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For an early afternoon weekend game, what’s the best thing to do for a driver from NJ? Walking has to be limited to five minutes, and once I leave, I don’t want to contend with more than 5-10 minutes of traffic. What are my best non-rail options?
I love this guy. He says the exact same things we do, but he says it while wearing a uniform. Because of that, the media shuts up and listens to him. I mean, just read his gems:
“It’s like flipping a coin. Everyone knows that you got a 50-50 chance of heads or tails. But maybe during the course of a baseball season, you flip it and it comes up heads seven or eight times. But over a million times, it’s going to come back to about a 50-50 ratio.”
...
“In terms of baseball, even the best teams need some luck. You have to have skill but you have to have luck, too.”
...
“This year is really the first time in my career it’s gone the other way. In 2007 I was lucky, 2008 I didn’t pitch that well, 2009 I pitched well and this year, I haven’t pitched great, but luck has been against me, too.”
...
“The reality is it’s a performance-based game,” he said. “It’s a business. So if you’re not performing well, it doesn’t matter why.”
...
“If it’s a mechanical thing, there would be something way out of whack with my peripherals, like my strikeouts would be way down or walks way up,” Bannister said. “I typically strike out about 5.5 guys a game and my walks are around three. I’m still right around there.”
...
“We’re in a stretch where I probably have flipped heads nine times in a row,” Bannister said. “I’m just saying if you get in a stretch like this and you start changing a lot of things, you can really get out of whack.
...
This year, the home-run thing has been frustrating but there is nothing that has changed with me. My career average says I’m right at a No. 4 starter.
“My goal is to pitch at a No. 3 starter level. Sometimes you get to No. 2. Sometimes you drop down to No. 4 or No. 5, and after that you’re in the minors.“But I won five games in a row earlier this year and I was the same guy. Really.”
G-dd-mn beautiful.
Bannister has a career rate of 10% HR per FB, pretty much the league average. In 2010, he’s at 14.5%. With 150 FB, that puts him at 2 SD away. Given that we cherry-picked him, and given that we expect someone to be at 2 SD, there’s nothing there. Not unless you also tell me the HR he gives up are going farther as well.
And maybe they are. Last year, he had 8 HR go for at least 410 feet. This year, he already has 10. In order to figure out how significant that is, we need to see what it means to other pitchers. This may be the kind of indicator that can tell us if allowing long HR means something, similar to Bannister’s point here:
“A guy that worked at JP Morgan was doing a project on sports and the stock market and games in general, and what had more influence, skill or luck,” Bannister said. “He had this huge timeline. The most skill was chess where luck had the least influence. Then it was running, golf and tennis, and then you get to baseball right in the middle.
Is giving up long HR something basic, something that is mostly the domain of bad pitchers? Greg has the data there ready to be downloaded. You guys tell me.
What you CANNOT do is look at average HR distance. Please, don’t do that. Please. We’ve talked about this.
If you go for the ambience, apparanently, it’s never too far.
I’ve sat pretty far away at Olympic Stadium, out in LF. The way it was setup:you had the bleachers, then you had the bullpen area, and then more bleachers. That’s where I was. You couldn’t even see the thrown ball. It was stupid and silly, and quite fun, if you are with the right crowd.
But only for baseball, and soccer could this make sense. In hockey? No, you need to be watching the game at all times. Basketball? I couldn’t even imagine it would be worthwhile to even be in the upperdeck. Football? Maybe, but I don’t think so.
The reason? I think it has alot to do with whether it’s important that you know where the ball is. In baseball, the positioning of the players tells you where the ball is, even if you don’t know where it is. You follow the players mostly. In soccer, the players are spread out, like in baseball, so it makes them easier to follow. In hockey, you follow the puck. Basketball and football have clustered players as well.
Anyway, teams that embrace family pricing for baseball are being smart: you need to get them in cheaply, and they can buy the expensive food. Like movie night Tuesday.
A fun read, with some behind-the-scenes talk from wind engineers.
This is from Greg.
It shows the minimum Speed off Bat required for a particular elevation angle in order to get a fly ball over the Green Monster in Fenway Park (at a point where the wall is 342 feet from home plate, roughly between straight-away left field and left-center field). On the plot, any ball above the curve is a homer, anything below it is a non-homer.
Re-read Greg’s description 2 or 3 times and then look at the image again. (Image is also clickable if you want to see it bigger.) This is how I responded at first glance:
Whoah, this is really cool.
So, we can even say that there is an “optimal” launch angle for each park, based on speed off the bat, and spray angle.
If you have a RHH pull power hitter (average spray angle of say -20 degrees) who hits fastballs at 100mph off the bat, then his optimal launch angle at Fenway might be 30 degrees, while in other parks it could be 27 degrees. And if he’s a weaker hitter, he might maximize his talent by launching at Fenway at 21 degrees, while he might launch at 23 degrees in other parks.
Yowza.
Good look from CarsonESPN:
A study by Dan Turkenkopf of The Hardball Times shows us that The Cell and PETCO have HR/FB indices of 118 and 75, respectively. What that means is that if you multiply those numbers by .11 (percentage of all fly balls that become numbers), you discover that about 13 percent of fly balls become homers in Chicago, versus only about 8.25 percent in San Diego.
Carson’s forecast is for .12 HR per IP, or about 21 HR in 175 IP. The FANS have him at 18. Chone and ZiPS are in-between these two numbers.
A lot! We sometimes talk about a team’s strength of schedule and how it might affect its win/loss record (not much, I think). We sometimes even talk about a team’s strength of schedule in terms of how it affects individual players. Of course, if you use BPF and PPF (batter park factors and pitcher park factors), like what you see on B-R, you are automatically adjusting for the pool of pitchers (for batters) and batters (for pitchers) that a player plays against, but even those numbers assume two things which are not true: One, that there is a balanced schedule, which there isn’t, and two, that players on the same team play an equal number of games against the same opponents, which they don’t, especially pitchers.
Anyway, I am not here to talk about the strength of a player’s pool of opponents, although that is an important discussion in and of itself. What about opponent park factors, or the average park factor that a player faces on the road? The same thing that I said above is true for road park factors. For one thing, the unbalanced schedule means that, for example, the Dodgers, Giants, and the Padres play a lot of games in ARI and COL, the two most hitter friendly parks in the NL. And pitchers, especially starters, because they don’t pitch every day, may play an inordinate number of games in one park or parks or another. This can make a big difference in terms of their raw, unadjusted (by their road parks) stats.
IOW, when park adjusting player stats, you really have to know their “average road park PF” rather than just using the “other parks factor” (which is 1 minus your home park PF divided by 13 or 15) which is traditionally used in park factor adjustments.
For example, let’s say that the Padres PF is .85 . That means of course that you would adjust a home stat (in runs) by dividing it by .85. Traditionally, for the road stats, you would use the “other parks factor” of 1+ .15/15, or 1.01. IOW, if the Padres have a PF of .85, all the other parks in the NL must have PF’s of 1.01 for everything to equal 1.00.
But, as I said, because they play lots of games against the D-Backs and Rockies, they play lots of games in two parks that have PF’s of around 1.10 and 1.20 and not 1.01 (the average park in the NL other than ARI).
Anyway, what I did was to compile the average road park factor for all players in 2009. You will be surprised at some of the results:
Here are some Padre pitchers and the average park run factor of all the road parks they played in prorated by the number of TBF in each of those road parks:
Peavy 1.00 So he did in fact play in average road parks (actually not the 1.01 that you would expect)
Mujica 1.03 So if his road ERA were 5.00, that would actually be 4.85 after park adjusting it, which would make a difference of .05 runs in ERA overall (as compared to if you used the generic 1.01 for his road parks)!
Chris Young 1.04 Besides sucking due to a large decrease in velocity, he also played in heavy hitters’ parks on the road, costing himself .075 in overall park adjusted ERA.
Gaudin 1.03
What about some COL pitchers? If you used the traditional “other park factor” you would adjust (divide) their road ERA’s by a factor of .988, since COL has a PF of 1.18.
DeLaRosa was .97, one reason why his stats were so good! He is benefiting overall by about .05 in ERA.
A bunch of relievers actually had road park factors of .94 and .95, even in a decent number of TBF, like Rincon, Daley, and Peralta.
Poor Glendon Rusch, aside from being a bad pitcher, his road park factor was 1.03!
Arizona pitchers have an “other park factor” (again, assuming that they play an equal number of games in all NL parks) of .993. Here are some pitchers who were pretty far from that:
Buckner .95
Petit 1.01
Vasquez .96
For batters, since they tend to play every day, the variations in road PF are not that great.
Here are the players, pitchers and batters, who were helped or hurt the most by their road PF’s, minimum of 150 TBF or PA in their road games:
Batters
Hurt
Carlos Gonzalez COL .96
Fowler COL .97
Iannetta COL .97
Carlos Ruiz PHI .97
J Hamilton TEX .97
A Jones TEX .97
Helped
Delmon Young PIT 1.03
McCutchen PIT 1.03
G Jones PIT 1.03
Pitchers
Hurt
Troncoso LAN 1.04
C Morton PIT 1.04
C Young SDN 1.04
Helped
B Buckner ARI .95
J Martin WAS .96
Sonnanstine TBA .96
Hunter TEX .96
Nippet TEX .96
Once you throw in the weather issues that I talked about the other day, and a player’s personal SOS (the quality of the pool of opponents they happen to face), I think you have quite a bit of context for a lot of players that is not accounted for by traditional park adjustments. Given the ease that these things can be computed with simple database queries, I would hope that sites like B-R will eventually include then in their OPS+, wOBA+, ERA+ and other stats.
It is said that one of the reasons for year to year variation in park factors is weather. For example, one year could be a particularly hot or cold year and thus a park can be more of a hitters of pitchers park than it is over several years. Same thing with wind. There can be other things that affect a park’s true factors from year to year besides weather of course.
Because there are much larger random fluctuations from year to year than those caused by weather (and other things), we usually use multi-year park factors when doing some sort of park adjusting.
Out of curiosity, I looked at average yearly game-time temperatures at all the parks from 00-09, at least according to retrosheet, and compared them to each park’s multi-year (00-09) average.
The SD of temperature per year per park is around 1.70, which means we can reasonably expect variations of up to 5 degrees or so. That is not going to terribly influence a yearly park factor, but it will influence it a little in some cases.
A degree in temperature is worth around .033 runs per game, so if a park is “off” by 3 or 4 degrees in any one year, it will change the run factor by around .012. IOW, a neutral park will have a 1.012 RF if it is warmer than average by around 3 or 4 degrees. The home run park factor will presumably be affected much more than that.
Just last year here are some example of parks whose average game-time temperatures were more than a few degrees wamer or colder than their 10-year (00-09) average.
Team Avg. temp. 09 temp. Effect on park factor
ARI 77.8 83.4 .018
CHC 69 63.9 -.019
STL 77.6 74.4 -.012
BAL 79.2 74 -.018
CWS 69.3 64.5 -.016
TOR 72.3 68.4 -.014
Also, one of the reasons for the low run scoring the last 2 years, besides less PED use (presumably), is that it was a little colder in both the NL and AL in 08 and 09. Last year, it was .5 degrees colder in the NL and 2.1 degrees colder in the AL, compared to the 00-09 averages. (So much for global warming.) That alone would reduce run scoring in the NL by .017 runs and in the AL, by .07 runs, not much but something.
For the record, according to my research, the NL and AL combined lost around .11 net runs in talent from 08 to 09. (Oddly, OPS (SLG only) went up a little from 08 to 09, but run scoring went down a little.)
Anyway, if you work with park factors, I suggest that your adjust each year by temperature. For example, if your multi-year run factor for Chase Field is 1.08, since last year was a particularly hot year (they might have just kept the roof open more to save money), you would use a run factor of 1.10 for 2009 rather than 1.08.
I might look at the same thing tomorrow for wind. Unfortunately, the wind data that are recorded for parks are notoriously unreliable, at least as far as the actual wind on the field is concerned.
My. Oh my. Oh my. Courtesy of Sean at Katron.org. This image is Safeco batted ball imposed onto Fenway. Yeah, I know. Coooool.
(All you guys are so ~!@#$ awesome. Seriously. I’d put a hundred of you guys into a blender and create the perferct sabermetric monster.)
Beautiful work as usual.
I’ll forgive the slight against the Expos.
At any rate, if people like stupid lists, that’s perfect for me. My two specialties are making lists and being stupid. This is right up my alley. Besides - it’s the off-season. If it wasn’t for dumb lists what the hell would we have left to talk about?
This week’s dumb list: ranking stadiums I’ve attended. No, it isn’t even a remotely deep or original idea. It’s still a fun, dumb column to scrawl out, though.
I’ve been to very few, so my list is:
Fenway
Yankee
Skydome
Big O
Shea
You really need to cozy atmosphere. For example, at Le Forum, it was GREAT. In the new arena (Bell Centre), I went to see the 1996 World Cup, Canada v USA. One set of friends sat in the lower level, and we sat in the upper level (but right at the first row of the upper level). In talking to him after the game, it was as if we saw two different games. We thought the game was good, and he thought it was incredible. Basically, we got the TV angle, and some of the fan response, while he got the ice-level view with great fan response.
I’ve had the same experience at Giants / Jets stadium, where when we sit in the top level, it’s one feeling, but down in the bottom level is a whole other thing. I think their new pricing for the new stadium reflects that. I would say it’s fair that if you have a 75$ ticket for the upper level, that that’s the same as 300$ for the lower level. I think in all the sports, the price between the worst ticket experience and best ticket experience in the same stadium should be about 3x to 5x. (Excludes courtside seats, and obstructed view seats.)
In a great article in Hardball Times annual, Greg looks at the batted balls at the new Yankee Stadium and Citi. The interesting finding is that while Yankee Stadium turns long flyballs into HR, it also turns almost-long flyballs into outs. Citi field however turns almost-long flyballs into hits. So, this would be an example of where the HR park factor and the Runs park factor on non-HR are not directly related (either unrelated, or inversely-related).
Ideally, we’d have a ballpark overlay tool, like this one, but for all batted balls, not just HR:
Studes: any chance you can put up a “preview” of each article in Hardball Times Annual, like we did for The Book? It would certainly make life easier to link to various articles in THT 2010. I’d say showing 5% to 10% of each article on the website would be perfect.
My answer must be: Yes, you are totally right, in response to this reader mail:
Eric makes his case:
If UZR had no park error, this estimate of staff BABIP skill would not correlate with our very reliably calculated Park Factors. But it does so, enormously (r = .47, p = 10^-15). In fact, the best predictor of what UZR thinks is staff BABIP skill is .751 * Park Factor. Which is an awful lot.
I dunno… my head was spinning quite a bit there. I think you would jsut need to correlate UZR to BPro’s park factor for BIP, much like I have it here. In that chart, we see that Coors and Fenway were fielding-unfriendly and Dodger and Yankee Stadiums were fielding-friendly. So, when you run your correlation, if UZR has properly handled the park effect, then the correlation should be close to zero. Eric howver is reporting a high correlation, but ... to something. I don’t like the way he says that if you subtract this from that, you are left with the other thing. Luck is always part of the equation too.
Now, the first thing that jumps out at you is that there’s no way the 2005-6 New York Yankees were both the worst fielding and best BABIP-pitching team in recent memory. They were certainly bad at the former and good at the latter, but the size of the numbers suggests that their UZR for those years was low, maybe way too low, and thus the data is giving their pitchers undeserved credit and Derek Jeter their fielders too much blame.
Equally suspicious are the ‘06-’07 Royals, who are the opposite. The ‘03 A’s, another crazy good-fielding, bad pitching team, are also suspect.
In fact, if UZR were doing a perfect job of separating fielding from BABIP skill (which is precisely what it is attempting to do), these two tables would not correlate at all. In fact, they have a mild inverse correlation (-.18); you can predict the numbers in the second table to a mild but very significant degree by multiplying the first table by .16 and flipping the sign.
I think at the least he’s given us enough to consider in order for us (or MGL) to show that bias does not exist. If it shows that we have an inverse correlation, then we can be pretty sure that the level of adjustment is not enough.
(and a portion, around 1/15 or so, of the home stats of course.)
I have thought about and written about this before, and this piece by DC got me thinking about it again.
Assuming that park adjusting home stats are problematic because we think that parks affect different hitters differently, there must be a point at which it is better to use road stats only (adjusting for HFA of course) plus a small portion of home stats, rather than using all of the home stats after park adjusting them. This is with respect to “neutralizing” a player’s stats of course, in order to determine his context-neutral true talent.
What point would that be? IOW, how many seasons or PA? Would you only even think about doing that for non-traditional parks, like Coors or Fenway? Would it matter if the player had extreme splits or not?
Or perhaps it is correct to always weight the road stats more heavily. If yes, by how much. And again, would you weight or weight them more heavily for players playing in unconventional parks or for those that had unusually large or small splits (for their home park)?
The Mets’ manager seems to think so:
“We’re going to try to build a team with speed and defense and pitching,” Manuel said. “I think that fits that style.”
So do 99.99% of all people who think they know anything about baseball.
In keeping the Bill James tradition of, “Is that true?” alive…
Is that true? Is there any evidence that that is true? Has anyone done a study on this? Seems to me that it is entirely possible that it makes almost no difference at all (especially since there really isn’t THAT much of a difference between parks and it is only in the far reaches of the OF of course), or that it is the opposite. I have looked at this issue from time to time and I don’t think I have ever come up with anything definitive, or I should say, compelling, one way or another.
BTW, one sign of a really poor manager or GM is when they make definitive statements about something that they clearly know nothing about. If they do that for one thing, how many other things do you think they do it for? Successful people in all fields always question what it is they know and don’t know and why. Ignorant and unsuccessful people do just the opposite (think they know lots more than they really do).
What say you guys?
Matt gives us a ton of data. You can also check the archives for a similar topic that Phil Birnbaum had when he looked at it by travelling through time zones.
Note that Matt uses “statistically significant” an obscene number of times, when really what he is saying is that the DIFFERENCE between the actual and the expected is non-zero at p = .05. That is, if Matt says that there is a statistical significance between seeing a .540 against an expected .550, he is NOT saying that the .540 is real. He is saying that something OTHER THAN .550 is true, and he’s 95% sure of that. It could be .549. And, it even depends if he did a one-tail or two-tail test, because it could even mean that .551 is also true. All we know is that there is something non-random going on, but we don’t know how much of it it is.
UPDATE: this was Phil’s article.
May 16 23:50
Now you frame it, now you don’t
May 16 23:47
Dodgers’ win reversed because Mattingly did not attest to proper score!
May 16 20:44
How to beat the shift
May 16 20:02
Sponsoring MLB jerseys
May 16 16:56
Did Manny Pacquaio actually quote Leviticus?
May 16 16:06
Does changing your pitch frequency lead to substantial change in results?
May 16 14:18
Extra Innings: One-minute review
May 16 14:16
This particular criticism of UZR is unfounded
May 16 13:21
Psst… wanna intern for the Astros?
May 16 12:23
Arena wars
THREADS
May 16, 2012
Now you frame it, now you don’t
May 16, 2012
Dodgers’ win reversed because Mattingly did not attest to proper score!
May 16, 2012
Does changing your pitch frequency lead to substantial change in results?
May 16, 2012
Sponsoring MLB jerseys
May 15, 2012
Andre The Hawk Dawson speaks
May 15, 2012
Euro 2012 Preview
May 15, 2012
How to beat the shift
May 15, 2012
Will Pujols end the season with at least 30 HR and .500 SLG?
May 15, 2012
Kershaw v Strasburg, part 2
May 15, 2012
Did Manny Pacquaio actually quote Leviticus?
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