Toronto Blue Jays v Tampa Bay Rays

We’ve done pop-ups here before, but let’s really do them this time, right? I mean, let’s get it right this time at least. Because last time I was writing about IFFB%, which I thought was infield fly ball percentage. Turns out that’s infield flies divided by fly balls. That’s a little strange.

Steve Staude on FanGraphs is a proponent of infield fly balls divided by balls in play. Freed from the shackles of fly balls, we can get a sense of the pop up as a sustainable skill — IFFB% only has a .37 year-to-year correlation, but pop up percentage (PU%) is better, around .63. That’s better than the year-to-year correlation on home runs (.41)! We have a stat — FIP — that treats home runs as a skill that’s wholely under the control of the pitcher, and yet infield pop-ups are better correlated season to season.

Staude’s excellent initial work on the subject is not incredibly fantasy-relevant, but it does go some distance towards explaining park effects better. Look at the parks that showed a PU% that was more than .5% higher than IFFB% — Anaheim, Wrigley, Citi, Tampa, Detroit — and you get a list of the ‘secret’ pitcher’s parks. Of course, Milwaukee, Detroit and Yankee Stadium are on that list, too.

But let’s take this and jump into the pitcher pool, no? Here are the leaders in PU% over the last two seasons (minimum 250 IP).

Name IP W K/9 BB/9 HR/9 BABIP ERA FIP IFFB% PU%
Bruce Chen 346.2 23 6.15 2.52 1.32 0.292 4.49 4.58 15.40% 6.95%
Phil Hughes 263 21 7.19 2.36 1.51 0.291 4.69 4.55 14.70% 6.84%
Colby Lewis 305.1 20 7.72 2.06 1.5 0.27 4.07 4.31 13.50% 6.47%
Jered Weaver 424.1 38 7.21 2.14 0.85 0.246 2.59 3.44 13.00% 5.98%
Shaun Marcum 324.2 20 7.4 2.72 1.05 0.268 3.6 3.87 13.60% 5.75%
Jake Peavy 326.2 17 7.77 2.01 1.02 0.289 3.94 3.61 13.50% 5.72%
Jeremy Hellickson 366 23 5.93 3.22 1.13 0.242 3.02 4.52 13.70% 5.64%
Chris Capuano 383.1 23 7.75 2.49 1.22 0.296 4.11 3.99 13.10% 5.24%
Dan Haren 414 27 7.24 1.54 1.04 0.285 3.67 3.53 13.30% 5.15%
Jason Vargas 418.1 24 5.85 2.45 1.23 0.27 4.04 4.4 12.10% 5.11%
Justin Verlander 489.1 41 8.99 2.15 0.79 0.255 2.52 2.97 12.90% 5.02%
Ian Kennedy 430.1 36 8.05 2.3 0.98 0.288 3.43 3.62 11.70% 4.77%
Josh Beckett 363.1 20 7.6 2.58 1.04 0.27 3.72 3.85 11.90% 4.69%
Clayton Kershaw 461 35 9.31 2.28 0.61 0.265 2.4 2.68 12.80% 4.65%
Bartolo Colon 305.1 18 6.28 1.77 1.09 0.295 3.71 3.87 12.80% 4.65%
Aaron Harang 350.1 24 6.55 3.67 0.87 0.289 3.62 4.15 11.00% 4.51%
Daniel Hudson 267.1 19 6.94 2.09 0.88 0.308 4.14 3.55 11.60% 4.47%
Jon Lester 397 24 7.89 3.24 1.02 0.3 4.17 3.98 14.40% 4.46%
Travis Wood 257 11 6.58 3.22 1.23 0.28 4.59 4.57 10.00% 4.42%
J.A. Happ 294 16 8.3 4.1 1.22 0.306 5.08 4.39 10.40% 4.35%

If that list doesn’t make you smile, I can do nothing for you, son. Yes, Justin Verlander and  Clayton Kershaw are on it, sure. But so many of the other guys on this list are pitchers that have beaten their FIP. This group as a whole averages a 3.78 ERA and a 3.92 FIP, for example. And it’s just littered with interesting pitchers that have ‘made the most’ of their talents. And J.A. Happ.

But Jeremy Hellickson, of course he’s on this list. He’s personally befuddled many an analyst with his FIP-busting ways. You could say the same of Jered Weaver, but Hellickson will go a lot cheaper in your next fantasy draft. And Ian Kennedy! They certainly seem a little tastier now then they did five minutes ago, don’t they?

If all of this makes you nervous — .63 doesn’t seem super high in terms of year to year correlations, does it — then check this list of pitching metrics correlated year to year that Bill Petti wrote while at Beyond the Box Score. PU% would come up .01 short of walk rate. And you generally think guys that have bad control just have bad control, right?

So maybe it is a skill — guys can elicit the pop up or they can’t.