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Fangraphs: Hitting 'Em Where They Are


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Pretty substantial piece.

My calculations confirmed McCracken's contention that a pitcher?s BABIP in one season provides little information about what it will be the next year. However, I noticed that two other statistics did seem to offer helpful clues about hit prevention. The first was popup rate: the share of batted balls that are flies to the infield. Popups have virtually the same effect as strikeouts, since they are almost always caught and runners cannot advance on them. All other things equal, a pitcher who induces more popups should have a lower BABIP. And unlike some other batted ball types, such as line drives, popups do show a strong year-to-year correlation pitchers who get lots of them in one year are likely to induce an above-average total the next year as well. From 2010 to 2011, popups correlated just as well as walks, significantly better than homers and of course far better than BABIP. Even more encouragingly, a pitcher's popup rate in 2010 had a negative correlation with his BABIP in 2011. Although analysts have long known that inducing popups is a repeatable skill, I had never seen a publicly available equation that used it for the purpose of BABIP prediction.

The second promising variable was a statistic provided by Fangraphs.com called Z-Contact. It measures how often opposing batters make contact when they swing at pitches thrown within the strike zone. Since almost all strikes are hittable, and most of them are easy to square up, if a pitcher gets batters to miss a high proportion of his easier-to-hit pitches, then the balls that do get put into play against him will tend to come on harder-to-hit pitches. All other things equal, such batted balls should be more likely to be hit weakly and become outs. Z-Contact also has a very strong year-to-year correlation, and again seemed to have some predictive power regarding BABIP. At the time, I had never come across any reference to the relationship between Z-Contact and BABIP, although about seven months later Steve Staude of Fangraphs.com independently reported it.

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This is big news!

SSS, but it might help explain Chen's low BABIP -- he had the second best Z-Swing% in the majors and an average IFFB%. Gonzo had about the same rates in an unqualified sample, and his BABIP was lower. Tillman would've been top 10 in both if he qualified, and he had a (completely unsustainable anyway) .221 BABIP.

So yeah, extremely small sample that should be taken with a grain of salt, but it at least might explain a little bit why they beat their FIPs so generously in that sample. If any of them can keep up those rates for 2013 (they probably won't) we'll be very lucky.

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