Drew Pomeranz and Beating BABIP
Drew Pomeranz is in the midst of a breakout season. He’s already surpassed his season high for innings and his ERA is a very low 2.47, while his FIP is a low — if not quite as low — 3.15. Those very good numbers netted the San Diego Padres a very good pitching prospect recently in the form of Anderson Espinoza.
Much of Pomeranz’s newfound success has been attributed to the addition of a cutter to his repertoire, which Jeff Sullivan detailed just before the trade last week. One notes, however, that the success is aided by a .240 BABIP and 80.8% left-on-base rate. Even if those numbers aren’t sustainable, the 3.15 FIP indicates Pomeranz’s success is real. But there’s reason to believe that Pomeranz isn’t as susceptible to regression as the average pitcher. Or there’s reason, at least, to believe that the Red Sox believe he isn’t.
Speaking with WEEI’s John Tomase, former major-league pitcher and current Red Sox assistant pitching coach Brian Bannister has indicated that Pomeranz’s cutter makes it more likely that he’ll sustain some of his batted-ball suppression in Boston.
[Bannister] explained that like knuckleballers, whose BABIP numbers tend to skew low, pitchers who feature cutters tend to outperform league average on balls in play. He knows this because he did it over his first two years in the big leagues, posting BABIPs between .239 and .249.
“I was an example of it,” Bannister said. “[Cutters] generate a different batted-ball profile. There’s just different weak contact in there. Some guys it’s popups. Sometimes you get gyro-spin and it’s almost like a knuckleball. I mean, knuckleballers beat BABIP. It’s not always a given that a full regression is going to occur. When I look at a guy, if there’s a cutter involved or a knuckleball involved, you just can’t say for sure. I know a lot of people look at those two numbers — left on base percentage and the BABIP — and say, ‘Oh, he’s going to get worse in the second half.’ It’s not always a given.”
While we know pitchers tend to gravitate towards league average when it comes to BABIP, some pitchers are better than others at limiting hits on balls in play. Pop ups, like Bannister mentioned, can be a good way to induce easy outs. Fly balls and ground balls have different expected batting averages. Given a large enough sample size, we might be able to deduce which pitchers have these type of skills. With a smaller sample, perhaps looking at pitch types would help us determine which pitchers are likely to produce low BABIPs and thus more likely to outperfrom their fielding-independent numbers.
