http://www.geocities.com/ajc730/ERAmodel.htm

And when JC takes his analysis one step further and makes his case for ceteris paribus, he really gets into trouble. Davenport shows that good minor lg pitchers (those who later make the majors) post better BABIP than bad minor lg pitchers. JC suggests we can’t accept that finding w/o controlling for the 3 DIPS variables: “When trying to determine if control over hits on balls in play is a distinct skill, we must control for the impact of the DIPS metrics that we know do influence this ability.” This is the classic mistake of confusing association with causality. We have no evidence at all that DIPS metrics “influence” the ability. In fact, by definition that cannot be the case (Ks, BBs and HRs cannot become balls in play). DIPS metrics are associated w/ low BABIP, they don’t CAUSE it. To the extent there is an association, we might just as well say that low-BABIP “causes” low K rates.

If Davenport had, say, attributed all of the ERA advantage enjoyed by MLB-bound minor leaguers to their lower BABIP, w/o accounting for their superiority on Ks, BB, and HRs, then JC’s point would apply. Clearly, all four components contribute to the superior ERAs. But Davenport would only need to control for DIPS variables if they had a causal impact on BABIP, which they do not.

The fact these variables are associated w/ BABIP (and somewhat w/ each other) tells us that there is some general (though weak) tendency for athletes who are good at one to be good at the others. It probably reflects some underlying skill that impacts them all — i.e. the ability to throw balls with a mix of velocity, location, and movement that prevents hitters from hitting the ball hard. To control for these factors in Davenport’s study is to say: Let’s see if good pitchers have lower BABIP than weak pitchers, but first let’s “control” for the fact that some of these pitchers are better than others.

Let’s move beyond predicing next year’s ERA and ask the bigger questions: What is pitching talent? What makes a pitcher successful? The evidence provided by Davenport and others shows that preventing hits on BIP is just as much a skill as the other three factors, and the variance in this skill is just as important as the other three in determining how many runs a pitcher allows. JC says that Davenport finds only “small” differences in BABIP among minor leaguers, but neglects to tell us that these differences are just as large as with Ks, HRs, or BBs in terms of the impact on runs allowed, which is what matters.

DIPS was right about the difficultly in predicting BABIP in any given year, but wrong about the role of preventing hits in pitchers’ success. JC’s argument here serves to further obscure rather than illuminate this point.

i am not clear on what you mean here – IF the batter strikes out, THEN the ball can not possibly be in play.

- i would guess ( sorry – i have NO freaking idea how to get a formula for something like that) that ML pitchers have lower BABIP for 2 reasons
1) better control of their pitches – so that batted balls get popped up more, or GO more
2) the fielding abilty of ML fielders (incredibly better) compared to minor leaguers

I ran a regression where the dependent variable was the difference between a pitcher’s AVG on BIP and the AVG on BIP for the rest of the team while the difference between SO, BB, and HR per BFP were the independent variables. The r-squared was only .05. I looked at the top 50 pitchers in BFP in the NL from 2004. I thought the r-squared might be
higher, thinking that if SO, BB and HR measure pitching quality. If you do better on that than the rest of your team, I thought you would do
better on BIP AVG. So that seems to support McCracken. Maybe I need to look at more years.