Sophomore Slumps? (March 23, 2004)
Aaron Gleeman checks in with the aging patterns of Rookie of the Year winners.
--posted by TangoTiger at 12:07 PM EDT
Posted 12:58 p.m.,
March 23, 2004
(#1) -
J Cross
All points made in the Chavez signing thread apply here. Of course, ROY's don't do as well the next year.
Posted 1:03 p.m.,
March 23, 2004
(#2) -
mathteamcoach
No mention of regression to the mean?
Posted 1:11 p.m.,
March 23, 2004
(#3) -
Rally Monkey
No mention of regression to the mean?
He didn't mention it by name, but I think he dealt with the concept.
Posted 1:12 p.m.,
March 23, 2004
(#4) -
tangotiger
I've been having an email discussion with Aaron, and I immediately told him about "regression towards the mean". I told him I'd post his thread, and that I would guarantee him that one of the regulars here would bring it up. Just to get the point home, I looked at the MVP award winners from 1955-2002, and their SLG in the award year was .565 and in the next year it dropped 50 points. That is, it regressed about one-third of the way towards the mean. And, that's pretty much what we expected.
Posted 1:21 p.m.,
March 23, 2004
(#5) -
Matt Rauseo
After reading that article I had two thoughts... regression to the mean, and check MVP award winners, because I bet this isn't a sophomore specific event.
Curses, once again beaten to the punch!
Posted 1:26 p.m.,
March 23, 2004
(#6) -
studes
(homepage)
Shoot, he showed it to me before publication last night, and it was the first thing I said!
Got to remember that Aaron is writing to a different type of audience than the folks who drop by here.
Posted 1:44 p.m.,
March 23, 2004
(#7) -
MGL
The article could have been written in 6 words. "Sophomore slump, regression to the mean"
I see nothing worthwhile in this article. For a large enough group of players (in order to smooth out the random fluctuations), any above average season is ALWAYS followed by a decline, and any below average season is always followed by an "improvement." Period! It doesn't matter whether you look at ROY players, MVP players, MVP runners up, best players on the team, silver sluggers, etc., etc., etc.! (The only caveat is that you have to balance regression with the age factor. For example, if your group of players were only slightly above average and they had an average age of less than 26, then you would expect about the same numbers in the subsequent year as the regression and the improvement with age would cancel each other out.)
RTM (regression to the mean) may be implied in the article (I agree that it is), but not speficially mentioning it is very misleading to all but the seriously math oriented and/or enlightened readers.
And how can any serious sabermetrician not know EXATLTY what to have expected, almost to the penny, in the second year! Tango, I, and many others could have told them almost exactly what the next year was going to foretell by simply using a one-year regression and then making an age asjustment.
If you really want to tell whether there is indeed a phenomenon whereby pitchers "figure out" good rookie hitters by the following year, it is very tricky. You would have to basically look at the "expected" sophormore year numbers (based on the aforementioned regression plus an age adjustment) and compare that to the actual sophomore numbers. Even then, there is so much "slop" that you are not likely to be able to come up with anything meaningful.
Hinske was an easy one BTW. In 2002, his rookie year, his Superlwts was +20 per 150. In 2000, his MLE Slwts (hitting only) was +2 and in 2001, it was -1. His "sophomore" Superlwts was +8, almost to the "tee" exactly what we would have projected him at!
I am surprised and concerned with the quality of the HT articles (I was kind with the last article linked here) so far...
Posted 2:02 p.m.,
March 23, 2004
(#8) -
Erin Gleeman
Simple explanation: I'm not a serious sabermetrician.
Posted 3:32 p.m.,
March 23, 2004
(#9) -
Ex-Ed
"For a large enough group of players (in order to smooth out the random fluctuations), any above average season is ALWAYS followed by a decline, and any below average season is always followed by an "improvement." Period! It doesn't matter whether you look at ROY players, MVP players, MVP runners up, best players on the team, silver sluggers, etc., etc., etc.!"
Regression to the mean is a group phenomenon, not an indivdual phenomenon, so one should not say that "any above average season is ALWAYS followed by a decline."
Rather, the right way to say it is that "for any group of players that experienced above average seasons, on average those players will tend to decline in the following season."
Posted 4:10 p.m.,
March 23, 2004
(#10) -
Uh
Sophomore slump says players put up worse #s in their second year and this article shows exactly that. WHY they put up worse numbers isn't what he was trying to show. The fact is that the sophomores slumped.
Posted 4:19 p.m.,
March 23, 2004
(#11) -
J Cross
Uh, Sophomore slump says that players put up worse #'s in their second year but this article just showed that ROY winners put up worse #'s in their second year. If you looked at ALL sophomores you'd get a very different result.
Posted 5:21 p.m.,
March 23, 2004
(#12) -
studes
(homepage)
Calm down, MGL. THT is not primarily about cutting-edge analysis, like you guys do here. It's not even about analysis, really. For instance, I won't be posting my heavier research articles on THT. I'll put those on baseballgraphs, still.
THT's articles will be about baseball, and the writing will be aimed at the common fan. I would expect you to be dissatisfied with a lot of the it.
This article was no different than the sort of thing Aaron has been posting on his blog all along.
Posted 5:30 p.m.,
March 23, 2004
(#13) -
MGL
Studes, I've always liked Aaron's work. There is a big difference between "soft" articles and misleading and innacurate ones. The "sophomore slump" article is closer to the latter category, especially in light of J. Cross' comments. A sophomore slump has nothing whatsoever (a little exaggeration) to do with second year ROY's, and everything to do with "the next year after an excellent year, rookie or not..."
Posted 6:06 p.m.,
March 23, 2004
(#14) -
studes
(homepage)
That's a good point, MGL. Actually, that's a good idea for a follow-up article: what happens to most players when they have a year similar to a typical ROY? I think we all know the answer, but it would be constructive to carry out the analysis.
Posted 7:54 p.m.,
March 23, 2004
(#15) -
FJM
How about changing the title of the article to this:
DEFYING REGRESSION TOWARDS THE MEAN:
1/3 OF ALL ROY'S ACTUALLY IMPROVE IN THEIR SOPHOMORE YEAR!!!!
Actually, it would be closer to 50% if you limited it to those who enjoyed an INJURY-FREE 2nd season. Now that's newsworthy.
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Posted 9:49 a.m.,
March 24, 2004
(#17) -
David Smyth
I know MGL mentioned this in passing (and I haven't read the article), but ROY are what, about 24 yrs old on avg? That is supposed to be a period of strong growth. So I guess regression is quite a bit stronger than growth, even in the stong growth period?
Posted 10:20 a.m.,
March 24, 2004
(#18) -
tangotiger
Regression is by far the most important thing. We're talking about 30 to 35% change! The age factor is up to 5%.
Posted 2:47 a.m.,
March 28, 2004
(#19) -
dsm
I'd like to see this broken down for hitters and pitchers separately. It seems to me that the pitchers are seriously affected by injuries, much more so than batters. And it was mentioned that hitters did not suffer from the "sophomore slumps" as much/often. Without more information, it's tough to compare the two groups. There may be pitcher/hitter effects beyond injuries, but I can't tell.
Posted 5:04 a.m.,
March 28, 2004
(#20) -
MGL
dsm, This "phenomenon" is nothing more than regression, and is not unique to rookies. As I (and others) said in an earlier post, you would see almost identical regressions in any year following an above average year for any large group of players.
The same thing by definition applies to pitchers, expcept that you will see more regression from one above average year to the next. Why pitchers regress more than hitters, we don't exactly know. Part of it is due to injury, but much of it is not (they regress a lot from bad injury-free seasons as well)...
Posted 9:39 a.m.,
March 29, 2004
(#21) -
Ex-Ed
Anyone see this non-answer in Davenport's chat? Pretty defensive.
***
Chris (North Carolina): Clay, every year EQA shifts around, making it impossible to determine its accuracy, predictive power, and overall value. When are you going to come up with a measurement that doesn't shift every year? And is BP abandoning EQA in favor of other, newer, better measurement tools?
Clay Davenport: I think you are confusing EQA with DTs. The formula for EQA hasn’t changed in five years at least, and the formula is published and readily available. The translation procedure, however, does change, as I test different procedures, discover old biases, and generally learn things I didn’t already know to try to incorporate it. In addition, some of the inputs to the program change from one year to the next. The park factor I used for San Francisco in 2003 is currently based on an average from 2001-2003; in next year’s book, the 2003 park factor will be an average of 2001-2004, and it won’t be until after 2005 that it will become a stable value. Likewise, the difficulty rating for leagues is reassessed each year, as I can now see how players who left that league did, not just players who came into that league.
Posted 10:06 a.m.,
March 29, 2004
(#22) -
tangotiger
I didn't think it was anything wrong with Clay's response.