The beginning of the Major League Baseball season is a good time to check in with Clear Thinkers favorite, Bill James, the father of sabermetric analysis of baseball. Steve Dubner over at the Freakonomics blog recently provided James with this question-and-answer forum and, as usual, James’ observations on baseball are insightful and entertaining. For example:
Q: Using various statistics over a player’s lifetime, and comparing them to “league norms,” is it possible to determine which players may have used steroids?
A: Absolutely not, no. The problem is that many different causes can have the same effects. If a player used steroids, this could cause his home run total to explode at an advanced age — but so could weight training, Lasix surgery, better bats, playing in a different park, a great hitting coach, or a good divorce. It is almost always impossible to infer specific causes from general effects.
Q: Can you tell us about a time when you thought numbers were misleading and why?
A: I would say generally that baseball statistics are always trying to mislead you, and that it is a constant battle not to be misled by them. If you want something specific — pitchers’ won-lost records. And if you want a specific pitcher, Storm Davis, 1989.
For the record, Davis posted a 19-7 record with the Oakland A’s in 1989 while posting a pedestrian 4.36 ERA and giving up 8 more runs that season than a National League-average pitcher would have given up pitching in the same number of innings. Needless to say, a National League-average pitcher in 1989 did not have a 19-7 record. Here’s another of James’ interesting observations:
Q: Generally, who should have a larger role in evaluating college and minor league players: scouts or stat guys?
A: Ninety-five percent scouts, five percent stats. The thing is that — with the exception of a very few players like Ryan Braun — college players are so far away from the major leagues that even the best of them will have to improve tremendously in order to survive as major league players — thus, the knowledge of who will improve is vastly more important than the knowledge of who is good. Stats can tell you who is good, but they’re almost 100 percent useless when it comes to who will improve.
Read the entire post.