I have long admired Bill James and I enjoy reading his work. I remember when Doug Drinen let me borrow his collection of Abstracts, and the jealousy I felt about growing up without ever knowing of James’s work. In my mind, Bill James thinks like an economist, and I didn’t realize my way of thinking naturally was commonplace in economics until I got to college. Had I found Bill James as a teenager, my life probably would have been a little bit different.
I happened across a post by King Kaufman the other day, which led me to A Bill James Primer, extracted from James’s 1988 Abstract. But, as I read the primer, I was surprised to see how often I disagree with many of the tenets. Though I’ve been writing about these issues for years, I just hadn’t noticed. So, I thought I’d wander through the primer in a blog post. I’ll point out where I agree, disagree, and have qualified agreement and why.
1. Minor league batting statistics will predict major league batting performance with essentially the same reliability as previous major league statistics.
I think that minor-league statistics can predict performance; though, I wouldn’t go so far as to say that they predict with the same reliability as major-league statistics. In Chapter 8 of Hot Stove Economics, I examine how minor-league baseball statistics can be used to predict major-league performance. I find that certain minor-league statistics at the High-A level and above are correlated with major-league performance. However, performances at Low-A and below do not have much ability to predict major-league performance. As a general rule, the closer you get to the big leagues, the more reliable predictor minor-league statistics become. The problem is that because the quality of minor-league players is so widely dispersed, good minor-league performances can be aided by taking advantage of qualities of the competition that won’t survive in the majors. However, it’s rare for someone who performs poorly in the minors and to excel in the majors.
2. Talent in baseball is not normally distributed. It is a pyramid. For every player who is 10 percent above the average player, there are probably twenty players who are 10 pecent below average.
I disagree. Below are two graphs that showing the distribution of hitters and pitchers in baseball, with a minimum of 100 plate appearances or batters faced in 2009. The solid line is league average and the dashed lines bound the standard deviation.
For this reason, I don’t believe replacement players are cheap and abundant, and it’s one of the reasons I dislike replacement-level metrics.
3. What a player hits in one ballpark may be radically different from what he would hit in another.
I agree that ballpark effects are real. You can’t judge players without adjusting for park effects. This seems obvious now, but I don’t believe it always was. I think that James was one of the first people to study and measure park effects.
4. Ballplayers, as a group, reach their peak value much earlier and decline much more rapidly than people believe.
Depends on which “people” you are. I think James’s claim that player peak at age 27 is wrong. I believe the methodology of his initial study of the issue is flawed. My own estimates indicate that players peak around 29. Though I disagree with his initial findings, the chapter on aging in his 1982 Abstract was groundbreaking in how he thought about aging functions.
5. Players taken in the June draft coming out of college (or with at least two years of college) perform dramatically better than players drafted out of high school.
It depends on what you mean by dramatic, and how this ought to inform draft strategy. Jim Callis of Baseball America conducted an analysis of how well high school and college players succeeded in the majors. College players did a little bit better—I wouldn’t call the difference “dramatic”—but that’s not surprising and I don’t think the identified difference should affect teams’ drafting strategy.
College prospects are a survivors of a previous high school draft pool. After three or four years of observation, we have a better idea of whom the good players are. It should be no more surprising that college players succeed at a slightly higher rate than high school players than that minor-league players three years from high school are more successful than recently-drafted players. We have better information about them, and time has culled out some non-prospects. But, if a team tried to improve its return to the draft by drafting more college players, it’s not necessarily going to benefit from the previously measured higher success rate of college players. The college draft pool is more certain: not only do we know the good players, we know the bad ones too. Part of the reason the returns to drafting college players are better is that teams stop drafting college players once the good ones are gone.
Let’s say you had to buy a car today. You have time to test-drive three, and you like one and hate the other two. But by the time you go to buy the good car you test-drove it’s gone. Should you buy one of the cars you know you don’t like or go for one you have a chance of liking from a pool of cars you didn’t test drive that were on your list of prospective cars from Consumer Reports? The latter group of cars has more risk, but at least has an upside that the former group doesn’t have.
So, agree with James here on the fact, but I don’t think the higher success rate of college draftees means that teams can improve their drafts by focusing on more college players. However, I’m not sure if James believes anything more than the fact.
6. The chance of getting a good player with a high draft pick is substantial enough that it is clearly a disastrous strategy to give up a first round draft choice to sign a mediocre free agent.
I’d probably agree with this, but I think the fact that the pick will likely yield a player who can be paid far less than he’s worth is more important than the likelihood that the drafted player is good. On talent alone, I expect a mediocre free agent has an expected talent value of close to that of a high draft pick.
7. A power pitcher has a dramatically higher expectation for future wins than does a finesse picther of the same age and ability.
I don’t know.
8. Single season won-lost records have almost no value as an indicator of a pitcher’s contribution to a team.
9. The largest variable determining how many runs a team will score is how many times they get their leadoff man on base.
Getting the first man on in the inning is important, but I’m not sure that it’s the largest variable. I’ll concede that I don’t know.
10. A great deal of what is perceived as being pitching is in fact defense.
I find baseball is 13% defense, and so does James. Agreement.
11. True shortage of talent almost never occurs at the left end of the defensive spectrum.
Possibly, but the problem is that for most of the game, players have to play both sides of the ball. And because fielding is such a relatively small part of baseball, purely defensive guys don’t have a lot of value. There is a shortage of guys who are decent hitters and play defense well, especially at defensive positions.
12. Rightward shifts along the defensive spectrum almost never work.
13. Our idea of what makes a team good on artificial turf is not supported by any research.
I have no clue, so he’s probably right.
14. When a team improves sharply one season they will almost always decline in the next.
Agree, that’s simple mean reversion.
15. The platoon differential is real and virtually universal.
Even as I find differences here, my affection and respect for James as a thinker has never diminished. I agree with Tyler Cowen that James is one of the greatest living social scientists. What I like about James is the way he approaches problems and finds answers. I may not agree with the exact method used or the answer—although; in most cases I do—but I like the frame of mind with which James tackles curiosities. The sabermetric approach that James espouses is right. That his findings sometimes don’t fit with mine, doesn’t bother me.