaching right now is really killing my baseball analysis time. -j
It’s career insurance.
Exactly. If they get severely hurt and/or ill any time over the next several years, they might get next to nothing. That's a catastrophic loss. These deals are essentially money for the rest of their lives, not to mention the lives of their families.
Could they likely get more if they just waited? Sure. But to someone like me, if I'm offered $20 million now, or $40-50 million later two years from now, I'm going to have a hard time turning down the $20 million now, especially if my earning the $50 million requires me to avoid getting injured while doing a physically-intensive task like running around a baseball field 162 games/year.
I'd be set for life with $20 million. And so would my family. Maybe it's not the optimal decision from an economic perspective, but for a lot of guys, I'm sure they feel it's the right decision from a human perspective.
-j
On the list of reasons why a team might overpay for a position (post #452), it seem to me that scarcity of talent should go on that list. For example, the free agent market for starting pitchers is rather weak this offseason, which may result in higher salaries to the passable starters who are available (Silva, Lohse, etc)...not to mention higher trade value for teams willing to deal their starters (Haren, possibly Bedard, etc).
One could argue, of course, that teams should just spend elsewhere, but you can only start 8-9 position players per game, so it may be hard to upgrade substantially after a certain point... -j
I missed that Cano is super 2. If super 2's are at 20%, then a 15.4*0.2 = $3.1 m is a reasonable salary for him.
All of Bobby and Tango's explanations do help. I think Bobby's explanation about people using non-inflation adjusted comparables, and that resulting in a self-reinforcing cycle, makes a lot of sense. I'd really like to do a bit more of a careful study on this before I feel comfortable, but unfortunately I'm swamped right now and just can't do it.
Anyway, Tango's various ideas on how to estimate salaries for these players also make sense and explain why high-end players might not be getting the kind of deals in arbitration that we'd otherwise project them to get. But at the same time, I'm still seeing someone like Phillips priced (by the Reds offer, at least) as a below average player ($2.7 / 0.4 = $6.75). 'Course, maybe they won't win the case...
-j
I've been fiddling with some 1st-year arbitration cases on my blog, and I keep coming out rather high.
2 examples:
Brandon Phillips. Club offers $2.7, Phillips wants $4.2 m. I gave him a simple-minded projection of 2.5 WAR on offense (his 2-year average) and ~+1 wins on defense (fielding metrics disagree on him, fans like him). No position adjustment, no projected aging (he'll be 27), so 3.5 WAR overall. 3.5 WAR is worth $15.4 m as a free agent. Assuming 40% of arbitration value for being a 1st-year arbitration player puts him at $6.2 million. That's much higher than even Phillips asked for.
Robinson Cano. His 3-year hitting average is ~3.0 WAR/season. Fieldingwise, I have him at ~+0.5 wins (fans think he's average, but zr and rzr metrics think he's plus). So again, 3.5 WAR or so. Maybe include a small bump for aging. He's asking $4.5 million, Yankees offered $3.2 m, both well under the $6.2 m mark.
$3 million (about what the clubs are offering these players), if the 40% adjustment for 1st-year eligible players is appropriate, is the equivalent of $7.5 million as a free agent, or 1.5-2 WAR. I have a hard time believing either of those two is an average player--not superstars, but above average.
$4.2 million, what Phillips is asking for, is ~$10.5 million using a 40% discount for 1st-year arbitration players, and that's worth ~2.5 WAR.
So unless I'm messing up something here, I'm wondering whether the 40% discount is too high. I know it matched up well in Wang's recent study, but it's not working well for these arbitration cases (at least). Maybe free agent salary inflation is outpacing 1st-year arbitration inflation? Anyway, feedback welcome.
-j
It'd also be possible to repeat Tango's procedure using Rally's retrosheet-years database, divided into decades perhaps. Not a small undertaking, but it'd be very interesting to see how actual defensive numbers change over time.
-j
mgl/403,
I took Rally's (delightful) comment as an explanation for how Marcel is able to perform so well against more sophisticated systems, year after year.
In this case, he points out that two things effectively canceled each other out when trying to come up with Pena's projection. And that this kind of thing happens often enough that Marcel is pretty close most of the time.
Clearly, there will be cases in which he'll miss because he doesn't consider all available information, or take steps to more carefully interpret the information he has. Your (and others) system will outperform it at those times.
Obviously, you know all of this--but I don't think the comment was directed at you.
-j
Even if it's not the best way to go, using the difference is more straightforward than the ratio for most people. So I'd definitely recommend going with the difference.
Also, I'd just like to suggest that if we want some big name individuals to actually step up and take Phil's bet seriously, we probably want to avoid critiquing their intellect in these threads. :)
-j
I think it's a great project, and hopefully I can send a fair number of Reds watchers over here when the voting commences.
I am curious about what you plan to do about injuries. If a player is hurt or otherwise has limited PA's, that would almost certainly make his top-50 PA's less crucial than the other players, simply due to the small sample you're choosing from. And if clutch guys do better in higher-leverage situations, then lower leverage situations might not be "exciting enough" (or whatever) for them to perform like their most clutchiest selves. So should there be a minimum number of PA's required (e.g. 500?) before you bump down to the next guy on the list?
-j
Tango/2,
It seems as though some teams are doing just that. I've read a fair bit about the Cleveland Indians' system, which apparently makes stride to integrate scouting information in a formal manner into a database. I have to think that the Red Sox are doing similar things, based on all their other innovations. Have you seen anything else reported on these kinds of efforts from these or other teams?
-j
Regarding standards/rigor in baseball operations, here's a question that was asked as part of an application for a job with a major league team as a minor league instruction manager last year (I probably shouldn't comment on how I got it, though I wasn't told to be hush-hush about it either):
Please identify two or three important areas where we would need to make a strategic choice about how we want to play the game. Describe the tradeoffs that would need to be understood, and any analysis that you would recommend doing to help point us in the right direction.
This was really a "separate the men from the boys" sort of question on the application, because it required applicants to describe two sides of an argument without laying out a conviction one way or another. Rather, it required folks to propose what sorts of information they'd need to collect to determine which is the best course of action for the team/organization in question. This is something that someone who isn't used to having to justify their claims with data and/or consider multiple roughly-equal courses of action might struggle with.
Keep in mind that this was an application for a minor league instruction manager position, not a stathead-type position. So, while I might be reading too much from this little window into an MLB team's operations, what I'm seeing is an emphasis on critical thinking and justification from a position that (I imagine) might have traditionally been held by people who weren't required to justify their approaches much beyond "that's what I was taught, and what I've seen works."
-Justin
I like Patriot's because they include regression (using MGL's coefficients, apparently), they're well thought-out, and seem reasonably rigorous without going overboard in trying to control for every little thing. And, they're super-easy to apply to players. -j
I'm going to try to read the paper over lunch. I did want to respond to this comment though, as a card-carrying academic:
Some academics don’t like us. Others though appreciate our no holds barred approach.
Academics are trained to be the harshest and most critical people in the world (or, so we like to think). Speaking at least from personal experience, reviews that I've seen on my own papers, grants, etc, have been far harsher than much of what goes on here. Perhaps the tone is more cordial. For example, I've never been called "stupid" in a review, which is a word that gets thrown around here from time to time (and, I'd add, isn't a particularly effective criticism). But in my experience, reviewers have no problem reporting criticisms that they feel completely undermine a multi-year study and make a paper unpublishable. :)
Therefore, if you've met with resistance in the past from academics with respect to your criticisms, keep in mind that we tend to be quick to defend our work given the rampant criticism we often encounter. Also, it wouldn't surprise me if some academics are more prone to brush off the critiques of "amateurs" simply because they're not also academics.
In the case of the folks that frequent this board, of course, you're probably more qualified to critique a study like this--at least with respect to the baseball elements of it--than the academics who actually reviewed this paper prior to its acceptance in this journal. I'd also add that we should keep in mind that, given that the paper has already been accepted, our comments here are very unlikely to affect the paper itself. But that doesn't mean that they won't consider changes for future work.
-j
Studes,
If players at one position are better overall than players at another position, doesn't this put players at the weaker position at an unfair advantage if you do such an adjustment?
In other words, what's the purpose of those position-adjustments? It's to try to put all positions on an even playing field, right? Because some positions are harder to play, defensively, than others? If there weren't differences among position defensive requirements, you'd stick your best offensive team on the field all the time. So the assumption is that shortstops deserve a boost because they're better defensive players than first basemen.
Ok, in current MLB, second basemen and center fielders hit about the same, with a slight edge to center fielders. And yet, center fielders are also better defenders than second basemen (based on Tango's data, at least if they're right-handed, the average center fielder would be a better than average-second baseman), making them a more talented group of players overall. So why should we give second basemen as much of a boost, if not a greater boost, relative to what we give to center fielders?
-j
By the way jinaz, the Reds have the worst fielding team in baseball, since 2003: -302 runs. Junior is -127 of that. Without Junior, you jump over DRays, Yanks, and Redsox.
LOL. er... ::sob::
Go Reds!
-j
Crap, just noticed that you mentioned arms above. Sorry.
Has anyone actually tried to do this sort of analysis to confirm your approximated 1.5-2 run difference?
-j
Hi Tango,
I continue to think that this is some of the most important work on player valuation being done these days. Bravo for continuing it, even if it didn't result in new insights.
I wonder about the LF/RF differences. UZR only includes information about out rate on fly balls (right?), but MGL's post on Griffey in the sabermetric thread helped me realize how important preventing runner advancement can be to a player's value. Do you think that if "arm" information was added to the fielding ratings for outfielders that RF would come out as a more demanding position than LF?
-Justin
Are you guys bored or fascinated by this? I can’t decide where I am here.
Fascinated. It's really interesting to see where the market "hits" and "misses." The disparity with respect to releivers in particular continues to be amazing to me.
Starter signings like Carlos Silva are also pretty interesting. I wonder if issues of supply also come into play here. After all, there are only so many spots on the roster, so it's not the case that you can always spend in other areas..
-j
Ok, so current/former Reds on those lists:
Reese +10
Conine -12
Encarnacion -14
Dunn -18
Cantu -20
Pena -24
Griffey -31
Yikes. And Reese wasn't even on the team during the period of time sampled.
-j
As I think of it, replacement level production (offense + defense) is the upper end of production that one could reasonably expect to get from a player acquired from the population of freely available talent. Therefore, given that it's a description of a population (or, perhaps, a subset of a population), it seems rather silly to me to set the baseline to the production of a single player on a single team.
Another point, of course, is that even if you're going to define replacement level with a single player, you have to consider both his offense and defense for your baseline to be even remotely relevant. Cust's actual value was lower than what Huckabay indicated because Cust was a below-average defender. I have him at -7 runs or so...not a huge difference, but a difference.
-j
Tango, thanks--I didn't follow this blog particularly well prior to this season, so I missed out on a lot of background work. I'll go check some of that out when I get a chance.
Also, in #4, my last sentence should have read "Though clearly the high "bust" rate is probably the bigger source of the difference." Never type while holding an unrelated conversation with a coworker. :)
-j
I really like Wang's study, because it's so relevant to some of the things I'm fretting about with the Reds talking about shipping off their farm system for Erik Bedard. But I had a question:
As I understand it, WARP has an extremely low baseline for position players because it compares players to "replacement level" hitting AND fielding. So if you're using a 75% of league average replacement level in each, then the replacement PLAYER is set to 0.75*0.75 = 50% of league average.
Does a similar problem exist for pitchers? Or does WARP use a more reasonable baseline for them? Comparing my RAR numbers to WARP for a few pitchers does still show WARP to be rather high, but I've never seen much discussion about WARP for pitchers.
If pitchers are treated more reasonably in WARP, that could be contributing to why pitchers do so much more poorly than hitters. Though clearly the high "bust" rate is probably the bigger source of error.
-j
Mark,
Also knowing that he sucks at public speaking means he’ll try to avoid it as much as possible. He knows he might say something stupid if he says anything at all.
Thing is, I'm not sure that he knows that. I'm not a particularly good off-the-cuff speaker, but I compensate for that by preparing bulleted remarks whenever I have to give some kind of presentation (e.g. when teaching). Krivsky seems to just goes into his press conferences with the idea that he'll speak from the heart. The result are very long ramblings in which he says almost nothing over and over. Just carrying a notecard with some key points written down would help a heck of a lot.
-j
That is pretty refreshing.
On the other end of the spectrum is our guy, Wayne Krivsky, who has to be about the most absurdly secretive GM I've ever encountered. Not to mention someone who's among the worst public speakers...
-j
I don't remember the incident in question (though I do remember one with Dunn after MacKanin took over this year--though Dunn handled his objections very appropriately), but Griffey was fairly bitter about the position change all season. He usually says something like "I'm just player #3." It's clear he doesn't agree with the idea, and that's among the reasons I've long suspected that he'd accept a trade, especially to a contender that would let him play in the outfield (I severely doubt he'd go to DH willingly). Unfortunately, the Reds won't deal him because he's supposedly too much of a draw, especially as he inches toward 600 hr's.
Winning's a pretty good draw too...
-j
Jinaz, there is no chance (well, maybe .1%) in this universe that Griffey is a -7 in fielding.
I dunno, I'm not sure that he isn't a -7 fielder (pre-position adjustment), at least in terms of tracking down fly balls. Fans have him as ~average overall in RF, and PMR has him at ~-10 runs. That said, I'm not sure that he isn't a -15 fielder either.
Your comment about reduced "arm" ratings due to being slow to get to the ball makes a lot of sense, though. Unfortunately, that's not something that I can track at this point, at least not yet.
Anyway, I agree that the Reds would be better off trading him if they possibly could.
-j
MGL, thanks for the breakdown. I don't include baserunning (aside from SB/CS) or throwing arm in my estimates, so that's a big part of our difference. Using your numbers pulls him down to 9 RAR in '07 using my fielding and offensive numbers. The throwing arm is particularly surprising to me, as Fans seem to rate his arm as a touch above average (could be the veteran player effect, of course).
To account for the rest of the 2 wins difference in our estimates, I have Griff at +16 RAA on offense (not sure why we'd differ, but it's only 4 runs), and -7 FRAA in '07 (Fans and ZR put him at about average, RZR has him well below average), which combined is about a win better than you have him in '07. And your offensive projection is 8 runs below your estimate of his '07 production, which accounts for the rest of the difference.
So anyway, that explains why you and I had such a big discrepancy. Probably didn't bother you much, but it bothered me! :)
-j
Hmm, I had Griffey at about 26 runs above replacement this past season (hitting + fielding + position adjustment).
http://jinaz-reds.blogspot.com/2007/11/player-value-part-4-position-player.html
Moving to right field helped him a great deal this year, as did the return of his on base percentage.
Granted, my fielding estimates are a bit bastardized (I used a weighted mean of RZR, ZR, and Fans to get that number--I'm planning to substitute PMR for RZR, but that will just help Griffey). But I'd be surprised if they're off by 25-some runs. He may decline a bit next season, but I'd be surprised if he goes below replacement-level. -j
Mark,
I just made a post on my blog that tries to ballpark what his salary "should be" using Tango's methods. I'm sort of new to thinking about contract values in a rigorous way, but my most optimistic estimate is that Cordero has averaged about 1.4 WAR over the past three seasons. That would put him at just $6.5 million on a one-year deal, which is a heck of a lot less than the $11.5 million/season he's getting over four years with the Reds... And that's not even accounting for the age-related dropoff you have to expect from him.
Here's my post on Cordero, if you're interested:
http://jinaz-reds.blogspot.com/2007/11/reds-sign-francisco-cordero-probably.html
As a Reds fan, I'm excited to have the help in the bullpen... but yikes. I hope my numbers are massively screwed up somehow, but I unfortunately think they're probably pretty close.
-j
I had the same question as Rally. I like the idea of using total balls in play - BIZ - non-zone-outs to get a better measure of opportunities for OOZ plays, but I don't quite see how you can distribute that to individual fielders beyond looking at BIZ distribution around the field and basing on that.
Maybe doing something like that is still better than just using BIZ or (as Rally does) innings in the denominator for OOZ, but I'd have to play around with the data.
-j
#34, That was Steve PHILLIPS! Just take the opposite of whatever he says and you pretty much can’t go wrong.
LOL! Yeah, that's about right. I still try to keep an open (yet critical) mind about stuff he says--thanks to you and Rally for taking a look.
I have to say, though, I'm getting incredibly tired of his constant concern about how "into it" the fans are at games. I just can't imagine that has a significant impact on anything except maybe communication among fielders on pop-ups.
-j
Speaking of defensive park factors...
Listening to the Col/Phi game right now. Steve Phillips just commented that an outfielder (I think it was Victorino) had an advantage in his home park because he knows the dimensions and therefore knows how much room he has and where balls will land. The prediction from this idea would be that the average park should have a positive outfield fielding park factor, at least based on home team performance only (i.e. ignoring visitor defenders).
Anyone ever looked at this? Just curious. :)
-j
Assuming the correlations reported are correct, we're looking at:
r=0.588 for previous year
r=0.636 for current year
r=0.651 for last two years
r=0.666 for last hree years
Granted, the three-year data are better. I'm not really disputing that. But how much better? An improvement in the correlation of 0.03 seems like a minor improvement to me. In fact, I'm surprised how small of an improvement we're seeing here.
To put it another way, you claim that 0.588 is "not too much different" from 0.636. So what's the motivation to go to 0.651, or to 0.666, when those are smaller jumps than 0.588-->0.636?
Just playing devil's advocate. Mostly. I have recently posted some postseason team profiles that include only '07 stats, mostly because I can get them quickly. When evaluating the individual players in the profiles, I take a look at their previous season's stats, as well as things like babip, props, fip, etc, that can give indications of lucky/unlucky performances in the current season. It's perhaps less objective than three-year weighted and regressed averages, but it's less work and probably comes to similar conclusions most of the time.
-j
Rally/19, that's awesome!
Dave/20,
Anyway, getting back to Rally’s point, it seems clear that the OOZ plays are the difference. All eight guys with 70+ OOZ plays by BIS data are ranked massively better by RZR than Stats ZR.
This is probably due to how OOZ plays are handled in STATS Inc's zone rating. They calculate it as (plays+ooz)/(biz+ooz). This massively devalues OOZ plays. The approach I used is basically (plays/biz) + (ooz/biz), which is the same as (plays+ooz)/biz.
I compared these approaches here last spring using the "raw" THT data:
http://jinaz-reds.blogspot.com/2007/03/how-should-we-calculate-zr.html
Including OOZ in the denominator is results in almost exactly the same estimates as leaving OOZ plays out altogether. Furthermore, I did some later work:
http://jinaz-reds.blogspot.com/2007/03/how-should-we-calculate-zone-rating.html
...that indicated that a 1:1 weighting of BIZ and OOZ provided the best match to PMR at all positions except 3B. That, of course, doesn't mean it's the right way to do it. Just that it's consistent.
I guess we could exclude OOZ plays altogether from outfielders because of the problems associated with ball-hogging. But I tend to think that they provide a lot of useful information, so I'm hesitant to do this.
For example, Griffey is rated as an average fielder in RF if you look only at balls in zone. It's the out of zone plays where he's well below average. Given his performance in CF the past several years, I tend to think that a below-average rating in right field is the more correct conclusion, and you only get that by including ooz information (this also conforms to UZR ratings).
-j
John Dewan published BIS +/- leaders & trailers at shortstop last week at Stat of the Week. Thought they'd be interesting for comparison:
Tulowitzki +34
McDonald +26
Vizquel +19
Bartlett +18
Pena +18
Eckstein -15
Young -15
Harris -19
Ramirez -35
Jeter -35
Tulowitzki, Visquel Pena, & Bartlett all show up on MGL's top-3 lists, while Jeter, Young, Ramirez, and Eckstein all show up on the bottom-3 lists, so there's good agreement overall.
The simple THT+- conversions I did at shortstop had a correlation of 0.95 with Dewan's data (biggest discrepancy was Harris). RZR, of course, is based on the same raw data as Dewan's more advanced +-, so you'd expect a fairly high correlation. But I was encouraged by that.
THT vs. UZR tend to have weaker correlations with one another based on past data, which is discouraging. But as Michael Humphrey's study at THT showed, there seem to be differences in the data provided by BIS and STATS.
-j
Wow. Why aren't all teams doing this sort of thing with all of their young pitchers on a daily basis? Seems like an awesome way to help prevent (and get early detection of) injury, which I'd think would be worth the cost of deploying this kind of system.
I would love to see what 2-3 years of collecting this sort of data on all players within a team's system would tell us about pitcher usage, how pitchers vary in their resilience, etc.
-j
Did a quick google search -- there are articles and editorials about this case dating back to late July. Apparently the initial publicity didn't result in the dismissal of the case that it should have.
It's a shame that the actual arrest happened off-camera. Video of the policeman tackling the woman as she was trying to borrow a cell phone would have resulted in a heck of a lot more attention that this case has gotten thus far.
The conflict of interest at the prosecutor's office is mind-boggling. -j
Franklin's 3.57 ERA season in 2003 is often cited as one of the great fluke seasons in recent years. He had an 0.235 BABIP and a 5.21 FIP that year (4.2 k/9, 2.6 bb/9, 1.44 hr/9). Some of that BABIP can be credited to the defense, I'm sure, but not all of it. -j
The thing you more commonly hear--and I myself have said it--is that you might be willing to give up defense for offense on the corners, but focus on defense up the middle. That seems to be what the M's have done. Obviously it has made things harder for their pitchers, but if the offense is there it might be a smart move..
So I guess my question is whether defense should be weighted differently at different positions. In other words, in a total assessment of a player, do you weight defense as 70% of the value of a ss/2b/cf/c, and 30% of the value of a 1b/3b/rf/lf? Or is a run saved worth the same (or even more?) than a run scored?
-Justin
However, I am surprised they haven’t developed and published their own advanced fielding metric
You'd think that has to be in their pipeline of important things to do soon. At this point, their continued reliance on Davenport's fielding translations for present-day fielding evaluations makes it hard to take a lot of their work seriously--including other important stats that rely on it. -j
Great to hear a) that THT will start streaming their ZR data soon, and b) that we can expect a fielding bible in 2008. Very exciting. I'd also gladly purchase a fielding bible each year. -j
In that case, we’re better off having a bibliography page online. It maintains its relevancy, and would be read by far more people.
That would be a fantastic resource for those of us who are still learning the basics of the literature. -j
Harang makes a lot of sense. Over the last two seasons, he has been a solid if not very good pitcher on the Reds' otherwise absolutely miserable pitching staff (see especially 2005). If I understand your methodology, the awfulness of the Reds' pitching from '04-'06 should give a quality pitcher like Harang an extra bonus relative to players on other teams. If he was part of an otherwise-average pitching staff, he wouldn't show up as brightly as he does here.
-j
Maybe this is going to sound too political, but....
I visited that site some time ago, and it declared that George W. Bush was my most compatible celebrity, with the highest ratings on intellect!
I screamed and clicked away from that site as quickly as I could, vowing never to return again. :)
-j
That would be particularly interesting if we looked at it in terms of effectiveness after throwing a large number of pitches to a single batter. You often hear announcers go on about how a terrific at-bat (defined by seeing a large number of pitches) tires out a pitcher either mentally or physically (or both), allowing subsequent batters to get him.
The problem is controlling for other factors...like the probable case that pitchers who can't get a batter out and thus throw a large number of pitches aren't likely to be on top of their game. I'm not sure how to approach it. -j
Junior has often (at least for the past 3 years) been backed up in CF by Ryan Freel, who is a plus defender, especially in the outfield. That, coupled with Griffey's misery as a defender, makes a pretty big differential... -j
The one difference between a the gambler's fallacy and this situation is that this situation is not a random process. Throwing a strike is a difficult thing, and if a pitcher is struggling badly with his control (which was the case in this situation), then it might, in fact, be more likely that the next pitch will be a ball. The context of the situation does matter. It is not the same thing as a coin flip, which is always random.
If a pitcher is struggling with control, my take advice is to look for one specific pitch in one specific location, but otherwise lay off it.
But hey, what do I know. :)
-j
- The BIS system is still developing, and the 2006 Zone Ratings were based on different parameters than previous years. John didn’t go back and change the old systems. That’s probably one of the main reasons there’s so much variance between years. John does feel that comparisons for specific players between years is still valid, however.
That's troublesome to me. What do you folks think this means for estimating the expected number of plays per BIZ when looking at this years' stats? I was planning to use the 2004-2006 totals posted by Tangotiger in comment #4, but now I'm wondering if just sticking with 2006 data ratios might be more accurate given the change in the system. Regardless of what I use, it'll have issues... -j
If you have an ipod touch, I think it would work fine(?). I doubt you'd have any luck integrating the in-ipod stopwatch into your scorekeeping, as you can't easily flip between apps. But if you had one in your hand, you could type in the time as a note for later retrieval. That's probably the best you could do w/ it for now. If I was doing anything official, I'd definitely bring a scorebook as a backup. At least that fights the power loss/malfunction issue. As for data loss...you can back up after every game. If you're mid-game and something happens, you're right, this could be bad. Seems pretty reliable, though. Might be worth checking the support forum to see what issues have occurred with the software. They do have some preventive measure suggestions, like clearing out your ram by doing a hard reboot prior to a game (some other apps don't clear out of memory like they should, which can cause a memory crisis for iscore). -j
iScore Review (jinaz) —
Yeah, that was something that really stuck out to me as I was doing it. I'd say that most of my balls in play are right at fielders, in the gaps, or on the lines. Distance-wise, it's either warning track, infield grass, or "medium." Its still useful info, but I'm sure I'm plus/minus 20 feet at best. The other thing I noticed is an explanation for why 90% of all balls hit into play are "medium." Unless it's hit REALLY hard, to the warning track, or is a weak infield hit of some sort, I rarely feel justified marking a ball as anything but hit "medium." I remember Shane Jensen joking in a video seminar once that the batted ball speed data they purchased were just like this. Need that stopwatch data... -j
True talent all-stars (jinaz) —
Oliver and CHONE's fielding projections include minor league data, so I'm not sure that this is true. Also, while it's spread over a bunch of seasons, we have almost a full season's of MLB innings on Torres, and his career UZR/150 across all outfield positions is +22 runs (+20 in CF, where a bit more than half of his innings have been). McCutchen has a similar MLB innings totals, but his career UZR/150 is -6 runs (admittedly all in CF). If I were picking players, I'd certainly take McCutchen over Torres. But Torres might be a poor man's Franklin Gutierrez. Or maybe not so poor man's--both rate as +14 run players vs. other CF's. -j
True talent all-stars (jinaz) —
Post updated. Gonzalez now included, and Steve's UZR projections are now given 50% weight in the fielding calculations.
True talent all-stars (jinaz) —
Sky/7, All of the projections are supposed to match the park environment of the hitter. That's why I park-adjusted the offense RAA numbers. BrianK/6, Torres' line is all fielding. Depending on how real you think it is, it can push his value up or down a lot. As for Gonzalez, that's a screw-up. I don't know how it happened. Complete user error. He is at +41 runs in my spreadsheet, right behind Fielder, 3rd among NL 1B's. I must have accidentally pushed him into the AL group somehow--maybe in anticipation of a trade? :) -j
True talent all-stars (jinaz) —
Aging is part of how we predict future performance. My goal here is to pick the best players. Past performance is part of it. But it needs to be interpreted, regressed, etc. That's what using a rest of season projection does for us. Re: UZR--I'm going to re-do this with Steve's uzr projections for NL tonight, and will use them for AL projections too. -j
True talent all-stars (jinaz) —
Yeah, I don't know how much I "care" about the All Star game. But it's always a good opportunity to take a moment and reflect on the current best players in baseball. So on that level, I like it. I should have caught the Zimmerman fielding thing, but missed it. Caught it for Kelly Johnson. I'm ultimately just not a huge fan of the Oliver/CHONE fielding stats, but they are probably close more often than they completely miss it. Something's better than nothing. Maybe I should pester Steve for his UZR projections. :) -j
The Book - book review (jinaz) —
Regarding application to fantasy: I had no idea how true this was until I started playing fantasy this year for the first time in over a decade. I'm amazed at the number of people who try to play hot streaks and cold streaks on a consistent basis. That, and people who choose who to start based on historical performance against individual teams. Those two things account for about a third of the conversations you see on discussion boards or hear on fantasy podcasts. For the most part, people are just chasing randomness. I assigned several chapters from the book this past year for my baseball class: clutch hitting, hot/cold streaks, and lineups. Most students seemed to do pretty well with it, which says something for how accessible much of it is. These were freshman college students, and often students with little math background. -j
"My stats": Custom Dashboard (jinaz) —
Now if I can just get my dashboard to show up on the iphone app, I'm golden. :)
Superiority of AL over NL (jinaz) —
Mike/6, I'm using essentially an 8 win difference in the BtB power rankings. I boost AL teams by ~4 wins per year and penalize NL teams by ~4 wins per year. As Tango pointed out above, it's actually conservative relative to recent history (~12 win difference), but it makes a big enough difference that I have a hard time boosting it any higher. I get enough hell about it as it is. :) -j
A very good article by Sky A. on batter tendencies (ability to hit the fastball, curve, etc.) (jinaz) —
I'm not a game theory expert by any means. But I produced a very simple game theory model looking at this question to help guide the discussion in my baseball class when we read MGL's fangraphs article on game theory & pitch selection. The model found that with optimal pitch selection, all pitch run values tend to be very similar, but not necessarily identical. Sometimes, it's worth it to occasionally correct throw in an occasional "bad" pitch--even if it's of inferior run value to the worst-case scenario for a "good" pitch--because it makes the good pitch that much better the next time around. It's a marginal effect, and depends on some assumptions. ... but I couldn't get away from it. I try to get it written up as soon as I can so you guys can tell me what's wrong with it. -j
Yahoo fantasy sabr league (jinaz) —
If you use putouts, C's and 1B's will break whatever you try to do. And without putouts, outfielders are nearly worthless. I don't think it's workable. -j
Yahoo fantasy sabr league (jinaz) —
Hi, I just used these linear weights: http://www.tangotiger.net/bsrexpl.html I'm using lwts_RC column since I'm doing things in absolute runs. Since a single is an AB+H, and a double is an AB+H+2B, some combining of these stats is necessary so that the totals come out right. Here are the "combined" linear weight values I'm using, followed by the rounded point values for each term: Event lwts_rc Pts AB -0.1 -1 H 0.563 6 2B 0.287 3 3B 0.57 6 HR 0.939 9 SB 0.193 2 CS -0.282 -3 BB 0.3 3 Hope that helps. -j
Matt on DIPS (jinaz) —
Found it! http://web.archive.org/web/20080112135748/mvn.com/mlb-stats/2008/01/06/on-the-reliability-of-pitching-stats/ Now someone go make tRA* for me, k? :) -j
Matt on DIPS (jinaz) —
Sky, Here's Pizza's hitter article: http://web.archive.org/web/20080102094412/http://mvn.com/mlb-stats/2007/11/14/525600-minutes-how-do-you-measure-a-player-in-a-year/ Assigned it for my class last week. Don't have the pitcher one, though, and that's probably what we need. Easiest way is to find someone who linked to it so we can get the old URL--that makes it easy to find on archive.org. But I haven't had any luck with that. -j
Panas' sabermetric primer book (jinaz) —
Lee also had me read a few sections a while back, especially on catcher defense. I skimmed the rest as well, though, and found it to be a nice, general primer that will get you up to speed on a lot of modern sabermetric work--especially player valuation. Good for him in getting it done! -j
Yahoo fantasy sabr league (jinaz) —
I've been fussing with this literally all day and finally came to something I'm somewhat comfortable with. Since others might be doing the same thing, I thought I'd report back. Here is ultimately what I came up with for pitchers: IP +5 K +2 BB -3 HR -13 SV +6 HD +2 I didn't set out to have those numbers match up to the coefficients in the FIP equation. I started with linear weights and went through a process that was as much guesswork as it was sensical. My plan was to create a DIPSy adjustment of absolute-runs linear weights....but those numbers started out too low, so in desperation I started increasing the positive terms, eliminating anything related to hits...and the result was suddenly something that looks a lot like the FIP equation (whether by coincidence or not). Seems to work pretty well--the rankings of players seem intuitive to me--though I don't think my methods would hold up to much scrutiny. The saves issue is tricky. I hate saves with a passion, but we have nothing else to work with that relates to reliever leverage. This gets elite closers in 2009 equivalent in value to starters like Aaron Harang, Johnny Cueto, Brad Penny, etc. That feels about right to me. I'm throwing setup guys a bone with the +2 holds, but it will take a lot of holds to get anywhere close to a closer's value. ::shrug:: Anyway, the system has good pitchers at 800+ points, great pitchers at 1000+ points, and elite pitchers at 1250+ points. This matches up pretty well with the hitter scoring, which more or less is wRC*10. Based on the number of slots for pitchers (8) vs. position players (9) in my league, I'm crudely estimating a 55%/45% split between hitters and pitchers in terms of team point totals. Not quite the 60/40 Tango's system provides, but it feels close enough to me. What I like about the wRCish system I'm employing is that negative players are hard to come by, so it's always better to have an active player in the lineup than someone who isn't playing at all. Managers in the league will essentially create a replacement baseline by plugging in the best talent they can when their starters go down. And we're still, at least with hitters, tied to something that is somewhat similar to reality. -j
Yahoo fantasy sabr league (jinaz) —
I'm starting a fantasy league along similar lines. I was going to use Tango's point system, but the problem with them is that since they are set to replacement level without a position adjustment, a number of starting SS's and C's show up as negative value players...meaning that, as a fantasy manager, it's more productive to plug in an injured player or demoted AAA player into that slot than start some of these guys. I've decided that the best way to address this is to use a point system that is more set to an absolute runs baseline than a replacement-level baseline. This way, it's the league market that sets up what will be our "replacement level", and it's incumbent on the manager to find players at or above replacement level when they have a player go down to injury (not doing so will have very bad consequences). This was pretty easy to do for hitters. Here are Tango's replacement level points: AB -2 H +6 2B +3 3B +5 HR +8 SB +2 CS -4 BB +3 Here they are in absolute runs-based points (they are just rounded absolute linear weights): AB -1 H +6 2B +3 3B +6 HR +9 SB +2 CS -3 BB +3 There are rounding issues that throw things off, but this more or less will give you points = wRC*10 for hitters. The main difference is an adjustment of the value of an out from -2 to -1 points (this is also seen with the CS). I'm not sure why my triples and HR's also are getting an extra point here--I tried to replicate Tango's work but was getting these same values in those cases as well. Anyway, my problem is that I'm having trouble figuring out how to convert Tango's pitching points into something that mirrors wRC. Here are Tango's points: IP +2 H -0.5 BB -2 K 1 HR -3 2B -0.5 3B -0.5 SV +2 Hold +1 Any ideas how to make this a good approximation for absolute runs? I could probably bump up the point value for innings pitched from +2 to +3 (or should it be +4?), but I'm not sure if that would really do what I want it to. Part of it is that I'm not entirely sure how Tango came up with his framework, so I can't reconstruct it. Advice welcome! Thanks, Justin P.S. If you're interested in my league, there are still ~5 slots open: http://www.redreporter.com/2010/2/12/1308231/sabermetric-fantasy-baseball-anyone Send me an e-mail so I have your contact info if interested. It probably won't be quite as hardcore as ShaneM's (autopick draft, transactions set to weekly), but my hope is that we have a nice balance between competitiveness and time commitments.
Pythag records (jinaz) —
I don't think what I'm doing is necessarily wrong, given that, for example, I'm using DIPS-based pitching. It could be that the slash line is misleading because of BABIP or something and what I'm doing is more indicative of actual performance. It is the case that I'm not applying park factors consistently, because I don't think you can use the same park factors on a DIPS stat as on an overall RC stat like wRC. I'm applying park factors to components going into tRA (or FIP), whereas I'm just doing an overall runs adjustment to the wRC data. It's a fair critique, but I preferred to just use wRC since it was available rather than deal with my own linear weights. Fielding: no regression, but I do average together two fielding estimates. UZR had Seattle at +85 runs, whereas THT's batted ball team fielding stat had them at +61 runs. Average is 73, plus 7 runs for plus catching. So yeah, if you just use UZR + catching (no THT), you save 12 more runs. As for pitchers, I think I'm pretty close to the mark: Actual runs allowed for Seattle was 692. If you park adjust it (again, using PF = 0.98), it moves to 706. Then, add back in the fielding estimate above (+73 runs) and that gives an estimated park neutralish 779 RA by pitchers alone. "My" FIP-Runs estimates 783 RA. Pretty much dead on. I know we're trying to not be wed to runs allowed here, but on average we should do a good job of estimating them. I'm not getting a massive disparity between RA and eRA here with respect to pitcher performance. So, maybe I'm missing on fielding. I think the pitcher estimate is pretty close. My hunch is that another part of this is that the Mariners had two forms of luck cancel here. They allowed a "lucky"-low number of hits allowed (which FIP doesn't track but the slash line does). But that the hits they allowed translated into an "unlucky" number of runs. So, maybe the slash line misleads a little bit too. Just a guess, but it helps explain our disparity here. -j
Pythag records (jinaz) —
Peter/12, Mostly because I also like to look at how teams stack up against one another in the component stats--offense vs. pitching vs. fielding. I agree that if all I was interested in doing was estimating team winning percentage, it wouldn't make much sense to do park adjustments. That said, you could argue that DIPSy stats are inherently park adjusted by themselves (they usually assume a neutral BABIP environment), so perhaps it is worth it to park adjust everything to (try to) make sure everything's compared in a neutral park context. -j
Pythag records (jinaz) —
Ed/10, Pythagorean record basically tells you the winning percentage you'd expect to get based on your team's actual runs scored and runs allowed. It's basically a model of how runs scored and allowed typically convert to wins. Looking at it is a way of getting past some of the timing of when runs are scored that are what ultimately cause differences between actual and pythagorean w%. Many of those timing events are random, though some (like when good relievers are leveraged) probably are not. A component-based approach like Tango, Dave, etc are advocating takes another step back and looks at how well a team performed based on their component statistics. Tango reported slash lines--how we evaluate hitters--at the team level to evaluate offense relative to defense. This gets away from even more of the timing events, like clutch hitting, that affect how components are converted into runs. But again, most of those timing events are fairly random. The result is arguably a better view of how well a team performed than straight-up pythagorean records, much less winning percentage, provide. -j
Pythag records (jinaz) —
Whoops, FIP should have read 4.48. And for some reason, looking back at my spreadsheet, it's now reporting 4.51. I think they're different because I'm now using 2009 HR park factor numbers from Patriot to adjust HR rate, whereas before I was using 2008. Anyway, just wanted to say that if I use the FIP number instead of tRA to figure estimated runs allowed, I get: 783 - 80 runs (fielding) = 703 eRA (I got 731 eRA using tRA & fielding). That's compared to an estimated runs scored of 665 based on wRC and EqBRR (removing steals), with park adjustments. Still puts them a few wins below 0.500, though obviously it puts them closer. I don't know why the slash line you cited wouldn't agree with what I'm doing. Maybe I'm not giving credit for fielding, or there were some "luck" factors that feed into the defensive slash line that aren't accounted for with a DIPS/Fielding approach...? Or it's internal weighting issues within OBP and SLG that aren't borne out in wRC. -j
Pythag records (jinaz) —
Tango/7, I'm not sure if that was a response to me or not. But just in case, to be clear, the number I cited is based on park adjusted wRC, BPro baserunning, a DIPSy pitching stat, and fielding (including catchers). No actual runs scored or allowed are used; it's all component-based estimates of RS and RA fed into Pythagenpat. Ultimately, what you're talking about is the entire motivation behind that power ranking project. Offense (park adjusted, including EqBRR baserunning) I have SEA at wOBA = 0.319. By tERA I have pitchers at 4.66 (though FIP = 4.38--I do some park adjustments on FIP so it may differ from fangraphs...next year I'll probably use xFIP instead of this home brew tRA of mine because I trust it more). Fielding, including catching, I have at +80 runs, which is way over the 2nd-ranked Reds at +59 runs. -j
Pythag records (jinaz) —
I had them as a 0.461 team based on component winning percentage last season: http://www.beyondtheboxscore.com/2009/10/11/1079698/btb-power-rankings-end-of-2009 (Converting Runs to Wins table) Adding in the league adjustment put them at 0.487. 2nd worst offense in the AL, 3rd worst pitching, but easily the best fielding. If I would have used FIP instead of tRA, pitching would instead have come in 7th-worst in the AL. -j
Colin's fielding metric, part 1 (jinaz) —
Mike/25, Egg on my face, I guess. I completely forgot that you nominated it, and in retrospect I probably should have seconded it since no one else did. I think I ultimately didn't because I was trying to avoid doing nominations or seconds in categories in which we already had large numbers of nominations. At the time it was submitted, we already had 11 (though one was the cheeseburger thing and we opted to omit it, and two were for Allen and we made him pick one), and I was hoping to keep the number around 10 to keep things manageable. But it was deserving of a nomination. Good work by Peter. Again, the main point is that the gameday work gives us a check on the BIS data, which is a really valuable thing to have. If Colin's work goes well and his metric seems to behave well--and given his track record, odds are good that it will--then I'll be very happy to average his numbers with UZR (and maybe TZ and Fans) to get a nice composite fielding estimate for players. -j
Colin's fielding metric, part 1 (jinaz) —
Nick/23, Yes, Peter is the main person I was referencing who has used gameday to build a fielding metric (and come to think of it, why didn't we get that project nominated for a Saber??). My point was that Colin's project, once complete, will presumably be implemented in BPro's statistics pages to give us up to date data on players throughout future seasons. Given the massive differences between sUZR and bUZR (and thus our awareness of how massively those two data sources differ), having another good-quality fielding metric available like this for all current players that uses a third data source will be very helpful. -j
Colin's fielding metric, part 1 (jinaz) —
I'm pretty late here, but I just wanted to say that the primary benefit I'm seeing in Colin doing all of this is that we'll ultimately have another data source to compare to the BIS-based data. If we use the ZR conversions as well, then we'd have BIS, Gameday, STATS Inc, and Fan Scouting for any given player. This would go a long way in helping us smooth out problems with the data sources. I know others have used Gameday for fielding before Colin, but it's not something that's easily accessible for all players like bUZR currently is. Looking forward to seeing this get put together. -j
Sabermetric awards (jinaz) —
Here's a hub for all of the award results posts. http://www.beyondtheboxscore.com/2010/2/4/1292810/btb-sabermetric-writing-awards
Is TurboTax a mess? (jinaz) —
This past weekend, my wife and I used the H&R Block software (cd, not online), as we got it from her dad who stumbled upon it for cheap somewhere a few weeks ago. We've always used turbotax in the past, and wouldn't have changed except that this was free. The HR Block software imported last year's turbotax data fine and seemed to do a good job. Our taxes aren't insanely complicated, but we did have child care tax credits, homeowner's insurance, interest on a mortgage, and an energy tax credit (new windows) to deal with. No problems incorporating any of those things into the return. -j
Sabermetric awards (jinaz) —
It was an extremely close vote both internally and externally, but congrats to Victor Wang for winning this category. Very important work for those of us who like to judge player moves by the big clubs. Not to take anything away from Victor (or any of the other nominees), but upon revisiting the top placers for the write-up, I have to say that I was also extremely impressed with Josh Kalk's Injury Zone article. It's one of things that might not currently "work," but has exciting promise and could potentially save careers. I love the idea of a laptop in the dugout that starts flashing warnings when a pitcher's arm starts to encounter trouble. :) -j
Peer review v internet debate (jinaz) —
Here's the updated list: http://www.basement-dwellers.com/2010/01/sabermetric-library-resource.html
How to track a flyball (jinaz) —
There's a good, readable summary of this sort of work in the Psychology of Baseball by Stadler. Less current (though only a few years old), but talks about the competing models. Link to the book in my name. -j
Peer review v internet debate (jinaz) —
Just wanted to say that a big part of the reason that I proposed the sabermetric awards at BtB (results are in, awards write-ups are in progress and should be out next week) was directly related to my feeble efforts to assemble a library of sorts for this baseball class I was prepping for. I was struck at how difficult this was to do. We rarely as a community seem to make a concerted effort to compile our best work, and so I thought an annual "awards" thing of sorts might be a good way to encourage us to do that. Naming a "winner" was always a very secondary goal, but it does make it a bit more fun and gets people interested. This year, my plan is to make monthly posts to help us take note of our favorite studies throughout the year--I think a lot of us had trouble remembering many of the great studies we'd seen over 12 months, so hopefully people will be willing to share their favorites. We could then mine these lists for next years' awards thing. Also, I have added a great deal to my list of sabermetric studies since I originally posted this thread: http://www.beyondtheboxscore.com/2009/12/17/1200459/want-to-help-me-plan-my-baseball I keep it in a google wave right now, but I can post it as a resource somewhere if folks would like me to. -j
Sabermetric Awards: 1. Novel Research Project (jinaz) —
Definitely looks to be a tight race. Currently there are 45 ballots submitted for the first category, and despite the "vote for as many as you like" framework, no study has appeared on more than 26% of the ballots. In fact, there are six studies that are named on between 22-26% of ballots. So yes, I'm not expecting a consensus on several of these categories. But that's ok. We'll still probably crown a "winner," but we'll include all the major vote-getters in the category write-up after voting is complete. Also, folks can continue to use the original project announcement post as a hub (click on my name). I'll add voting threads as they are released. -j
Sabermetric moves of the 2010 pre-season (jinaz) —
I'm interested in folks' perceptions on the Aroldis Chapman signing. It's been hard to get a clear breakdown on the contract, but I THINK it's a for 5 yrs/$25M with a 6th yr/$5 M option. And there are also reports that there are numerous incentives to bring it even higher. Furthermore, at least some parts of the contract will be deferred as far back as 2020. A lot may have to do with how well he ranks as a prospect. Top-10? Top-5? Top-2? -j
The Sabermetric Awards (jinaz) —
I don't want to go over 10 nominations, except maybe for the best writer award where it may be as much a popularity contest as anything else. I think we're ok in most categories, though I'd prefer to have more than four choices as much as possible. Cheers, Justin
The Sabermetric Awards (jinaz) —
Today is the last day to submit & second nominations. Here's a hub post for the day. http://www.beyondtheboxscore.com/2010/1/11/1245198/last-call-for-btb-sabermetric Thanks again for the link. -j
SABR 399 (jinaz) —
Obviously it's a very different course than mine, but it's helpful to see what other people are doing. Nice set of links to quality studies that still could be useful for my stuff. -j
The Sabermetric Awards (jinaz) —
Tango/5, good idea, will do. -j
The Sabermetric Awards (jinaz) —
Thanks for the link! We'll see how this goes. Could be a lot of fun. -j
Psst... wanna work at Baseball Prospectus? (jinaz) —
LJ/14, What I see is BPro realizing that they were becoming irrelevant, and throwing resources behind an effort to bring in some of the best saber talent around. That many of the new hires were on statspeak is a testament to how special that place was for a while. I think BPro should be commended for this move--to me, these guys (Tommy Bennett too) are a major draw. They're getting my subscription money again after the holidays are over. -j
Sabermetric moves of the 2010 pre-season (jinaz) —
Brian, given the lack of SS in the system (unless one believes in Cozart's bat), I tend to think that Frazier would still be at SS (where he started) if the Reds thought he would be anything but a disaster over there. He hasn't played SS above high-A ball. You're using position-specific MLE's on the fielding numbers right? Valaika's still at SS, for example, and few think he will be able to play there. I think Frazier's always been considered a poorer fielder than Valaika--or at best, they are equals. And Bruce isn't half bad in the field. He's not a CF, but he's above average in the corner slot. Both the Fans and UZR said so! :) If he ever figures out how to hit like we thought he would, he'd have a ton of value... -j
Sabermetric moves of the 2010 pre-season (jinaz) —
Brian/171, League-average defense at SS from Frazier might be a stretch based on scouting data: the Reds don't seem to think that he's a viable option at SS. At 2B or 3B, though, I think he's got a shot to be solid enough. He's also apparently fine in a corner outfield slot. I think of him as an average fielder overall: below average at SS, average at 2B/3B, above-average at LF/RF. Francisco...I'd certainly be delighted if he could be an effective player for us, but I'm extremely skeptical despite your projections. I wonder how well a projection system can work on a player as extreme as he is. I honestly expect MLB pitchers to exploit the heck out of his tendency to literally swing at just about anything. As you said, even Frenchy has a higher walk rate--and Frenchy gets a lot more balls in play than Francisco ever has (~13%K rate vs. 25% k-rates if I remember right). He's fascinating, but I'm not banking on much coming from him. -j
Sabermetric moves of the 2010 pre-season (jinaz) —
The only internal option I see as being viably better than replacement at 3B come 2011 is Todd Frazier, and there's a good chance that he may end up as our LF next year instead. And even if he doesn't, having a better-than-replacement internal option is a good thing when you're working with an injury-prone starter like Rolen. There will be lots of opportunities for bench players to impact games. The other internal person that people are talking about Juan Francisco. But a) he's reputedly not a good defensive 3B range-wise, and b) I doubt he'll hit in the majors. Anyone have a good comp of a player with a 4% walk rate and a 25% K rate in the minors who went on to be a successful big league hitter? Best I've found is Wily Mo Pena, and he walked 6% of the time in the minors! -j
Sabermetric moves of the 2010 pre-season (jinaz) —
Seth/166, I have it as somewhere around a 2 WAR surplus for the Reds over the life of the extension. http://www.redreporter.com/2009/12/19/1209173/the-rolen-extension-by-the-numbers Depending on what you do with fielding, this can move up or down a bit. But I think it's certainly no worse than market-even. -j
Sabermetrics Syllabus (jinaz) —
Yeah, I'd love to be able to offer an interdisciplinary sabermetrics minor some day. :) I actually think it could be a big draw from the university (we're small, so a few extra students a year is a big deal). Might have some trouble getting it approved by my chair, however--something about them hiring me in to teach biology, not baseball. :) The reading list is obviously much too big for one class. My goal in making it, however, is to be able to give a topic list to the students early in the semester and allow them to choose which specific topics they'd most like to target. The reading list will let me quickly generate a reading assignment from those selections without having to do much background research at that moment. Semesters get busy, and I want this class to be awesome...hence the planning. Thanks for the link! -j
The best defenders (according to UZR) of the decade (jinaz) —
I second Tango/8.
The ten year aging curve (jinaz) —
@Nick/5, I think my comment was more a counter to the argument that is being made elsewhere that, because something is peer reviewed, it's of high quality. All too often, I'll read a paper from my field that has been peer-reviewed by people within my field and I'll end up asking "how the heck did this get published?" I'm sure it's the same in economics. I think it's disingenuous for any academic to hold up the process of peer review as a shield against criticism, because we all know that it's nothing more than an imperfect filter. -j
The ten year aging curve (jinaz) —
Not much to add to the paper critiques. But regarding peer review: it's an important process in academia, and it does, on balance, do a good job of improving papers and keeping some of the worst stuff out of press. My most recent submission, for example, received a lot of very constructive but nonetheless damaging criticism that, if it doesn't kill it, will make the paper much stronger the next time I submit it for publication. But it's nonetheless the case that a lot of crap gets through the filter. Most journal clubs I've been a part of are basically about tearing papers to shreds. The fact that something has been peer reviewed doesn't mean that it's perfect, nor that it's beyond reproach. Really, it just means that you got at least one of the two referees, plus the editor, to buy into the paper. As has been pointed out many times on this blog and elsewhere, the serious amateur baseball research community can do a superb job of peer review. It's different in flavor to what happens in academia, but from where I sit it sometimes works even better. -j
Sabermetric moves of the 2010 pre-season (jinaz) —
Hanigan's also a heck of a defensive player, based on 2009, so yes, I'd rate him above Hernandez on the depth chart. You need more than one catcher, though. Hanigan's a fine player, but most catchers won't be 85% players. I'd prefer that Hanigan play more than Hernandez, but you can do worse than a Hanigan/Hernandez tandem. -j
Sabermetric moves of the 2010 pre-season (jinaz) —
Fairly minor move, but the Reds re-sign Ramon Hernandez for $3M in 2010. Option for $3.25 in 2011 if he's a 74% playing time guy in 2010, which seems unlikely. They also had to pay a $1M buyout to get out of his last contract, so effectively they're paying $4M in 2010, which is worth somewhere around 0.9 wins. Hitting: Rally has him at -9 RAA/150G, but 54% playing time. Pro-rated, that's -0.6 wins or so. ZiPS is similar in both rate stats and playing time. Fielding: Fans have him straight-up average. Catching stat based on SB/PB/WP/E rates puts him right about average as well based on the last three years of data. I call him average. Position adjustment + replacement is +1.25 wins and +2.25 wins (I think Rally's baseline is 2.25 wins across the board compared to his R150 number..?). Prorated, that's +1.9 wins. So: -0.6 + 0 + 1.6 = +1-1.5 WAR in 2010. Seems somewhere between fair and a modest bargain for the Reds. -j
The 2009 Fans Scouting Report - last chance (jinaz) —
Something interesting with SS's. http://www.tangotiger.net/scout/index6.php?prim_fld_cd=6 Jack Wilson was rated by both PIT and SEA fans. Average scores as you're reporting them are 4.38 & 4.36. Orlando Cabrera was rated by both OAK and MIN fans. Average scores as you're reporting them are 3.33 & 3.28. In both cases, they show up right next to each other in the overall SS rankings. And their individual skill ratings track extremely well (e.g. Jack Wilson's sprint speed vs. catching scores). So, either we have the same fans voting on each player twice, or the FSR is apparently quite repeatable on individual players (or at least these individual SS's). -j
Forecasters Challenge 2009 - Who was similar to who (jinaz) —
No question that real-world knowledge of projected playing time are a huge part of success here. As far as systems using some kind of algorithm to forecast playing time, though...is CHONE showing up the best of those, at least in the head-to-head competitions? It looks that way to me, though I don't know all of the systems. -j
The best- and worst- fielding catchers in baseball (jinaz) —
And, generally speaking, catchers with reputations for great arms (e.g. I-Rod as a young catcher) have awesome runs saved numbers, despite the fact that "no one" ran on them. It seems to work well, at least qualitatively. -j
The best- and worst- fielding catchers in baseball (jinaz) —
@Aaron/4, slyde (at redreporter) and chuckb (at BtB) did this earlier this summer, referring to it as "rep runs." I've never been comfortable with it, though. If a team is running on a catcher, but they're not being successful above the break-even point, it's actually to the catcher's team's advantage that this team is running. Running or not running is sort of irrelevant in my view, the question is whether they are successful or not when they do run. I'm willing to be wrong about this, but so far I haven't seen an argument for reputation runs saved that makes sense to me. -j
The best- and worst- fielding catchers in baseball (jinaz) —
I think the formula devil fingers was using in that case came from my post: http://www.basement-dwellers.com/2007/11/player-value-part-3c-fielding-catchers.html I agree that it's sort of an odd way to present it--when I went back to this recently to implement the method for another project I did a double-take. I thought I had worked out at the time that the math was equivalent, though, and thus saved a step vs. working it out separately for SB's and CS's. I don't really have time to look into it now to see what I did to verify this, but Tango's check suggests that it's not equivalent. If so, I'm happy to do it the other way. Makes no real difference to me. -j
An AIDS vaccine trial and statistical significance (jinaz) —
In that case, they need to at least report that subsets of the data were not significant, and demonstrate that the problem was statistical power (which can be specifically reported), not the direction or size of the effect. -j
An AIDS vaccine trial and statistical significance (jinaz) —
I'm not in drug testing. But the general guideline according to my training (I'm a biologist) is to decide before the study begins what data you will release in the publication. You don't let the data determine what goes into the paper. Now, it's often the case that things happen and you have to add alternative analyses to address unexpected confounds or surprises. And sometimes it becomes necessary to drop less informative parts of a study for the sake of space or focus in the paper. But I'm not sure that this is the same thing as happened in this paper. It sounds like their data were noisy, and they chose the analysis that showed the most significant-looking results. That is NEVER supposed to be what determines how you analyse your data. Transformations, model fitting, parametric vs. nonparametric, etc, are all data-driven decisions. But you can't choose which dataset to use based on which one shows the most significant results! -j
Measuring clubhouse chemistry (jinaz) —
That didn't make sense. Here's what I mean: Cliff Floyd was paid a $350k premium for being a great clubhouse guy, which is the value of less than a 10th of a win. If he's the best-case premium, that's a lot less of an adjustment than the hit that teams are apparently willing to take to avoid the bad clubhouse guy based on Bradley/Bonds. -j
Measuring clubhouse chemistry (jinaz) —
I'm reminded of Tango's post on Cliff Floyd earlier this year: http://www.insidethebook.com/ee/index.php/site/comments/measuring_the_immeasurable/ So, is positive presence worth less than negative presence? -j
Pssst… Wanna Meet Neal Huntington and Dan Fox? (jinaz) —
Tango, Agreed. I'm sure they have mechanisms to put together a "number" or a few "numbers" for a given player. In fact, I'd be surprised if Dan Fox does not generate estimates of overall player value in wins, surplus dollars, etc. Maybe what Huntington ultimately works with at the end of the day isn't one specific number. But in order to perform well in a trade market--and the Pirates generally seem to--they must have a pretty well developed mechanism of assessing player value...even if it's not as sterile in the end as "surplus $." -j
WAR v Win Shares (jinaz) —
So, brainstorming causes of differences: * WSAB uses a higher baseline, so WAR will give more credit for playing time than WSAB. * Fielding metrics. This could be huge. * Position adjustments. I have no idea how WS does this, but I'm sure it's not based on fielding talent disparities. * Team wins vs. hypothetical wins? Others? -j
Question of the Day (jinaz) —
I'll say "take more often"...because what I do (or would do if I could play, which I can't) is pick one specific location and pitch type and zero in on it, with the exclusion of other potentially hittable pitches. In this case, I'll probably pick a fastball down the middle and take anything else. -j
Brandon Inge (jinaz) —
David, Thanks for that! I might have never seen it. I'll give it a read and probably will do a quick write-up on it, as it's old enough that I think most of us will have never seen it. -j
Brandon Inge (jinaz) —
And DH's don't hit as well as they do when playing a position either. -j
Brandon Inge (jinaz) —
There's a piece in this month's Baseball Digest in which one of the Atlanta catchers makes exactly this claim--being a catcher, with all of its physical rigors, has a negative effect on your hitting. I remember seeing an interview with Joe Mauer a few years back, I think at BPro, where he makes the same claim. It's something I'd like to see further research on. For example, does the gap between catcher hitting and other position hitting get worse in the hotter months? Does the gap get larger later in the game (as catchers get tired)? This is on my list to look at. But if someone wants to run with it before I am able to--which might be months/years from now--be my guest. I just want to see the results. I wonder how good of a hitter Mauer would be if he wasn't catching. :) -j
Blogspot blocked (jinaz) —
Either someone's out to get you... or someone in the IT department just bought some list of common distraction sites or something. I like the former hypothesis, but I'm the paranoid type. -j
Blogspot blocked (jinaz) —
Tango/16 http://joeposnanski.com/JoeBlog/feed/ Works for me. -j
Blogspot blocked (jinaz) —
Time to buy that shiny new domain I've been thinking about.. :) I'm pretty sure that there are comment feeds as well via blogspot, but that gets clunky. -j
Additive park factors (jinaz) —
That is, if a park adds +.01 HR, 3B, 2B, 1B, BB per PA, the net effect is not half as many runs as a park that adds +.02 of those events per PA. So, only for runs per game do you actually want to use the multiplicative method. For the component stats, the additive method is better. Well, crap. So, your recommendation would be to either a) use additive component factors, plus some kind of adjustment for PA's in hitter vs. pitcher parks. or b) convert RAA data to absolute runs, apply the multiplicative park factor, and then convert back to RAA? Just trying to figure out how to do this in an acceptable way. -j
Brian Bannister speaks "FIP" (jinaz) —
Also speaks to Pizza Cutter's semi-recent article about using sabermetrics to influence players on the field. Bannister tried to increase his strikeout rates last year, and succeeded...but the bottom line--runs per 9 innings--wasn't there. -j
Dual-roled pitchers (jinaz) —
I've long assumed that platoon advantage is a big part of why relievers do better than starters, and thought I'd read confirmation of this, but I don't remember where. I guess the prediction is that this effect would be weakest for long relievers and closers, and largest for middle relief and setup guys... -j
Dual-roled pitchers (jinaz) —
I might have missed it (or don't remember if it was covered in The Book), but to what extent does the platoon advantage impact the effect Rally documented? Relievers--especially LOOGY's--must be more likely to have a platoon advantage than starters, right? -j
The Race Database (jinaz) —
On the issue of skin tone...why not just measure skin tone directly? The head-shot photos taken of major league players aren't completely consistent in their exposure, lighting, etc. But my impression is that they're reasonably close. You could sample a 5-pixel by 5-pixel spot on every player's forehead from their headshot, and then just report the average brightness of those pixels. This could be done in Photoshop, GIMP, or I imagine one of you codewizards could put together a quick program to made it reasonably automated. You can find "facepacks" of MLB player faces on some of the baseball sim sites, like those for out of the park baseball. Historical packs are even available, though the consistency of photography of older images will vary a lot. This won't answer the ethnicity question, but it would give you a quantitative description that has at least something to do with what we perceive as skin tone. I've used similar methods to document the brightness of visual signals in animals. -j
A word on batting orders (jinaz) —
I try not to get too worked up about it, but my Reds often bat two of their three worst hitting position players in the #1 and #2 slots. Our manager has stated already this year that when Jerry Hairston isn't in the lineup, we will see Willy Taveras leading off, followed by Alex Gonzalez hitting #2. Otherwise, Hairston hits second. Way to write off the first inning and maximize PA's for poor hitters. Like I said, I try not to get too worked up about it given the relatively modest differences over a season. It's astonishing to me, though, that a company spending the amount of money that any ballclub spends on players can be so obviously inefficient. -j
World Series or WBC? (jinaz) —
I love the WBC for many reasons. I love the huge talent differences across clubs, because you get to see teams like the Netherlands pulling massive upsets despite AAA-level (at best) talent. I love that it's a way to learn more about the personal backgrounds of all the players we follow in MLB. And I love the nationalism of the event. I completely reject the idea that nationalism (actually, I think patriotism is probably a better word for what we're seeing) on the level shown in the WBC is evil. The WBC is all about pride in your country. There's nothing wrong, and a lot right, about that. I wrote when Obama was elected that I felt a genuine since of pride in my country for the first time in a long time. It's made a tangible difference in my attitude toward team USA this go-around. Maybe that's shallow, but that's where I'm at. I also love to see the patriotism exhibited by the players and fans of other countries. It helps me remember that there is far more to this world than this tiny part of our country where I closet myself. Fans and players of other teams are proud of their own countries, and they should be. The kind of nationalism we're seeing in this event is not, or at least does not have to be, the same thing as isolationism or exclusionism. It does not mean that you don't respect and admire other countries. It just means you're proud of your own country and the players representing it. -j
The Best Catcher of the Retrosheet era (jinaz) —
^edit out the "an approach" above. I always regret not proofreading before hitting submit. Also, if you're interested in seeing more results using that approach, I independently came to virtually the same catcher evaluation procedure here and used that in my WAR stuff I posted all last year: http://jinaz-reds.blogspot.com/2007/11/player-value-part-3c-fielding-catchers.html -j
The Best Catcher of the Retrosheet era (jinaz) —
Rally'll have to confirm, but I'm pretty sure that for the WAR stuff, he uses an approach this approach: http://www.baseballthinkfactory.org/files/primate_studies/discussion/tweaking_zone_rating/ It assesses things that must matter...but leaves a lot of other things that may matter on the sidelines that WOWY would measure. -j
Ill-considered fielding position moves (jinaz) —
The Reds are famous for doing it way too late: Ken Griffey Jr. played CF through the 2006 despite being historically bad there from at least 2004 onward. The move to RF for 2007 has to be one of the most overdue such moves in history. His defense essentially negated his offense for many of his last 4 years with the Reds. Edwin Encarnacion is still scheduled to be the Reds' starting third baseman despite 3.5 seasons of being somewhere between bad and terrible there. They have the opportunity to move him to left field this season, but they will not. The Reds also had a great opportunity to move Adam Dunn to 1B for the 2006 season, but didn't in order to get Scott Hatteberg in the lineup. Hatteberg did have a pair of excellent years with the Reds, but at the time it seemed beyond crazy... -j
Chone has its own site (jinaz) —
Rally/9 -- Thanks for getting the defensive projections back up there so quickly! -j
Poll: The relaunch of WARP (jinaz) —
So he's also going to use SFR? That's a big improvement over DT's. Still not as good as what we can do at fangraphs now with wOBA and UZR. But it'll make a huge difference in the arguments we see from BPro fans. Really great news. -j
Bill James does positional adjustments (jinaz) —
It's possible to both respect (or even be in awe of) Bill James as baseball's Darwin, while at the same time be unexcited about and unimpressed with his most recent work. -j
UZR on Fangraphs: using BIS on Ichiro (jinaz) —
In Humphrey's study, he tried to get both Shane and MGL to use the same engine as best he could. Probably wasn't perfect, but it was close. I agree, this is a tighter comparison, but I think it's been pretty clear for a while now that STATS and BIS have massive disagreements. In any case, at least now if there were any doubts before, they surely must be placated with this new comparison. I'm just going to keep on averaging--but now I can use Fangraphs' UZR data instead of RZR, which is really nice. Say "bye bye" to the OOZ denominator problem. I also completely support the bUZR and sUZR notation. -j
UZR on Fangraphs: using BIS on Ichiro (jinaz) —
Oops, that was MGL and Shane Jensen, not David Pinto. My memory deceived me. -j
UZR on Fangraphs: using BIS on Ichiro (jinaz) —
Let me add to the chorus of "thank you"'s to MGL for working to get this integrated to Fangraphs. And also to David Appleman for continuing to produce such an innovative and important site. Now he just needs to start calculating WAR based on his linear weights and UZR fielding values! I will say that I'm surprised at the apparent surprise here of a lack of agreement between BIS and STATS. Michael Humphreys found this same thing in 2007, with MGL and David Pinto's help: http://www.hardballtimes.com/main/article/ghosts-in-the-outfield/ And my quick'n'dirty correlation matrix between different fielding systems had similar findings: http://jinaz-reds.blogspot.com/2007/10/player-value-part-3b-comparing-of.html FWIW, Fans Scouting Report agreed with BIS statistics slightly better than it agreed with STATS statistics. And in Humphrey's study, his own stat, DRA, correlated better to BIS data than STATS data. So I think we'd be justified in favoring the BIS data. Nevertheless, I continue think that our best bet, as Rally has advocated for a long time, is to average statistics from at least these two sources (using the best engine we can in each case--now it's UZR for BIS data and probably also for STATS data). -j
Nate Silver: hero to interviewers (jinaz) —
As Stephen Colbert has noted, reality has a strong liberal bias... :) -j
Nate Silver: hero to interviewers (jinaz) —
I think the big assumption here is that Silver is, in fact, running a fair and accurate transcript of the conversation. He states that there were a few ad hominum exchanges that he excised. I just wonder if their inclusion would change our perspective on the interview (even if they are vulgar). I also wonder whether Nate is being accurate in depicting the way he asked his specific questions. For example, is it possible that Ziegler's being accurately quoted (by most accounts, he's a major ass), but that Silver himself isn't? The problem here is that, even though I generally agree with him most of the time, Silver is not an unbiased reporter in this case. He is part of the dispute, clearly on one side of the matter and not the other. As such, just providing a text transcript, rather than a recording or something, makes me uncomfortable...especially given that it makes the guy look so terrible. Not saying that Nate is being dishonest here--my guess is that he is not--but still, it makes me uncomfortable. I also agree with MGL that the senator questions at the end were in poor taste and unfortunately indicate a specific agenda on Nate's part that again suggests bias. -j
Best performances of 2008 (jinaz) —
Frankly, my brain's not up to that stuff tonight, so I might be missing something. I'll try to find time to read through the other thread tomorrow. But I used outs as my denominator when calculating runs per game. I then compare a player's runs per game to a baseline (average or some fraction of average for replacement level--it varies by league) to calculate RAA or RAR. I use outs because I was using absolute linear weights and not relative linear weights. They do not include the full impact of outs, and therefore it's important to measure playing time in terms of outs instead of PA's. I'm not sure if that's what you're referring to or not, Colin, because I didn't keep up with that prior discussion. But I was under the impression that this was the correct methodology...PA's are never actually used in my estimations of R/G, RAA, or RAR. So in tango's question above, 100 absolute BsR (as I calculate them) in 400 outs would result in 100 / 400 * 26.25 outs/g = 6.6 runs per game. And 100 absolute BsR in 350 outs would result in 100 / 350 * 26.25 outs/g = 7.5 runs per game. To convert those to RAR, I do this: (6.6 r/g - K * Lg) / 26.25 * outs = RAR where K = your replacement level coefficient (I use 0.72 for the AL and 0.77 for the NL IIRC) and Lg = league average runs per game. For Lg, I use league average for all position players rather than overall r/g because I don't like to compare my position player hitters to a group that includes pitcher hitters. -j
Best performances of 2008 (jinaz) —
@terpsfan, I'm using Patriot's spreadsheet but not his base runs equation. I used Tango's base runs equation (variables culled a bit to match my dataset), plugged it into Patriot's spreadsheet, and then forced the base runs equation to match 2003-2007 MLB totals. The main reason I use his spreadsheet is that it makes extracting the linear weights from the base runs equation automatic. I do not include SF's except to increase the number of batted outs above what AB's would suggest. GDP's are included, though I see your point on opportunities...I'll think on it, though I like knowing that additional outs were created. That would seem important to getting league-wide numbers to match up to reality. As for different equations for different leagues, while it may be "better," in my experience it doesn't matter much. It's sort of like using team-specific linear weights--there are minor differences in terms of the actual results. And, when I was setting this up, I judged that it just wasn't worth the effort to use different equations for different leagues. I do, however, have an adjustment to replacement level depending on league. One can argue on these same lines that I shouldn't bother doing custom linear weights at all. But given that I'm using a different dataset than Tango used, and especially that I have different variables and perhaps a slightly different model (again, not including things like ROE's and such), I thought it was worth doing. Besides, as an intellectual exercise, it was good for me to learn how to do it so that I understood what was going on under the hood. The specific equations I'm using are laid out in the post linked in my name, if you're interested. As far as I can remember, those are the equations I currently am using in my spreadsheet. @Tango, I'm not sure what you mean by offensive numbers. You mean lwts? r/g? RAR? I'm guessing you mean RAR, because that's what Sky described as offense? In any case, I'll have to get back to you on it because I need to run. The equations I'm using are in the link, though, if you want to see what I'm doing. Thanks, Justin
Best performances of 2008 (jinaz) —
Methods: I use Patriot's base runs spreadsheet to force a base runs equation that uses Tango's coefficients (Base runs explained) to match 2003-2007 MLB data (it adjusts the B terms up or down to match the numbers). Those equations are directly used for pitchers. For hitters, I extract linear weights from that base runs equation (again, using Patriot's spreadsheet, which uses calculus instead of the +1 method to do this). I actually don't do team-level linear weights, because a) I'm interested in comparing players across teams and therefore it makes more sense to me to use league-level linear weights, and b) it just doesn't make enough of a difference to be worth the massive increased complexity in the spreadsheet to have team-dependent linear weights. We're talking fractions of runs, at worst. The resulting linear weights typically have larger values for individual offensive events (single = 0.51 runs instead of 0.46), and larger values for outs (-0.099 runs vs. -0.098...I'm using lwts_RC) than are reported in Tango's base runs table. I've always figured this was due to some combination of a higher runs environment over the past several years (2003-2007) as well as the fact that I'm not including all the terms in my model that Tango does (THT doesn't report ROE's, for example), and so the missing terms' effects are generated via up-weighting correlated offensive events). The reason I don't go with B-Ref's data, which does report ROE's, is that THT's fielding data is nicely detailed (in addition to being the only source of RZR data) and is easier to pull into a spreadsheet than B-ref's. And so I use their hitting data because the names all match up perfectly. The only source I use other than THT is ESPN for the ZR data, and there are occasional issues with names not matching up between the two datasets. -j
Best performances of 2008 (jinaz) —
@MGL, yes, each position at which a player plays is pro-rated for the position adjustments, based on innings. This unfortunately has the exception of DH's, for which I don't even get games played as DH info from my main source (Hardball Times data pages). This messes up a few guys, like Jack Cust, pretty severely. I don't have a good way around it aside from manual intervention. But if a guy spends 100 innings at 1B, 300 innings at SS, and 500 innings at 2B, those position adjustments will be assigned based on innings each position and then summed up to get the overall position adjustment you see displayed in those tables. Also, I do list primary position on the original data tables that Sky is pulling from. Click on my name to get to that spreadsheet. I probably could include all the other positions, but that's a relatively low priority item for me compared to some of the other adjustments I want to make. And given that it's all excel based, it might be a bit of a pain to get automated (though I have some idea about how to do it...). -j
Best performances of 2008 (jinaz) —
Just thought I'd say thanks to Sky for running this series. I had planned to do something similar for a while and publish it at THT, but I'm still buried by work and such. Sky's series gave the data a proper vetting (and good visibility to boot). And he did a nice job of pointing out places where the data were likely misleading or prone to misinterpretation. One thing I will say in response to Tango's comments: part of the reason for only showing the columns we did was that further detail (e.g. showing park factors, league adjustments, etc) is that it might blind people with numbers. Keeping it as simple as possible -- offense + fielding + posadj -- helps keep this approachable. If anyone wants the spreadsheet so they can pick apart the methods, I have no problem sharing it (with minor conditions). Just fire me an e-mail. Methods were also laid out on my blog in my player value series last offseason, and I've tried to stick to those as much as possible. They're built upon Patriot's and Tango's work, mostly. -j
An historic and sad day at the same time (jinaz) —
I hadn't even noticed that Prop 8 passed until now. Like a lot of you, I'm pretty surprised and a bit dismayed. But I guess social politics haven't really changed--it's really just the economy that has changed. I think that the goal for those of us who think that homosexuals are deserving of decency should be securing specific rights for same-sex couples. Hospital visitation, inheritance, custody, tax benefits, health insurance benefits, etc. The country clearly isn't ready to condone the word "marriage." And that sucks. But at least we can work toward securing specific rights for same-sex couples to gain some measure of equality. It may be "separate but equal," and therefore not truly equal. But it may serve as a stop-gap until, as Craig implied, the opposition either changes their minds or dies off. -j
How good are the Fans in evaluating fielding? (jinaz) —
Also FWIW, Rally, I read it this morning and saved it in bloglines for a subsequent link dump (whenever I get around to doing one). It's nice work, and would give me an opportunity to plug your essentially one of a kind defensive projections as well. As for the comments on your moneyball piece, I think you can blame studes and his link at THT for that! :) -j
Starter, reliever or swingman? (jinaz) —
wow, that last sentence didn't make much sense. Should read: though I imagine it’s based on some combination of past usage of the specific player and the historical usage of comparable players...with some manual tweaking if needed.
Starter, reliever or swingman? (jinaz) —
Also, 4/mgl, while I don't know about specifics, PECOTA (at least) does include an adjustment based on whether a player was pitching in the past as a starter or reliever. It was implemented and discussed a few years back (maybe in the 2006 BPro annual?). Not sure what's used for the projections, though I imagine it's based on some combination of past using of the specific player and the history usage of comparable players...with some manual tweaking if needed. -j
Starter, reliever or swingman? (jinaz) —
Hi Tango, Thanks for thinking about this problem, as it is something that I essentially punted on. Yours is a nice workaround, and I agree is much better than just forcing someone into one category or another. I'll probably try to institute this adjustment next time I post my numbers. It could potentially make a big difference for someone who had a substantial number of starts and yet still fell below my starting pitcher criteria (15 starts or 50%+ of games as a starter iirc). -j
Challenging Nate Silver (and all other forecasters) (jinaz) —
So, participants can submit three ranked lists--one for each metric? -j
Complete WAR, 2008 (jinaz) —
Part of it's personal preference. I don't like dealing in numbers where the range of values for most players is 1-5 or so. I find it easier to think about a compare players using numbers that vary from 10-50. Small headed, I guess. Also, the conversion from runs to wins is just an approximation in my methods (everything would be converted to runs first, and then to wins), and therefore just adds another layer of uncertainty. People have enough trouble understanding where I'm getting the runs data from, especially (for whatever reason) with fielding. Explaining the 1 win equals average total runs per game approximation just makes it more complicated, and arguably makes the meaning of the data less precise. So I personally just prefer to just use runs. You can always divide by 10 in your head to convert to wins, of course. :) -j
Complete WAR, 2008 (jinaz) —
Thanks for the link, Tango--there's little I've had time to do lately, but at the least I can post these data. I'm sure the methods behind them aren't perfect, but I think they're pretty good. It does seem that I have DH's too high--they were rated at -15 runs/season. I'll switch to -17.5 runs in the next update. Not that big of a difference. I still have some other things to do as well before I consider these things "final," like using custom linear weights that include the 2008 season, and using patriot's park factors. -j
Converting Zone Data (jinaz) —
Well, it all comes down to the average plays per unit estimate of opportunities, where unit is either BIZ or innings. You (or I, at least) calculate this separately for each position, so the decreased number of chances for a 2B will be reflected in the decreased average plays per unit no matter which unit I use. My rationale for using BIZ has always been that it seemed more likely to reflect the gb/fb or left/right peculiarities of a team's pitching staff than simply using innings played. But it also might be the case that you get an inverse correlation, because a ball in zone will no longer be available to be a ball out of zone (if that makes sense). -j
Converting Zone Data (jinaz) —
Good stuff, Colin. I haven't noticed too much of a difference between what I post (which uses OOZ/BIZ) and what Rally posts (OOZ/Inn), but maybe I haven't checked closely enough. If both you and he favor that approach, it might be time for me to switch over to Rally's approach for individual fielders. -j
Which has more predictive value for a player: last year's stats or this year's stats so far? (jinaz) —
I'm not sure where else to put this, but Sal's version of Marcel appeared in an article in the Cincinnati Enquirer today to try to understand what (if anything) we can take from Chris Dickerson's performance. http://news.cincinnati.com/apps/pbcs.dll/article?AID=/20080906/SPT04/809060374/1071 It's perhaps not the best use of the system...Dickerson's minor league numbers tell us that his performance with the Reds this year is way out of line with his talent. But still, Marcel mentioned in the paper... -j
Sabermetric Moves of the 2008 In-Season (jinaz) —
Question about free agent compensation, following on the discussion in #52, #54, and #60... Griffey's contract has an option for 2009, and therefore the White Sox will (you would think) buy that out at $4 million this offseason. So that's a loss for the White Sox. However, if they buy out the contract, will they also get the opportunity to offer arbitration and therefore get the free agent compensation? Griffey qualified as a class-A free agent last year according to Elias's widsom (though not by much--click my name for link). But if he's a class-A free agent again this offseason, then the free agent picks would be carry the $10 million value discussed above. The Sox negate a fair bit of that with a signing bonus (right?), but it might help the Sox's cause here... -j
Sabermetric Moves of the 2008 In-Season (jinaz) —
Playing time? Sal's spreadsheet forecasts 654 PA's (based on ytd usage), which he hasn't done since 1999. He's been healthy so far, but he's not a sure bet to last the rest of the season. -j
Sabermetric Moves of the 2008 In-Season (jinaz) —
Ok, my understanding (still lots of research to do) is that the Reds are sending Griffey + $4 million (the remainder of his 2008 salary) in exchange for two guys who are at best C-level prospects. So, essentially, the Reds are sending him away to avoid paying his $4 million buyout in 2009. That $4 million should be worth almost a win on the free agent market. Griffey would produce no wins above replacement, with the team or off the team, and his option year is worth $16.5 million. So not paying the option year is the best outcome for the Reds. That they got two scrubbish players (I know nothing about them) is a bonus. So, at first blush anyway, this is a win for the Reds. -Justin
Sabermetric Moves of the 2008 In-Season (jinaz) —
Reds fans are holding their breath and hoping this doesn't fall apart. #63 isn't even factoring in Griffey's pro-rated salary over the past few months. Assuming that goes with Griffey....wow. Word 'round the campfire is that they might get Lance Broadway for him. A 24-year old pitcher who might work as a #5 starter next year is a better return than I could have imagined. -j
Ibanez, the fielder (jinaz) —
It's more or less irrelevant to your main point (that one person's opinion on someone's defense doesn't matter), but Dunn's fielding numbers have been up a bit this season. I have him as +0.7 runs by ZR, and -4.5 runs by RZR. Taking the average of the two gives -1.9 runs. I've heard anecdotal commentary from people who watch more games than I do indicating that they think he's running a bit better too. I'd like to have some stopwatch data on that, but I'd like a lot of things. He did have a "clean out"-type knee surgery last offseason, so maybe there's something to it. Anyway, I'll be interested to see how the Fans rate him this fall. I'm still they'll still say he sucks...but perhaps not as much as the past few years? We'll see. -j
Which has more predictive value for a player: last year's stats or this year's stats so far? (jinaz) —
Sounds great, Sal, I'm looking forward to seeing it! -j
Which has more predictive value for a player: last year's stats or this year's stats so far? (jinaz) —
It seems like it's relevant to link to Sal Baxamusa's article on rolling Marcel projections: http://www.hardballtimes.com/main/article/the-running-of-the-monkeys/ That's probably the best available mechanism by which one can use 2008 stats as part of your analysis of player talent...at least among those that I've seen. I'd love to see a site like THT or B-Ref formally incorporate his methodology (or Tango's, who has a similar approach as I recall) into a line on their player pages. It would be extremely helpful to see that during the season. It does look like B-Ref has (with subscription) an "Over past 365 days" split, which is about as close as we can get right now. I'd have to fiddle around and see if I can get it to post all players' stats on one sheet for easy copy 'n pasting. -j
How much should a smart organization pay for a replacement-level name player? (jinaz) —
I hate to say this, but as a Reds fan, I can only sit and hope that TB does this. But, like you, I doubt they will. It would be hard to find a worse value in baseball than Griffey. I'm sure there must be other players out there that are as bad of a value (maybe Schilling this year?), but his combination of terrible defense and declining offensive skills makes him hard to beat. If the Reds aren't able to trade him this season, I do expect them to let him walk. Problem is, they have to eat a $4 million buyout to do that. But paying $4 million + $400k for a replacement player is better than paying $16.5 million for a replacement player. -j
When to walk 'em... (jinaz) —
Wrote this at ballhype, but I thought I'd copy it here as well... Neat article, MGL, looking forward to the next part. Minor comment: seems as though another factor to consider is the quality of the pitcher. I'd guess that the average pitcher in your "runner on 2nd and 3rd, one out" situations is worse than the average pitcher overall, simply because good pitchers don't get into that situation as often. This might be another reason that you're seeing the higher-than-expected wOBA after the intentional walk. And it's another reason to be careful about comparing actual rates to average rates in this situation. -j
Boring college professors say of surfing students: (JinAZ) —
Trev, your instructor should be distributing handouts of her/his powerpoint slides in advance so that people don't have to copy them down. Talk about a waste of class time! Not to mention a massive disruption to any sense of flow or conversation. S/he could be using that time to lead discussions, have students work through problems, etc... And if you distribute the slides ahead of time, note-taking becomes much more about writing brief comments or jotting down occasional words or phrases to help your understanding and recapture what is said in lecture. And lecture becomes much of an engaging experience where you have time to listen, think, and discuss. I'd also add that I have no idea how people using laptops can take replicate illustrations on the board...which, at least in a biology class, are frequent and essential. :) That all said, if I had a student like you who felt his/her ability to learn was being particularly negatively affected by my laptop ban (and I haven't had anyone voice such concerns yet, though I admittedly only adopted this rule this past semester), I'd probably be willing to be flexible...with the understanding that if it gets to be a problem (e.g. I see other people's eyes fixated on that person's screen for minutes at a time), things will have to change. Sitting in the back row might be an option... -j
Boring college professors say of surfing students: (jinaz) —
Well, in my classes, I don't permit laptops, at least not just for note-taking. Call me a power-monger, or whatever, but I'm pretty firm on this. Here's my rationale: If the effect of a person surfing the web or what have you was limited to the particular student in question, then I wouldn't care. The student would only be hurting themselves. This is why I don't care about attendance in lecture either. The problem is that it doesn't just affect that one student. It affects everyone who can see that student's computer screen. If 10% of the student population is surfing the web during class, then it's affecting almost everyone in the classroom. And this, in turn, can cause major problems for any attempts to cultivate a dynamic and engaging learning environment within the classroom. It's disruptive, and like any other disruptive behavior, is completely unacceptable because it impairs the ability of other students to gain what they want to from a class. Teaching done right is not just about having people pay attention to you. It's about directly engaging the class, cultivating a dialog between you and them, and probably most importantly getting them to think along with you. This is a hard thing to do. It requires buy-in on the part of the students. And getting this buy-in becomes quite a bit harder when students see other students so obviously not engaged. Classrooms aren't democracies. And education isn't entertainment. Students are paying money for the opportunity to learn and achieve, and I am not going to permit one student to impair the experience of another student if I can help it. If it were a less frequent issue, banning laptops wouldn't be necessary. But my experience is that roughly 2/3 of laptop users in classrooms are engaged in activities not related to the lecture/discussion at hand. And, at least in my experience, banning laptops has resulted in a much better learning environment within the classroom. Call me a power-monger if you will. But from my vantage point, cultivating that learning environment is probably the most important part of my job. And, of course, if students don't like it, they don't have to attend... -j
Help Dusty make the optimal batting order (jinaz) —
I finally figured out the difference between my and Beamer's data--it was a second case in which I just didn't understand how to use his spreadsheet. My results now match is perfectly. So, at some point here, I'm going to go back and re-do the Baker study and see how things fall out. -j
Community Forecast, 2007 - Preliminary Results (jinaz) —
I'm also seeing this rather late (thanks for the tip, studes, I missed this entire thread). Amazing findings. I had one small question: why did you use OPS? Is it just because it's the only composite statistic reported by all of these systems? It would be possible to calculate wOBA from data for PECOTA, Marcel, and CHONE (at least). Given how close all of these systems are, I guess it probably doesn't matter. I just hesitate to use OPS given how often folks tend to argue against its use for precision jobs like this. -j
Help Dusty make the optimal batting order (jinaz) —
Great. Looks like I'm doing something wrong with my setup. I wonder if I somehow screwed up the spreadsheet when fiddling around with it over the past few months. I won't be around much today, but I'll start with the original spreadsheet and try to reconstruct my results with a fresh version. I don't really see what else I could be doing wrong, but clearly there's an issue. -j
Help Dusty make the optimal batting order (jinaz) —
Well, I can't test the user issue, but John Beamer will be able to. :) I've sent him copies of my input page, so if I'm screwing up something he'll be able to catch it. Here's my attempt to replicate your table 63 using the Markov. I used 2007 NL splits by batting position, so the "pitcher" spot includes pinch hitters and Tony LaRussa's #9 hitters. The expectation from that would be that the difference between the best and worst lineup would be less than you found, because "pitchers" are better hitters in this case. Here are the data. When the pitcher hits 7th, the original #7 and #8 hitters hit 8 & 9 respectively.
Pitcher hits R/G Prd RS 9 5.061 819.9 8 5.063 820.2 7 5.061 819.9 6 5.059 819.5 5 5.062 820.0 4 5.028 814.5 3 5.028 814.5 2 5.083 823.4 1 5.070 821.3No idea what to make of pitchers doing well in the 1 & 2 holes, but the maximum difference between these lineups was 0.055 runs per game. Also, the model is missing high by ~0.3 runs per game. This latter finding is consistent within '07 NL teams as well. Here's the above work repeated, this time using b-ref's 2007 NL pitcher hitting splits in the pitcher spot, with all other positions the same as above. I expected that the max difference between spots would be closer to what was in your (tango's) study because pitchers are so incompetent in this lineup:Pitcher hits R/G Prd RS 9 4.831 782.6 8 4.834 783.1 7 4.829 782.4 6 4.826 781.8 5 4.830 782.4 4 4.795 776.7 3 4.794 776.6 2 4.849 785.6 1 4.836 783.5Again, 0.056 difference between the best (pitcher hits #2, for whatever reason) and worst (pitcher hits #3) lineups. At this point I'm going to step back and see what Beamer finds--if there is a problem with the model itself, then I can't be of much help. -jHelp Dusty make the optimal batting order (jinaz) —
I can copy over run expectancy matrices and state frequency matrices for any lineup I feed into the thing if that helps. I just don't really know what to look for at this point. Beamer has said that he did a fair bit of testing of his model against '07 data. Maybe the first thing to do is ask him replicate what I just did (using your data) and make sure that I'm (again) not doing something patently wrong. We chatted about it last night, though, so I'm pretty confident that I'm doing it properly... I may also try to use 2007 NL totals for each lineup slot and see how the model does with those totals. That would get away from any peculiarities with these particular players, and SHOULD match up pretty well. Don't have time to do that right now, though... Any in-depth analysis of the Markov's inner workings is probably going to have to be done by Beamer...though he has offered to send me the "source code" version of the spreadsheet and walk me through it, so maybe I can help at some point after I figure out how it all works. My time's kind of limited though...been spending too much time on this the past few days as it is. I know there are some things that it doesn't include (like handedness), but I still wouldn't expect the Markov to be as different from your sim as it is. It's a complicated model, and Beamer did a nice job of trying to include a lot of small details in it. Ultimately, it should converge on the sim results (assuming your sim is accurate, and I believe you that you've tested it extensively), especially with a fairly standard set of players. Hopefully we can figure this out, as it would be a great tool to be able to toy around with. -j
Help Dusty make the optimal batting order (jinaz) —
Reposted from my blog: ---------- Ok, I've run MGL's projections through the model. And I'm sure I'm now using the model correctly. Those projections are much worse than the PECOTAs! But the rank order from this model has Baker actually coming out on top. Here are the results, listed in the same order you listed them: Baker OD: 4.41 r/g, 715 r/sea Old Top 3: Bluzer OD: 4.32 r/g, 700 r/sea, -16 above Baker Chris-OD2: 4.34 r/g, 703 r/sea, -12 above baker Pickoff-OD: 4.36 r/g, 706 r/sea, -9 above Baker Old Bottom 3 (bottom first): redmanrick-OD: 4.26 r/g, 691 r/sea, -24 above Baker Brad-OD2: 4.30 r/g, 697 r/sea, -18 above baker fareast-OD: 4.33 r/g, 701 r/sea, -14 above baker Mine: jinaz-OD: 4.39 r/g, 711 r/sea, -4 above Baker jinaz-OD-exploit: 4.33 r/g, 701 r/sea, -14 above baker I'm using 2007 #9-slot hitting totals now, which come to a 0.170/0.216/0.250 hitting line. Before I was using pitchers only, but this helps account for the late-inning pinch hitters. So...Still disagreements between the two systems. These come out much lower than yours (using the same projections, mostly), and with a different rank order. And the range is a bit higher as well, with ~24 runs between the worst and best in the Markov and ~11 runs between the best and worst in your sim. The rank order differences are just bizarre though. Baker's lineup comes out on top in this Markov, but is doing terribly in your sim. And the worst lineup according to this Markov is the best in your sim...it's almost like they're inverted! ???? -Justin
Help Dusty make the optimal batting order (jinaz) —
John Beamer discovered an error in my usage of the model tonight. I'm re-doing the lineups with those modifications, and made it through the opening day lineups this evening. It isn't changing the principle findings thus far, and if anything is resulting in larger gaps between the lineups... I'm also going to take MGL's projections and run them through the Markov. It will be interesting to see if the differences between the two systems remain. As far as speed numbers goes, it's restricted to SB rates. GDP numbers are included, but they are estimates based solely on PECOTA projected BIP rates as PECOTA did not actually forecast GDP. In the version of the spreadsheet that Beamer released, all baserunning aside from stolen bases is a constant across all ballplayers...though you can manipulate the heck out of what happens in each situation (I'm leaving it at the default settings). And no, no differences between LHP and RHP are entered into the model in its present form. -j
Sabermetric Moves of the 2008 In-Season (jinaz) —
studes, That might be it! I don't remember seeing that in your equation--though I do see it there now. :) -j
Sabermetric Moves of the 2008 In-Season (jinaz) —
Could it be that you’re not including HBP? THT does. Nope, I include HBP. :) -j
Sabermetric Moves of the 2008 In-Season (jinaz) —
Eric, I tend to prefer my own numbers to those someone else has calculated...and in the case of FIP, that's particularly the case because I haven't been able to reproduce THT's FIP using their stated equations. One should be able to back-calculate their additive constant and have it be the same across players (at least within a team), but the times I've tried it hasn't worked out. So I'm not honestly sure how they get to their FIP numbers, though mine are usually close to theirs (as they are in this case). My numbers on Carmona are from my piece on the Indians last year: http://jinaz-reds.blogspot.com/2007/09/postseason-profile-cleveland-indians.html I used the FIP equation published on THT's website, and I calculated the coefficient to force FIP=ERA (probably MLB ERA in this case, 'cause I get sloppy by league differences at times). I sometimes also do a park factor correction on the HR totals, but I don't think I did that in this case. As for Carmona, I think "definitely" is a bit too strong. But in general I agree--as I said, if Marcel knew about DIPS, he would probably be a bit more pessimistic about Carmona than he is. Still, there's only so much you can teach a monkey, eh? -j
Sabermetric Moves of the 2008 In-Season (jinaz) —
One thing about Carmona: his FIP last year was (by my numbers) 3.83, which may indicate that he got a bit lucky with his 3.03 ERA. BABIP wasn't overly bad at 0.284. But still...If Marcel understood FIP, he might forecast Carmona a bit more pessimistically. But without running the numbers, I imagine this still works out as, at best, a break-even for Carmona. The Indians know what they're doing... -j
Psst... wanna work for Fangraphs.com? (jinaz) —
I'd love to do it, but there's no way I can post once a day. Heck, I'm struggling to post once a week at this point.. Dusty Baker study has been half-written for about a week. Damn dissertation keeps getting in the way of my blogging! -j
Technolgy in hockey (jinaz) —
Wow, that's different. Refreshing even. Hell, I'm not even sure if I'm allowed to post pictures to my blog, even if I take them myself at a MLB game: http://www.red-hot-mama.com/2008/03/04/were-here-were-consuming-information-get-used-to-it/ -j
Help Dusty make the optimal batting order (jinaz) —
Should be done by the weekend... What's interesting, preliminarily, is that it's remarkably hard to beat Dusty Baker's lineup with his players. If you start swapping in Jay Bruce and Joey Votto, you can do it. But Markov rates lineup pretty favorably. It might not be "perfectly" optimized, but somehow the interactions between players seems to work well under Markov. Despite Corey Patterson in the leadoff slot. -j
The Great Clutch Project has started (jinaz) —
I wonder if the titles on the two scoreboards at fangraphs should be reconsidered. As it is, it might give the impression that it's a question of whether Tom Tango's "better" or "smarter" than the fans...which isn't really the point. I'd suggest "Clutch hitters" vs. "Top hitters" or something like that. Anyway, just a suggestion. -Justin
BIS v PITCHf/x (jinaz) —
One thing I took from reading the Neyer/James Guide to Pitchers was that the words that pitchers use to describe what they do can be very unreliable in terms of predicting the behavior of those pitches. Pitchers also often seem to throw multiple kinds of individual pitches (like, say, a curve ball). So I wonder how much establishing groups of pitches ahead of time would really be helpful to discrimination... -j
Being a sabermetrician (jinaz) —
Here's what I wrote in response to David's post. I think it's relevant to your response as well, which is why I'm reposting here. -j --- Hi David, Thanks for the link and thoughts. I think my critique of the term isn't that it's a made-up word, per se. It's that the term sounds to me, as I put it in my post, a bit "pompous and half-baked." I think this is especially true for those who are disinclined to listen to us. Frankly, I think the term serves to isolate us and our work from the rest of the baseball community (both professional and amateur), which isn't a good thing. I will say that I certainly don't intend to make a habit of running around the internets critiquing people over the use of this term. It's not THAT big of a deal to me. And I have no illusions that the term is likely to go away, particularly not in response to my little post. But it's something I've been thinking about for several years now, and I decided that it was time to share my opinion on it. Take it for what it's worth. -Justin
The Great Clutch Project (jinaz) —
Looking great! If you don't get much Reds traffic, let me know and I'll try to stir up some more. I don't know if there's anyone with a more "unclutch" reputation than Adam Dunn, at least among local fans, so I'd think lots of folks would be ready to vote "against" him, no matter who they're voting for. ...while this won't really matter (no one's going to pick him), Corey Patterson is probably going to be the Reds' centerfielder for at least half of this season. Might be worth adding him if that can be done without difficulty. Also, when's the deadline for voting? Prior to opening day? Cheers, Justin
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
MGL, I mean inconsistent in how he produces his 15-20 RAR. :) Fans, at least Cincinnati fans, absolutely hated Lohse last year because he pulled a Jekyll and Hyde routine. He pitched some amazing games, but also pitched some miserable ones. Fans just couldn't stand it. Of course, as Sal B. and David Gassko showed at THT (and I often commented upon last year with respect to Lohse on my blog), inconsistency in a starting pitcher often results in slightly better wins value from his 15-20 RAR than if he'd been perfectly consistent. But apparently most people would rather just have the same result every time out. Or, like you indicated, they see him doing well in some games and can't fathom why he can't do well all of the time. -j
Brian Bannister was wrong, we need to get back to our basements, according to Bob Costas (jinaz) —
To be fair to Costas (which we don't really need to be), there is an awful lot of crap out there. A lot of the top-hyped sports articles on Ballhype are often from blogs that focus on sports babes, rumor mongering, etc. And the comments sections attached to local papers often are filled with the rants of the ridiculous. But the quality stuff isn't rare nor difficult to find. And the best quality stuff is very, very high quality--certainly on par with what you see in peer-reviewed academic journals, much less mainstream media. Costas clearly hasn't looked very deeply into this...and therefore really shouldn't be ripping on something that he hasn't taken the time to even begin to understand. -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
Not hurt. Apparently, it's a case where he and Boras tried to wait out the market, and the market just moved on. Or something. I just can't believe that someone wouldn't give him at least $6 million for one year. I wouldn't have minded having him back with the Reds this year. .... though he was inconsistent enough that I doubt many Reds fans would agree with me. -j
Brian Bannister was wrong, we need to get back to our basements, according to Bob Costas (jinaz) —
I think it's even worse than Costas realizes. Some of these pathetic get-a-life losers are actually getting FEATURED in the local papers, and not just in the comments sections. Recently and Last Summer Talk about a disaster. Why can't we go back to the day when the only people who could write about a team were card-carrying members of the Baseball Writers Association of America. -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
Very interesting summary. The growing value disparity between young players and veterans is the biggest thing I've started to come to grips with this offseason. It's a very different game than it was even 10 years ago. Your point about minimum in the NHL is pretty interesting. I'm surprised that this wasn't a bigger issue in the most recent CBA. .... I know the thread is now de-stickied, but I'd love to hear your thoughts on Kyle Lohse at 4.25/1 yr. Seems like a major negotiation screw-up on Lohse/Boras's part to me, and a small coup by the Cards. ...especially given what happened with Silva a few months back. -j
How often is your closer not available in an optimal setting? (jinaz) —
Pizza, if you ever do write that book, put me down for a preorder... -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
I am admittedly just basing it on his 2-year MLB averages, and I am ignoring his terrible 2005 minor league performance. I have him as +2-2.5 WAR hitting, +1 fielding, no position adjustment, and ignoring baserunning aside from stolen bases. Marcel has him at 0.339 wOBA in 610 PA's, or a dead-on average hitter. So if he plays most of a season, and NL replacement level is -2 WAR, he's essentially a +2 WAR hitter next year. Unless I'm missing something, I might be a tad high, but I don't think I'm crazy-high. Looking at your numbers, it looks like the difference lies in the fielding estimates. Fans like him, as do BIS-based stats (PMR thinks he was a god last year). STATS Inc stats don't seem to like him as much (at least not ZR), nor do retrosheet-based systems. I tend to side with the Fans when there's a disagreement. -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
Reports are that Phillips got 4yrs/$27 million, plus an option year. I had Phillips (post #410) at 3.5 WAR next season, without aging. If we go slightly more pessimistic and assume 0.5 WAR per season aging, that projects him as: 2008: 3.0 WAR 2009: 2.5 WAR 2010: 2.0 WAR 2011: 1.5 WAR That puts him at 9 WAR over the guaranteed part of his contract. Assuming 10% inflation in $ per WAR ($4.4 million this season), and 40%, 60%, and 80% of free agent value in his three years of arbitration, I get a total predicted contract value of $29.9 million over four years. To quote Tom Tango, bingo! -j
Tango On Demand (JinAZ) —
Ooooo...#15 sounds fantastic... -j
Tango On Demand (jinaz) —
I'll echo #6 as something I'd love to see, though Rally's excellent retrosheet fielding numbers make this not quite as important as it would have been a few months back. Possible related project idea as a #12: historical position adjustments, based on either your or Rally's retrosheet fielding data. I'd be very interested to know the extent to which changes in defensive skill among positions has tracked changes in offensive performance among positions. You could do it decade-by-decade and have fabulous samples to work from. This would be a real boon for folks like me who are starting to dabble in historical player valuation . It'd also be nice just to have the position adjustments calculated on a system other that UZR, in case UZR handles some positions differently than others. ... I could do this too at some point, but the night class I'm teaching right now is really killing my baseball analysis time. -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
It’s career insurance. Exactly. If they get severely hurt and/or ill any time over the next several years, they might get next to nothing. That's a catastrophic loss. These deals are essentially money for the rest of their lives, not to mention the lives of their families. Could they likely get more if they just waited? Sure. But to someone like me, if I'm offered $20 million now, or $40-50 million later two years from now, I'm going to have a hard time turning down the $20 million now, especially if my earning the $50 million requires me to avoid getting injured while doing a physically-intensive task like running around a baseball field 162 games/year. I'd be set for life with $20 million. And so would my family. Maybe it's not the optimal decision from an economic perspective, but for a lot of guys, I'm sure they feel it's the right decision from a human perspective. -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
On the list of reasons why a team might overpay for a position (post #452), it seem to me that scarcity of talent should go on that list. For example, the free agent market for starting pitchers is rather weak this offseason, which may result in higher salaries to the passable starters who are available (Silva, Lohse, etc)...not to mention higher trade value for teams willing to deal their starters (Haren, possibly Bedard, etc). One could argue, of course, that teams should just spend elsewhere, but you can only start 8-9 position players per game, so it may be hard to upgrade substantially after a certain point... -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
I missed that Cano is super 2. If super 2's are at 20%, then a 15.4*0.2 = $3.1 m is a reasonable salary for him. All of Bobby and Tango's explanations do help. I think Bobby's explanation about people using non-inflation adjusted comparables, and that resulting in a self-reinforcing cycle, makes a lot of sense. I'd really like to do a bit more of a careful study on this before I feel comfortable, but unfortunately I'm swamped right now and just can't do it. Anyway, Tango's various ideas on how to estimate salaries for these players also make sense and explain why high-end players might not be getting the kind of deals in arbitration that we'd otherwise project them to get. But at the same time, I'm still seeing someone like Phillips priced (by the Reds offer, at least) as a below average player ($2.7 / 0.4 = $6.75). 'Course, maybe they won't win the case... -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
I've been fiddling with some 1st-year arbitration cases on my blog, and I keep coming out rather high. 2 examples: Brandon Phillips. Club offers $2.7, Phillips wants $4.2 m. I gave him a simple-minded projection of 2.5 WAR on offense (his 2-year average) and ~+1 wins on defense (fielding metrics disagree on him, fans like him). No position adjustment, no projected aging (he'll be 27), so 3.5 WAR overall. 3.5 WAR is worth $15.4 m as a free agent. Assuming 40% of arbitration value for being a 1st-year arbitration player puts him at $6.2 million. That's much higher than even Phillips asked for. Robinson Cano. His 3-year hitting average is ~3.0 WAR/season. Fieldingwise, I have him at ~+0.5 wins (fans think he's average, but zr and rzr metrics think he's plus). So again, 3.5 WAR or so. Maybe include a small bump for aging. He's asking $4.5 million, Yankees offered $3.2 m, both well under the $6.2 m mark. $3 million (about what the clubs are offering these players), if the 40% adjustment for 1st-year eligible players is appropriate, is the equivalent of $7.5 million as a free agent, or 1.5-2 WAR. I have a hard time believing either of those two is an average player--not superstars, but above average. $4.2 million, what Phillips is asking for, is ~$10.5 million using a 40% discount for 1st-year arbitration players, and that's worth ~2.5 WAR. So unless I'm messing up something here, I'm wondering whether the 40% discount is too high. I know it matched up well in Wang's recent study, but it's not working well for these arbitration cases (at least). Maybe free agent salary inflation is outpacing 1st-year arbitration inflation? Anyway, feedback welcome. -j
UZR positional adjustments (jinaz) —
It'd also be possible to repeat Tango's procedure using Rally's retrosheet-years database, divided into decades perhaps. Not a small undertaking, but it'd be very interesting to see how actual defensive numbers change over time. -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
mgl/403, I took Rally's (delightful) comment as an explanation for how Marcel is able to perform so well against more sophisticated systems, year after year. In this case, he points out that two things effectively canceled each other out when trying to come up with Pena's projection. And that this kind of thing happens often enough that Marcel is pretty close most of the time. Clearly, there will be cases in which he'll miss because he doesn't consider all available information, or take steps to more carefully interpret the information he has. Your (and others) system will outperform it at those times. Obviously, you know all of this--but I don't think the comment was directed at you. -j
The Clutch Project (jinaz) —
Even if it's not the best way to go, using the difference is more straightforward than the ratio for most people. So I'd definitely recommend going with the difference. Also, I'd just like to suggest that if we want some big name individuals to actually step up and take Phil's bet seriously, we probably want to avoid critiquing their intellect in these threads. :) -j
The Clutch Project (jinaz) —
I also posted on the Reds forum about Phil's bets, and I'll make a blog post about it tonight. Maybe you'll get an unclutchy Dunn bet or three. -j
The Clutch Project (jinaz) —
I think it's a great project, and hopefully I can send a fair number of Reds watchers over here when the voting commences. I am curious about what you plan to do about injuries. If a player is hurt or otherwise has limited PA's, that would almost certainly make his top-50 PA's less crucial than the other players, simply due to the small sample you're choosing from. And if clutch guys do better in higher-leverage situations, then lower leverage situations might not be "exciting enough" (or whatever) for them to perform like their most clutchiest selves. So should there be a minimum number of PA's required (e.g. 500?) before you bump down to the next guy on the list? -j
Does Tony LaRussa hate MGL or Ron Shandler? (jinaz) —
Tango/2, It seems as though some teams are doing just that. I've read a fair bit about the Cleveland Indians' system, which apparently makes stride to integrate scouting information in a formal manner into a database. I have to think that the Red Sox are doing similar things, based on all their other innovations. Have you seen anything else reported on these kinds of efforts from these or other teams? -j
Does Tony LaRussa hate MGL or Ron Shandler? (jinaz) —
Regarding standards/rigor in baseball operations, here's a question that was asked as part of an application for a job with a major league team as a minor league instruction manager last year (I probably shouldn't comment on how I got it, though I wasn't told to be hush-hush about it either):
This was really a "separate the men from the boys" sort of question on the application, because it required applicants to describe two sides of an argument without laying out a conviction one way or another. Rather, it required folks to propose what sorts of information they'd need to collect to determine which is the best course of action for the team/organization in question. This is something that someone who isn't used to having to justify their claims with data and/or consider multiple roughly-equal courses of action might struggle with. Keep in mind that this was an application for a minor league instruction manager position, not a stathead-type position. So, while I might be reading too much from this little window into an MLB team's operations, what I'm seeing is an emphasis on critical thinking and justification from a position that (I imagine) might have traditionally been held by people who weren't required to justify their approaches much beyond "that's what I was taught, and what I've seen works." -JustinWanna do some peer review? (jinaz) —
I like Patriot's because they include regression (using MGL's coefficients, apparently), they're well thought-out, and seem reasonably rigorous without going overboard in trying to control for every little thing. And, they're super-easy to apply to players. -j
Wanna do some peer review? (jinaz) —
John/18, I like Patriot's: http://gosu02.tripod.com/id103.html -j
Wanna do some peer review? (jinaz) —
I'm going to try to read the paper over lunch. I did want to respond to this comment though, as a card-carrying academic: Some academics don’t like us. Others though appreciate our no holds barred approach. Academics are trained to be the harshest and most critical people in the world (or, so we like to think). Speaking at least from personal experience, reviews that I've seen on my own papers, grants, etc, have been far harsher than much of what goes on here. Perhaps the tone is more cordial. For example, I've never been called "stupid" in a review, which is a word that gets thrown around here from time to time (and, I'd add, isn't a particularly effective criticism). But in my experience, reviewers have no problem reporting criticisms that they feel completely undermine a multi-year study and make a paper unpublishable. :) Therefore, if you've met with resistance in the past from academics with respect to your criticisms, keep in mind that we tend to be quick to defend our work given the rampant criticism we often encounter. Also, it wouldn't surprise me if some academics are more prone to brush off the critiques of "amateurs" simply because they're not also academics. In the case of the folks that frequent this board, of course, you're probably more qualified to critique a study like this--at least with respect to the baseball elements of it--than the academics who actually reviewed this paper prior to its acceptance in this journal. I'd also add that we should keep in mind that, given that the paper has already been accepted, our comments here are very unlikely to affect the paper itself. But that doesn't mean that they won't consider changes for future work. -j
The Tidy Lie (jinaz) —
Studes, If players at one position are better overall than players at another position, doesn't this put players at the weaker position at an unfair advantage if you do such an adjustment? In other words, what's the purpose of those position-adjustments? It's to try to put all positions on an even playing field, right? Because some positions are harder to play, defensively, than others? If there weren't differences among position defensive requirements, you'd stick your best offensive team on the field all the time. So the assumption is that shortstops deserve a boost because they're better defensive players than first basemen. Ok, in current MLB, second basemen and center fielders hit about the same, with a slight edge to center fielders. And yet, center fielders are also better defenders than second basemen (based on Tango's data, at least if they're right-handed, the average center fielder would be a better than average-second baseman), making them a more talented group of players overall. So why should we give second basemen as much of a boost, if not a greater boost, relative to what we give to center fielders? -j
UZR positional adjustments (jinaz) —
By the way jinaz, the Reds have the worst fielding team in baseball, since 2003: -302 runs. Junior is -127 of that. Without Junior, you jump over DRays, Yanks, and Redsox. LOL. er... ::sob:: Go Reds! -j
UZR positional adjustments (jinaz) —
Crap, just noticed that you mentioned arms above. Sorry. Has anyone actually tried to do this sort of analysis to confirm your approximated 1.5-2 run difference? -j
UZR positional adjustments (jinaz) —
Hi Tango, I continue to think that this is some of the most important work on player valuation being done these days. Bravo for continuing it, even if it didn't result in new insights. I wonder about the LF/RF differences. UZR only includes information about out rate on fly balls (right?), but MGL's post on Griffey in the sabermetric thread helped me realize how important preventing runner advancement can be to a player's value. Do you think that if "arm" information was added to the fielding ratings for outfielders that RF would come out as a more demanding position than LF? -Justin
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
Are you guys bored or fascinated by this? I can’t decide where I am here. Fascinated. It's really interesting to see where the market "hits" and "misses." The disparity with respect to releivers in particular continues to be amazing to me. Starter signings like Carlos Silva are also pretty interesting. I wonder if issues of supply also come into play here. After all, there are only so many spots on the roster, so it's not the case that you can always spend in other areas.. -j
Best UZR, 2003-mid07 (jinaz) —
Ok, so current/former Reds on those lists: Reese +10 Conine -12 Encarnacion -14 Dunn -18 Cantu -20 Pena -24 Griffey -31 Yikes. And Reese wasn't even on the team during the period of time sampled. -j
This week's replacement thread... (jinaz) —
As I think of it, replacement level production (offense + defense) is the upper end of production that one could reasonably expect to get from a player acquired from the population of freely available talent. Therefore, given that it's a description of a population (or, perhaps, a subset of a population), it seems rather silly to me to set the baseline to the production of a single player on a single team. Another point, of course, is that even if you're going to define replacement level with a single player, you have to consider both his offense and defense for your baseline to be even remotely relevant. Cust's actual value was lower than what Huckabay indicated because Cust was a below-average defender. I have him at -7 runs or so...not a huge difference, but a difference. -j
SABR's By The Numbers (jinaz) —
Tango, thanks--I didn't follow this blog particularly well prior to this season, so I missed out on a lot of background work. I'll go check some of that out when I get a chance. Also, in #4, my last sentence should have read "Though clearly the high "bust" rate is probably the bigger source of the difference." Never type while holding an unrelated conversation with a coworker. :) -j
SABR's By The Numbers (jinaz) —
I really like Wang's study, because it's so relevant to some of the things I'm fretting about with the Reds talking about shipping off their farm system for Erik Bedard. But I had a question: As I understand it, WARP has an extremely low baseline for position players because it compares players to "replacement level" hitting AND fielding. So if you're using a 75% of league average replacement level in each, then the replacement PLAYER is set to 0.75*0.75 = 50% of league average. Does a similar problem exist for pitchers? Or does WARP use a more reasonable baseline for them? Comparing my RAR numbers to WARP for a few pitchers does still show WARP to be rather high, but I've never seen much discussion about WARP for pitchers. If pitchers are treated more reasonably in WARP, that could be contributing to why pitchers do so much more poorly than hitters. Though clearly the high "bust" rate is probably the bigger source of error. -j
Friend-of-The-Book Indians give non b.s. answers (jinaz) —
Mark, Also knowing that he sucks at public speaking means he’ll try to avoid it as much as possible. He knows he might say something stupid if he says anything at all. Thing is, I'm not sure that he knows that. I'm not a particularly good off-the-cuff speaker, but I compensate for that by preparing bulleted remarks whenever I have to give some kind of presentation (e.g. when teaching). Krivsky seems to just goes into his press conferences with the idea that he'll speak from the heart. The result are very long ramblings in which he says almost nothing over and over. Just carrying a notecard with some key points written down would help a heck of a lot. -j
Friend-of-The-Book Indians give non b.s. answers (jinaz) —
That is pretty refreshing. On the other end of the spectrum is our guy, Wayne Krivsky, who has to be about the most absurdly secretive GM I've ever encountered. Not to mention someone who's among the worst public speakers... -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
I don't remember the incident in question (though I do remember one with Dunn after MacKanin took over this year--though Dunn handled his objections very appropriately), but Griffey was fairly bitter about the position change all season. He usually says something like "I'm just player #3." It's clear he doesn't agree with the idea, and that's among the reasons I've long suspected that he'd accept a trade, especially to a contender that would let him play in the outfield (I severely doubt he'd go to DH willingly). Unfortunately, the Reds won't deal him because he's supposedly too much of a draw, especially as he inches toward 600 hr's. Winning's a pretty good draw too... -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
Jinaz, there is no chance (well, maybe .1%) in this universe that Griffey is a -7 in fielding. I dunno, I'm not sure that he isn't a -7 fielder (pre-position adjustment), at least in terms of tracking down fly balls. Fans have him as ~average overall in RF, and PMR has him at ~-10 runs. That said, I'm not sure that he isn't a -15 fielder either. Your comment about reduced "arm" ratings due to being slow to get to the ball makes a lot of sense, though. Unfortunately, that's not something that I can track at this point, at least not yet. Anyway, I agree that the Reds would be better off trading him if they possibly could. -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
MGL, thanks for the breakdown. I don't include baserunning (aside from SB/CS) or throwing arm in my estimates, so that's a big part of our difference. Using your numbers pulls him down to 9 RAR in '07 using my fielding and offensive numbers. The throwing arm is particularly surprising to me, as Fans seem to rate his arm as a touch above average (could be the veteran player effect, of course). To account for the rest of the 2 wins difference in our estimates, I have Griff at +16 RAA on offense (not sure why we'd differ, but it's only 4 runs), and -7 FRAA in '07 (Fans and ZR put him at about average, RZR has him well below average), which combined is about a win better than you have him in '07. And your offensive projection is 8 runs below your estimate of his '07 production, which accounts for the rest of the difference. So anyway, that explains why you and I had such a big discrepancy. Probably didn't bother you much, but it bothered me! :) -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
Hmm, I had Griffey at about 26 runs above replacement this past season (hitting + fielding + position adjustment). http://jinaz-reds.blogspot.com/2007/11/player-value-part-4-position-player.html Moving to right field helped him a great deal this year, as did the return of his on base percentage. Granted, my fielding estimates are a bit bastardized (I used a weighted mean of RZR, ZR, and Fans to get that number--I'm planning to substitute PMR for RZR, but that will just help Griffey). But I'd be surprised if they're off by 25-some runs. He may decline a bit next season, but I'd be surprised if he goes below replacement-level. -j
Sabermetric Moves of the 2008 Pre-Season (jinaz) —
Mark, I just made a post on my blog that tries to ballpark what his salary "should be" using Tango's methods. I'm sort of new to thinking about contract values in a rigorous way, but my most optimistic estimate is that Cordero has averaged about 1.4 WAR over the past three seasons. That would put him at just $6.5 million on a one-year deal, which is a heck of a lot less than the $11.5 million/season he's getting over four years with the Reds... And that's not even accounting for the age-related dropoff you have to expect from him. Here's my post on Cordero, if you're interested: http://jinaz-reds.blogspot.com/2007/11/reds-sign-francisco-cordero-probably.html As a Reds fan, I'm excited to have the help in the bullpen... but yikes. I hope my numbers are massively screwed up somehow, but I unfortunately think they're probably pretty close. -j
This week's replacement thread... (JinAZ) —
Just wanted to say that I've found this thread to be very helpful in trying to wrap my head around these issues. So thanks everybody. -j
Converting Zone Data (jinaz) —
I had the same question as Rally. I like the idea of using total balls in play - BIZ - non-zone-outs to get a better measure of opportunities for OOZ plays, but I don't quite see how you can distribute that to individual fielders beyond looking at BIZ distribution around the field and basing on that. Maybe doing something like that is still better than just using BIZ or (as Rally does) innings in the denominator for OOZ, but I'd have to play around with the data. -j
Best and Worst of 2007 UZR (jinaz) —
#34, That was Steve PHILLIPS! Just take the opposite of whatever he says and you pretty much can’t go wrong. LOL! Yeah, that's about right. I still try to keep an open (yet critical) mind about stuff he says--thanks to you and Rally for taking a look. I have to say, though, I'm getting incredibly tired of his constant concern about how "into it" the fans are at games. I just can't imagine that has a significant impact on anything except maybe communication among fielders on pop-ups. -j
Best and Worst of 2007 UZR (jinaz) —
Thanks for taking a look! Always interesting to test claims like that. :) -j
Best and Worst of 2007 UZR (jinaz) —
Speaking of defensive park factors... Listening to the Col/Phi game right now. Steve Phillips just commented that an outfielder (I think it was Victorino) had an advantage in his home park because he knows the dimensions and therefore knows how much room he has and where balls will land. The prediction from this idea would be that the average park should have a positive outfield fielding park factor, at least based on home team performance only (i.e. ignoring visitor defenders). Anyone ever looked at this? Just curious. :) -j
What stats should we use to represent how good a player IS? (jinaz) —
Assuming the correlations reported are correct, we're looking at: r=0.588 for previous year r=0.636 for current year r=0.651 for last two years r=0.666 for last hree years Granted, the three-year data are better. I'm not really disputing that. But how much better? An improvement in the correlation of 0.03 seems like a minor improvement to me. In fact, I'm surprised how small of an improvement we're seeing here. To put it another way, you claim that 0.588 is "not too much different" from 0.636. So what's the motivation to go to 0.651, or to 0.666, when those are smaller jumps than 0.588-->0.636? Just playing devil's advocate. Mostly. I have recently posted some postseason team profiles that include only '07 stats, mostly because I can get them quickly. When evaluating the individual players in the profiles, I take a look at their previous season's stats, as well as things like babip, props, fip, etc, that can give indications of lucky/unlucky performances in the current season. It's perhaps less objective than three-year weighted and regressed averages, but it's less work and probably comes to similar conclusions most of the time. -j
Best and Worst of 2007 UZR (jinaz) —
Rally/19, that's awesome! Dave/20, Anyway, getting back to Rally’s point, it seems clear that the OOZ plays are the difference. All eight guys with 70+ OOZ plays by BIS data are ranked massively better by RZR than Stats ZR. This is probably due to how OOZ plays are handled in STATS Inc's zone rating. They calculate it as (plays+ooz)/(biz+ooz). This massively devalues OOZ plays. The approach I used is basically (plays/biz) + (ooz/biz), which is the same as (plays+ooz)/biz. I compared these approaches here last spring using the "raw" THT data: http://jinaz-reds.blogspot.com/2007/03/how-should-we-calculate-zr.html Including OOZ in the denominator is results in almost exactly the same estimates as leaving OOZ plays out altogether. Furthermore, I did some later work: http://jinaz-reds.blogspot.com/2007/03/how-should-we-calculate-zone-rating.html ...that indicated that a 1:1 weighting of BIZ and OOZ provided the best match to PMR at all positions except 3B. That, of course, doesn't mean it's the right way to do it. Just that it's consistent. I guess we could exclude OOZ plays altogether from outfielders because of the problems associated with ball-hogging. But I tend to think that they provide a lot of useful information, so I'm hesitant to do this. For example, Griffey is rated as an average fielder in RF if you look only at balls in zone. It's the out of zone plays where he's well below average. Given his performance in CF the past several years, I tend to think that a below-average rating in right field is the more correct conclusion, and you only get that by including ooz information (this also conforms to UZR ratings). -j
Best and Worst of 2007 UZR (JinAZ) —
John Dewan published BIS +/- leaders & trailers at shortstop last week at Stat of the Week. Thought they'd be interesting for comparison: Tulowitzki +34 McDonald +26 Vizquel +19 Bartlett +18 Pena +18 Eckstein -15 Young -15 Harris -19 Ramirez -35 Jeter -35 Tulowitzki, Visquel Pena, & Bartlett all show up on MGL's top-3 lists, while Jeter, Young, Ramirez, and Eckstein all show up on the bottom-3 lists, so there's good agreement overall. The simple THT+- conversions I did at shortstop had a correlation of 0.95 with Dewan's data (biggest discrepancy was Harris). RZR, of course, is based on the same raw data as Dewan's more advanced +-, so you'd expect a fairly high correlation. But I was encouraged by that. THT vs. UZR tend to have weaker correlations with one another based on past data, which is discouraging. But as Michael Humphrey's study at THT showed, there seem to be differences in the data provided by BIS and STATS. -j
The Joba Rules? How about the Papelbon Program? (jinaz) —
Wow. Why aren't all teams doing this sort of thing with all of their young pitchers on a daily basis? Seems like an awesome way to help prevent (and get early detection of) injury, which I'd think would be worth the cost of deploying this kind of system. I would love to see what 2-3 years of collecting this sort of data on all players within a team's system would tell us about pitcher usage, how pitchers vary in their resilience, etc. -j
Good samaritan translator arrested, awaiting trial... (JinAZ) —
Did a quick google search -- there are articles and editorials about this case dating back to late July. Apparently the initial publicity didn't result in the dismissal of the case that it should have. It's a shame that the actual arrest happened off-camera. Video of the policeman tackling the woman as she was trying to borrow a cell phone would have resulted in a heck of a lot more attention that this case has gotten thus far. The conflict of interest at the prosecutor's office is mind-boggling. -j
Good samaritan translator arrested, awaiting trial... (JinAZ) —
Wow. Hopefully the newspaper column and the ensuing publicity will help matters. This is just awful. -j
The Modern Day begins in 1947 (jinaz) —
I think that the initial point is a very good one, and I completely support it. Not that you needed my affirmation, just wanted to say that. :) -j
Mariner OF defense: from fantastic to horrible (JinAZ) —
Franklin's 3.57 ERA season in 2003 is often cited as one of the great fluke seasons in recent years. He had an 0.235 BABIP and a 5.21 FIP that year (4.2 k/9, 2.6 bb/9, 1.44 hr/9). Some of that BABIP can be credited to the defense, I'm sure, but not all of it. -j
Mariner OF defense: from fantastic to horrible (JinAZ) —
The thing you more commonly hear--and I myself have said it--is that you might be willing to give up defense for offense on the corners, but focus on defense up the middle. That seems to be what the M's have done. Obviously it has made things harder for their pitchers, but if the offense is there it might be a smart move.. So I guess my question is whether defense should be weighted differently at different positions. In other words, in a total assessment of a player, do you weight defense as 70% of the value of a ss/2b/cf/c, and 30% of the value of a 1b/3b/rf/lf? Or is a run saved worth the same (or even more?) than a run scored? -Justin
The Complete Dewan Fielding Plus/Minus (JinAZ) —
However, I am surprised they haven’t developed and published their own advanced fielding metric You'd think that has to be in their pipeline of important things to do soon. At this point, their continued reliance on Davenport's fielding translations for present-day fielding evaluations makes it hard to take a lot of their work seriously--including other important stats that rely on it. -j
The Complete Dewan Fielding Plus/Minus (JinAZ) —
Great to hear a) that THT will start streaming their ZR data soon, and b) that we can expect a fielding bible in 2008. Very exciting. I'd also gladly purchase a fielding bible each year. -j
Measuring Plate Discipline (JinAZ) —
Thanks for posting those data! -justin
UZR, 2007, complete list (JinAZ) —
Thanks for this! Just in time for some Reds stuff I was about to do. -j
Marketplace (JinAZ) —
In that case, we’re better off having a bibliography page online. It maintains its relevancy, and would be read by far more people. That would be a fantastic resource for those of us who are still learning the basics of the literature. -j
Runs Allowed, Relative to Teammates (JinAZ) —
Reds have had a great offense, particularly during Harang's very good 2005 season, so again this does make some sense. -j
Runs Allowed, Relative to Teammates (JinAZ) —
Harang makes a lot of sense. Over the last two seasons, he has been a solid if not very good pitcher on the Reds' otherwise absolutely miserable pitching staff (see especially 2005). If I understand your methodology, the awfulness of the Reds' pitching from '04-'06 should give a quality pitcher like Harang an extra bonus relative to players on other teams. If he was part of an otherwise-average pitching staff, he wouldn't show up as brightly as he does here. -j
Who gets Jessica Alba? (JinAZ) —
Maybe this is going to sound too political, but.... I visited that site some time ago, and it declared that George W. Bush was my most compatible celebrity, with the highest ratings on intellect! I screamed and clicked away from that site as quickly as I could, vowing never to return again. :) -j
What should you do when a pitcher has just thrown a bunch of balls in a row? (JinAZ) —
That would be particularly interesting if we looked at it in terms of effectiveness after throwing a large number of pitches to a single batter. You often hear announcers go on about how a terrific at-bat (defined by seeing a large number of pitches) tires out a pitcher either mentally or physically (or both), allowing subsequent batters to get him. The problem is controlling for other factors...like the probable case that pitchers who can't get a batter out and thus throw a large number of pitches aren't likely to be on top of their game. I'm not sure how to approach it. -j
Hey Jeter, I've got your back! (JinAZ) —
Junior has often (at least for the past 3 years) been backed up in CF by Ryan Freel, who is a plus defender, especially in the outfield. That, coupled with Griffey's misery as a defender, makes a pretty big differential... -j
What should you do when a pitcher has just thrown a bunch of balls in a row? (JinAZ) —
The one difference between a the gambler's fallacy and this situation is that this situation is not a random process. Throwing a strike is a difficult thing, and if a pitcher is struggling badly with his control (which was the case in this situation), then it might, in fact, be more likely that the next pitch will be a ball. The context of the situation does matter. It is not the same thing as a coin flip, which is always random. If a pitcher is struggling with control, my take advice is to look for one specific pitch in one specific location, but otherwise lay off it. But hey, what do I know. :) -j
That's troublesome to me. What do you folks think this means for estimating the expected number of plays per BIZ when looking at this years' stats? I was planning to use the 2004-2006 totals posted by Tangotiger in comment #4, but now I'm wondering if just sticking with 2006 data ratios might be more accurate given the change in the system. Regardless of what I use, it'll have issues... -jBIS Fielding Data (JinAZ) —
BIS Fielding Data (JinAZ) —
Joe, I did, in fact, use the distance/100 PMR data when it was available. Thanks for the comments. -j