Tuesday, March 02, 2010
Era adjustments
Era comparisons. Haven’t read it yet.
Glove-slap: Alan.
Buy The Book from Amazon
Era comparisons. Haven’t read it yet.
Glove-slap: Alan.
Well, they equate the “steroids era” to post 1993, which I know has been discussed around here to likely coincide with a change in the ball (as it’s unlikely that the whole league or everyone that used PEDs started at the same time)..
Even though I’m essentially an observer (i.e., they aren’t stepping on my toes), it seems to me that they used a slightly different method for doing what has been done by many others, but their only suggestion that others have done something similar is a reference to the BPro book from a few years ago right at the end…
I’m not smart enough on the other approaches to era adjustment to know how their approach (appears to be a weighted average of yearly performance relative to league) compares to others, so it would have been nice if they had looked at other approaches that are out there and compared/contrasted…
Agree that the bibliography in the paper is weak, and misses some preceding studies specifically asking “What do statistics tell us about steroids”? Nate Silver has an article with just this title in Baseball Between the Numbers, a book that the authors of this study cite but strangely attribute to James Click. He also wrote a chapter comparing Bonds to Ruth in that same book.
They seem to be doing each hitting statistic in a vacuum. Ruth gains 450 Home Runs, but he loses 100 RBIs for his career in the adjustment.
So those authors knew of other estimates but didn’t even cite them. For example, in his “Ruth vs. Bonds” intro chapter in Baseball Between the Numbers, Nate Silver estimated that if Bonds had begun his career in 1916 (when Ruth did) he’d have had 444 career home runs. And if Ruth had begun his career in 1984 (when Bonds did), he’d have hit 913 homeruns in his career.
This is a vastly different set of numbers from what the authors of this article came up with—yet they cited the book without citing Silver’s estimates. Not saying Nate’s right and they’re wrong, but the authors’ had an obligation to read the lit.
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An interesting but somewhat curious study. I can’t follow the math but I can follow the logic.
Despite the title, it says nothing about steroids per se, as opposed to era in general.
(I’ll leave aside the fact that they chose RBI as one indicator.)
I find it curious that they decided to scale the HR so that “The Babe” ended up with over 1200 HR. Maybe they could have anchored the baseline curve to the HR levels in the 20’s and 30’s and shrunk the more recent levels more than they did?