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Scouting
Wednesday, April 28, 2010
By , 02:15 AM
About 3 weeks ago, Matt Swartz wrote an article on BP that concluded fairly emphatically that players (pitchers and hitters) who sign multi-year deals with their own teams aged and performed significantly better than those who did not. To be honest, I did not re-read the article carefully and it is not real clear what the criteria were for the various groups of players.
Here is what he wrote at the end of the article:
What appears to be happening is that teams seem to have some sense of the aging curve of individual players, especially if they are already in their organization. There are probably a variety of reasons that this subset of players aged well, but the team knowledge about the player’s medical and scouting information appears to contribute to the decision to give a player two-year deals. This is important to keep in mind when we hear of a player signing a new contract and look to a projection system to figure out how smart the deal was. Chances are that there is additional information—especially about aging—which teams have that we may not.
Today, he wrote a long article telling us why the Ryan Howard contract might not be as bad as some analysts are making it out to be. One of the reasons he cites that it may not be so bad is that because Howard is signing with his own team, he may age better than we think (using comparable players, the traditional aging curves, etc.).
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Tuesday, April 27, 2010
By , 04:07 PM
http://www.nypost.com/p/sports/yankees/second_to_none_2ELierhYWKOJFwCRv3Gz6K
If you are an MLB team, you want very specific and limited information from your scouts and then you can integrate that into your player evaluation methodologies. If you rely on your scouts to estimate player value or compare players for valuation purposes, you are in big trouble. Ryan Howard anyone? I’m sure scouts love him.
Wednesday, March 31, 2010
He says:
Tulowitzki is very aware of the zone ratings measurment, but says it only goes so far in accurately assessing how effectively a shortstop plays the position.
“Say a ball is hit in the hole (between third and short),’’ he said. “Some guys will take an angle that may or may not get them to the ball, knowing that’s what they need to do to get the out.
“And some guys will take an angle that will get them to the ball, just so they can get to it, but not have much chance to throw the (runner) out. That makes their rating look better.’’
I’m trying to follow his logic. Let’s see. In one version of Zone Rating, an out-of-zone play counts in the denominator (and numerator), if you get the out. If you don’t get the out, it doesn’t count (in either numerator or denominator). In another version of Zone Rating, an out-of-zone play does not count in the denominator, even if you get the out. (An out counts in the numerator.) So, on out-of-zone plays, it doesn’t matter if you reach the ball and not make the out. It’s not going to hurt more.
Tulo is thinking that you get credit for “touches”, whether it leads to an out or not. He should feel assured that the bigshot fielding metrics are not doing what he’s criticizing them for.
The Mariners GM says this:
I’m amazed over the course of my career about the (scouts) who have put their necks on the line because of what they knew about a player, and they turned out to be right. In the same sense, you have to look at the numbers to confirm things.
That is one thing the scouts have over the numbers guys. The numbers guys will have a high uncertainty level with a small sample size. A scout’s uncertainty level will not change much after a certain point. This is why the Fans’ Scouting Report is so powerful. A fan doesn’t need to see a player alot to cast his judgement. But, UZR and the other fielding metrics have a high level of uncertainty to them. Once you’re up to 3+ years of fielding data, then, yeah, the scale tips towards the numbers guys. But at less than one year, it’s the scout that counts the most. And that’s why a scout will always be important, because he can provide the low uncertainty level that the numbers-guy can’t, in the face of limited sample size.
Monday, March 01, 2010
This is exactly how I think about it too:
Sabermetricians do not understand the human element of the game. There, I said it. My question is, who died and made (insert favorite MSM punching bag) an expert on the human element? Oh sure, he probably played the game. But then, I drive a car every day, and I have no idea how the thing works. He probably talks a lot about the human element, but talking a lot about something and having an idea of what you’re saying are two different things. They’re called politicians.
I find it funny when sportscasters talk about, with absolute certainty, that a player can’t handle pressure or that he’s clearly being bothered by some event or other that happened in the past (Hi there, Mr. Lidge. I didn’t see you over there. Remember that home run you gave up five years ago? Would you like to see a replay?) It often drifts into the realm of practicing psychology without a license. Or sometimes, a clue.
I can’t say that I blame the pundits, reporters, and commentators for engaging in this sort of talk. They are, at their core, trying to produce an entertainment product for their audience, and people want to feel connected to the emotional experience of the game.
Right, exactly.
1. Saberists only (try to) understand what the data is telling them
2. Gasbags need to engage in gasbaggery
3. For some gasbags, after engaging in said gasbaggery, start to believe their own gasbaggery
It’s #3 that’s the problem.
Wednesday, December 30, 2009
Where do you see advanced metrics in 10 years? Fad? Major part of a front office operation? Replace traditional scouting?
Fad? You haven’t seen anything yet. Wait until PITCHf/x, FIELDf/x, and HITf/x take shape. You will wish and pray to get back to the simpler times of 2000s. The 2010s will bring an avalanche of data. It will absolutely be a major part of the front office. The best-case scenario is that you have all these f/x systems set up at colleges and high schools. Instead of one scout seeing one game of some prospect in one town, while missing a game on another town, you will have every single pitch charted, every swing charted, and every single fielder charted. The question is to try to identify all of the contributions of each player to each pitch and each play. Having a summary opinion without evidence is bullsh!t. Scouts have summary opinion on limited amount of data (say they see 5% of someone’s games in college). That’s valuable. Now, imagine having a summary opinion based on 100% of the data?
And no, it will never replace traditional scouting, because as I said, you will always need two lenses to your glasses. It will certainly make him more efficient. Instead of seeing 5% of each player’s games, maybe he will see 30% of the games that the f/x system is high on, and only 2% for the less-than-stellar players. It’s another tool they can add, in addition to their radar gun.
If the goal of this industry is not to advance it monetarily or its role in MLB, then why have it? What’s the point? It seems like a very time consuming hobby with little reward.
The hobby itself is its own reward. You may as well ask the millions of bloggers why they blog. Those things also consume time. Why do you go watch a movie? Why do you have dinner with friends? In those cases, you actually pay with money to get your reward. In this case, the payment is time. And, we are more than happy to give it, especially if others also give their time. We all benefit.
Making money and having a role in MLB is a byproduct. I wrote The Book, and I spent several hundred hours on it, if not 1000 hours. And I made less than minimum wage. Based on your line of thinking, I’m crazy and stupid. Yes, you are probably right. But, that doesn’t mean I shouldn’t have done it, nor does it mean that others did not get a bigger benefit of it than I did. Yes, I’d have loved it if we had sold a million copies rather than 1 percent of that, so I could turn my hobby into a full-time profession. But this is true of anyone who has a hobby. It’s ideal if your hobby and your living can merge. But you are not going to stop your hobby if you can’t make money out of it. Your hobby is all about trading time for enjoyment. My job is what I do. My hobby is who I am.
Wednesday, November 25, 2009
By , 09:30 PM
His name is Jeremy Greenhouse (I never heard of him before).
http://baseballanalysts.com/archives/touching_bases/
Thursday, November 05, 2009
I will close balloting Monday night. If you haven’t voted, here’s your last chance.
Friday, October 30, 2009
Rally commented:
[Tim McCarver] said something about Melky having an arm that is just slightly above average. Not an informed comment at all. Does he even watch the games? Does he forget everything that happened a week or 2 ago? In game 3 of the Angels series, when Mathis hit the game winning gapper, there was no chance to throw Kendrick out. But that didn’t stop Melky from trying, and he threw the ball on the fly from left center to a spot about 10 feet in front of home plate. Very impressive throw indeed.
What did MLB fans say? The strongest arms in CF in MLB: Ankiel, BJ, Kemp, Hamilton, Victorino, Melky .... (bottom 2 Jacoby and Coco). Even if you don’t buy the Fans literally, arm strength is one of the easiest things to observe, and he’s at least well-above average.
Tuesday, October 13, 2009
Devil Fingers gives us his chart, and we can compare that to the Fans.
The answer for “best” seems to be Gerald Laird or Yadier Molina. Laird was #1 for Devil and #3 for The Fans, and Molina was #1 for the Fans and #5 for Devil. Ryan Hanigan of the Reds was #4 for Devil and #4 for The Fans.
As for the bottom, you have a few to choose from, among the consensus: John Buck and Miguel Oliva (both Royals), Mike Napoli (Angels), and Josh Bard (Nats).
Monday, October 12, 2009
This is your last chance to submit a ballot. Balloting will close on the day after the World Series ends.
I have updated all the team rosters, so there may be a few new players since I created the ballots in mid-August, like Drew Stubbs with the Reds, who played full-time starting from Aug 19.
Spread the word, and thanks for participating.
Tuesday, September 29, 2009
Dave puts the 2009 Mariners as the best fielding team according to bUZR (since 2002), with a +85 runs in UZR.
There’s no stats v scouts. It’s stats AND scouts.
Tuesday, September 08, 2009
I just have two teams that are below my threshhold for success. I’ll keep pushing for them every few days.
Monday, August 31, 2009
I need your help for the Fans’ Scouting Report. Thanks.
Tuesday, June 02, 2009
I’ve been thinking of doing something along these lines for quite a while. However, I like Rally’s approach that focuses only on a very small group of stars. It can serve as a decent guage of whether I should roll out the thing for all baseball history.
If you want to help, please post in the comments section below (Ed note: on Rally’s site or here). I’ll give a week, hope to see some responses, then post my ratings for this group.
Monday, April 20, 2009
I love these little compilations:
As a Mariner (from sbnation.com):
As a Phillie:
These are the kinds of indicators to pay attention to. I don’t think you’ll find Beltran ever look like this will you? If for example a fielding system calls Ibanez “average”, it would seem hard to believe. I’d like to see the worst play by all the great fielders last year, and see if any of them looked this bad? Pick out Beltran, Chavez, et al, and let’s see those horrible plays.
I am positive you will find horrible at bats at the plate by great hitters (ARod, Pujols, etc). But, I don’t think you will find anything resembling the Ibanez Special on the field from a great fielder, would you?
Tuesday, March 31, 2009
Hey Tom, I’m a frequent reader of yours, and I had been wondering about a new possible stat derived from the vector things that UZR uses. Could we use batted balls to get a offensive stat that takes out great defensive plays. Like the example of the medium-speed, straight-at-the-shortstop ball being converted at 95% of the time (dont recall exact numbers), and then Derek Jeter makes the play and has a UZR of +0.05. Could we give the batter a scoring of 0.05 and then multiply by a run valued linear weight, like lets say 95% out and 5% single. and then he would get 5% of .47 (what i think is the run value of a single) then make an average? Wouldnt that take luck out of the stat?
What is the model? The model is a set of humans, who each have their own unique skills, each of whom is faced with a different set of circumstances at different frequencies, with a changing environment (weather, park, umpires, how they feel). Ideally, we’d put each human under all the possible combinations of parameters, and make him face each context one million times, all in the same day. That is the model.
What we have instead is 4 PA a day, of a set of known and unknown variables. That’s the performance data.
What we also have is how observers see those players, in-game or out. That’s the scouting data.
The idea is to create a model that is complex and comprehensive enough as to make both performance and scouting data obsolete. We’re not there, and we’re not going to be there. But, the plan is to work toward getting there as much as possible. PITCHf/x, HITf/x, and FIELDf/x (or similar systems) is the gold we’ve been looking for.
Imagine knowing exactly when Ryan Howard starts his swing when he faces Johan Santana, when he expects fastball, and gets curve, he expects it inside, and it goes outside. It will become not only important the angle at which it comes off the bat in that particular pitch, but at what angle does it normally come off under those conditions. We’re not going to necessarily care exactly where the ball ended up, we won’t necessarily care what happened when the ball and bat met, what we may end up caring about the most is the exact millisecond prior to impact: given all the effort exuded by Santana and Howard, in the amount, direction, and timing of that effort, what should have happened?
Friday, February 13, 2009
Maybe.
A more dramatic example would be Ryan Braun, who was universally panned for his fielding at 3B, by both the play-by-play metrics (-37 per 150G in UZR), and the Fans Scouting Report (overall a “40"), notably for his inaccurate arm (0 for arm accuracy, the lowest rating possible). However, one year in the OF (-3 UZR), and he looks completely different (52 for the Fans, with 46 for arm accuracy). Indeed, his “transformation” looks very little when looking at the Fans than when looking at UZR.
Braun could be a changed man. Or, his game could be better suited to the OF than the IF, like Soriano or Upton. Cuddyer had a similar change in evaluation based on whether he was in the IF or OF. Indeed, I talked about him a few months ago. When he was in the IF, his profile looked like that of a RF. And in the OF, his profile looks like that of a 3B.
The bias in the Fans is probably shared by the play-by-play metrics. While the average 3B moving to the corner OF would gain a few runs in UZR, this is not the case for everyone. Some guys gain a little, some lose a little, and others like Braun gain an enomous amount. Trying to measure things as seven traits is obviously not enough, which is why you have to take as much care in IF/OF translations using the Fans, as you would from using UZR.
Wednesday, November 26, 2008
Here you go. Balloting is still opened.
Tuesday, October 28, 2008
We tracked a good portion of the balls in play yesterday, using nothing more than our eyes and baseball sense. Below you will find the complete log of our observations. Note that this was our first try, and obviously, we’d need some guidelines. For example, if you have a play that will be made 40% of the time by 20% of the fielders, and 20% of the time by 30% of the fielders, 10% of the time by 40% of the fielders, and 0% of the time by 10% of the fielders, it’s not really apparent what the average is (18%).
Anyway, for posterity’s sake, and future research purposes:
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Friday, October 17, 2008
It’s not formatted, but you get all the data. Explanations of a few of the columns:
playerID: that’s the STATS player ID
GP: innings divided by 9, for that team, as of Aug 20 (regardless of position)
PosText: primary position, as of Aug 20
Pos_Specific: the 7 traits, weighted for his primary position
Pos_Neutral: the 7 traits, weighted for each of the 8 positions, then averaged
avgN: number of ballots (which is really number of data points divided by 7)
Agree: agreement level (average is .7)
Regressed: Pos_Neutral, regressed (done by adding 2 ballots of rating of 50)
The winner this year is: CARLOS BELTRAN. Sorry, Ichiro. Ichiro ended up in 3rd place, between John McDonald and Endy Chavez. The rest of the top 10: Brandon Phillips, Scott Rolen, Adrien Beltre, Evan Longoria, Franklin Gutierrez (this is the find of the year) and Mark Ellis. Other young players in the top 30: Fukudome, Asdrubal Cabrera, Erick Aybar, Adam Jones (what did Seattle do?), Denard Span.
The worst fielders: Estrada, Marlon Anderson, Chris Duncan (yup, Larussa saying that he could be average is the overstatement of the year), Dmitri Young.
The best by position:
C: Yadier Molina, Mauer
1B: Pujols
2B: Ellis, Phillips
SS: McDonald
3B: Rolen, Beltre, Longoria
LF: Willie Harris, Crawford (*)
CF: Beltran, Ichiro (**)
RF: Endy, Gutierrez
(*) Weak-a$$ field of fielders in LF. I’d make the three OF as: Endy, Beltran, Ichiro.
(**) Though I think Ichiro will move to RF by the time I re-run.
Enjoy…
from Amazon
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