On Wednesday, the St. Paul Pioneer Press published a piece by Mike Berardino about how the Twins—well, more like one full-time employee of the Twins—are starting to explore sabermetrics. It's worth a read. The article won't leave you with the sense that the Twins are anywhere close to the cutting edge, relative to teams that aren't the Phillies, but at least they're not opposed to the idea of incorporating statistics into their decision making.
Toward the end of the article, Berardino quizzes Twins GM Terry Ryan on some stats he uses:
How about BABIP — batting average on balls in play?
"Sure," Ryan says, nodding.
An average BABIP is about .300, which means Worley's 2012 figure of .341 suggests he was pitching in bad luck as much as bad health (bone chips in his elbow).
"You can deduce that, but he's also a year-plus player," Ryan says, citing Worley's limited service time. "He hasn't been around hardly at all. Plus, he was hurt."
Yet wasn't Worley's BABIP skewed enough last year to make him a worthwhile risk?
"I don't know if it's skewed. It might be," Ryan says. "I'm just saying, if there's a pattern there … but he hasn't been in the big leagues very long. Most young pitchers are going to have a high batting average on balls in play. Most young pitchers — most."
Ryan is right to point out that Worley's elbow injury might have made him more hittable. But what about his contention that most young pitchers have high BABIPs? Here's pitcher BABIP broken down by age over the past 10 seasons, a period during which the league average was .293.
.png)
Ryan is right in the sense that if you were to pluck a typical teenage pitcher out of A ball and put him in the American League, he'd probably have a high BABIP. But among pitchers who have made the majors, there's really no trend toward higher BABIPs at an early age. If anything, it's more likely to be the opposite​—there's probably some survivor bias in the stats above, since pitchers whose BABIPs increased over time would have tended to drop out of the sample sooner. Worley might be healthier and luckier this season than he was in 2012, but if he's anything like most big-league pitchers, another year of experience won't improve his skill at preventing hits on balls in play.
Thanks to Ryan Lind for research assistance.
Thank you for reading
This is a free article. If you enjoyed it, consider subscribing to Baseball Prospectus. Subscriptions support ongoing public baseball research and analysis in an increasingly proprietary environment.
Subscribe now
What's wrong with my math?
One additional point about how the variance is important: The population may be large on the whole, but teams have to care much more about applying it back to an individual. If you were to choose between two pitchers based on expected differences (of five points of BABIP), wouldn't you expect a ton of overlap in observed BABIP? And I would venture that there'd still be a ton of overlap looking at population means for an entire staff of young vs. old. So that's why I don't see a meaningful trend here, along with Ben.
That said, it could be worth testing whether controlling for other factors make age a more significant predictor. (When is it not?)
If we're to be as kind as possible to Mr. Ryan, that is.
The effect of age was non-sig (p = .55) although the trend line was pointing down, by about a ten thousandth of a point each year of age.