Yesterday, I discussed some of the starting pitchers who have underperformed their xBABIP marks the most. Today, we’ll check in on the other side of the coin — those starters who are significantly outperforming their xBABIP marks. Whether it’s great defensive support, some mystical ability to consistently induce weak contact or at ’em balls or good old lady luck, xBABIP thinks these levels are unsustainable.
After missing about two and a half months of the season with a variety of maladies, it would appear that Mat Latos hasn’t lost a step since returning. But it’s been a ridiculous .213 BABIP and a suppressed 4.9% HR/FB ratio that has hidden the steep decline in his skills. It’s true that he has induced a sky high rate of pop-ups, but he has also allowed line drives at a higher than league average clip. Of course, both those batted ball types should be accounted for in the xBABIP formula. The red flags abound, from a career low SwStk% below 8% (the first time it’s dipped below even 10%), to fastball velocity being down two miles per hour to a strikeout rate in free fall. And more worrisome is that his slider usage has dipped considerably, probably owing to not wanting to put as much stress on his elbow. SELL SELL SELL!
Danny Duffy has parlayed a huge fly ball rate and strong pop-up rate into an extremely low .229 BABIP. Of course, that’s precisely the type of batted ball profile required to prevent hits on balls in play, but there still remains a floor that skill alone could account for. Like Latos, he’s also benefiting from a low HR/FB rate and has seen his SwStk% tumble. With just average control at best, he needs those whiffs and punchouts to return in order to fight off the inevitable appearance of the regression monster.
There has been a lot written about Chris Young here over the last couple of months, and for good reason. He hadn’t even pitched in the Majors in 2013 or endured a full season in a rotation since 2007. Yet here he is with a 3.27 ERA, despite terrible traditional skills and a 5.18 SIERA. Young’s extreme fly ball ways that also induces lots of pop-ups is a recipe for a low BABIP, and his career mark does stand at .251 (which of course includes this season’s .229 mark). He’s even posted a full season mark almost identical to this year back in 2006, when he enjoyed a .226 mark over 179.1 innings. So this isn’t unprecedented for him. But he’s still sporting a LOB% above 80%, which is near league leading territory, and not a level he’s really shown capable of in the past. I would still remain far too nervous to roster him given his poor strikeout rate and risk of implosion.
Dillon Gee looks to be a prime example of an average pitcher. He offsets the lowish strikeout rate with better than average control and he owns a league averageish batted ball profile. But, that league averageish batted ball profile has somehow yielded a .230 BABIP. It’s hard to believe given his low IFFB%, but perhaps that’s canceled out by his suppressed line drive rate. Still, it’s nowhere near an explanation for that BABIP, so his final month and a half could look quite a bit worse than his first four and a half months.
Johnny Cueto has posted either league average BABIPs or sub-.250 BABIPs throughout his career, which is quite odd. He became a ground ball pitcher in 2011, then his strikeout rate began inching up before sky rocketing this season. And during all this, his control remained stellar. By simply looking at his batted ball distribution, you would expect an above league average BABIP, given his high ground ball rate and low IFFB%. Perhaps his delivery is really that deceptive, but I can’t imagine that’s the only explanation. A .225 BABIP is freakishly low and it’s hard to believe he can sustain anything close to that. To top that, my updated xK% equation suggests suggest he’s due for some strikeout rate regression, given his strike type percentages. Add the ever present injury risk, and he’s a sell candidate and one nearly guaranteed to be overvalued next season.
Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.