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Sampling
Wednesday, October 29, 2008
Derek Carty gives us his take.
The quickest explanation of sabermetrics was given by Theo Epstein early in his GM career, when he said that he sees statistics and scouting as two lenses of the glasses. Unsaid by him is that the glasses is sabermetrics. So, anyone who thinks of the choice as beer or nuts, ignores the reality that the choice is beer and nuts.
Also, the more performance statistics you have, the less value you can place in scouting, because at some point under certain conditions, the reality of what actually transpired is more important in determining what will happen than what the scout thinks that player will be doing. And vice-versa of course, if the performance numbers was based on small samples.
Monday, May 05, 2008
Joe Sheehan points out that the “slash” data is the same, but run scoring is down:
AL AVG OBP SLG ISO R/G
April 2008 .260 .334 .398 .138 9.04
April 2007 .255 .327 .404 .149 9.36
NL AVG OBP SLG ISO R/G
April 2008 .256 .331 .404 .148 9.11
April 2007 .258 .332 .400 .142 9.31
Is that random variation, or is something else going on? Taking a quick crack at it:
We have in Mar/Apr 2007 in MLB: .256 .330 .402
And this year: .258 .332 .401
That’s remarkably close. The runs scored per 27 outs in each year: 3785 runs in 7490.1 innings, 4.55 runs per 27 in 2008. 3360 in 6670.1, or 4.53 runs per 27 in 2007.
Huh? What’s Joe talking about?
Here’s the data I’m using:
http://www.baseball-reference.com/pi/psplit.cgi?team=TOT&lg=ML&year=2007#dates-month
http://www.baseball-reference.com/pi/psplit.cgi?team=TOT&lg=ML&year=2008#dates-month
Either Joe misstated his facts, or Sean has a bug, or I’m reading something wrong.
I’ll let the Wisdom of the Crowd make the decision.
Monday, February 11, 2008
By , 09:12 PM
This is from Chris Jaffe, no less, a baseball analyst. While I have read plenty of his stuff and I recognize the name, I admittedly know little about him (and get him mixed up with the other Jaffe). This is also an example of how when you start writing for a (somewhat) mainstream web site or publication, you invariably develop a case of “I can write crap too, just like the rest of the guys (mainstream writers)...” (See my past comments about Keith Law.)
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Sunday, December 02, 2007
By , 01:39 AM
I did not really know how to title this entry, but…
Here is an article that, in my opinion, is a good example of how baseball “insiders” are woefully inadequate in understanding the confluence of baseball and statistics, such that it can and will lead to bad deicision-making.
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Thursday, October 11, 2007
By , 12:44 AM
Actually, I’ll generalize to all teams that have lost any game or series throughout the history of baseball (and most other sports). Their opponents probably outhit and/or outpitched them, likely outscored them, and definitely won more games than they did. Oh, and several players on the losing teams had a bad game/series - worse then their regular season stats. And the winning teams probably played with more heart, guts, guile, and confidence, and some of them were even teams of destiny. Did I leave anything out?
Friday, September 21, 2007
If we look at his 2002-2004 data, we see the following totals: 202 GB, 187 FB, 108 LD. This year, he’s 52/54/32, which is almost exactly in line with his 2002-2004 performance. Nate Silver points out the enormous flip in GB to FB ratio of Eric Gagne, between Texas and Boston this year. Excluding bunts, in Boston, he’s at: 14/20/13. If you divide his 2002-2004 data by 10, you’d get this expectation: 20/18/11, which means he’s given up a couple more FB, a couple more liners, and a few less ground balls. When your sample size is 50, that really means nothing. Of his 14 groundballs, batters are 6 for 14. But again, that’s 14 PA. Of the 20 FB, batters are 6 for 20 (all extra base hits). Of the 13 liners, batters are 11 for 13. He’s given up 2 more groundball hits than he should have, a few more extra base hits than he should have and one more line drive hit than he should have. In high-leverage situations though (LI of 1.8 or higher), opposing batters reached base 13 of 21 times, which is horrible. But still, it’s only 21 PA.
All this to say that with some 70 PA, Gagne needs to be evaluated on his mechanics and pitch effectiveness, and not on the resulting batter performance. Rereading Nate’s piece, he says exactly this, and he’s right:
There may be scouting evidence that Eric Gagne is not the same pitcher in September that he was in June. But there is little or no statistical evidence based on an informed reading of his numbers.
Tuesday, August 14, 2007
By , 01:33 AM
Here is the Study
There is a discussion of said article, where I made some comments, on BTF.
Monday, July 02, 2007
By , 07:12 PM
This time from a sabermetric web site. Where are their editors?
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Wednesday, January 24, 2007
Abbott Katz, in the November 2006 issue of By The Numbers shows us that players who had exactly 17 at bats hit .171 from 1959-2005.
Does it mean anything? Obviously, if you only have 17 seasonal at bats, it means alot. It means you are a September callup, it means that you are on your last legs, it means you got hurt, it means that you did so badly that the manager doesn’t want to look at you. It could mean a whole lot of things. It might even mean that you suck.
In order to figure out more about what it means, you need to look at the data outside from which you selected from. And that means, look at the data in the season before and after that selected season. Which I will right now:
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Wednesday, August 23, 2006
Cy Morong takes a look at establishing the replacement level. He says:
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