The Two Month BABIP Overachievers

Last week, I began my examination of in-season BABIP with a look at how the league was utilizing the defensive shift and individual players were being shifted versus last season. It was a precursor to identifying and discussing where hitters currently stand with regards to my new xBABIP equation, which was developed earlier in the year and accounts for defensive shifts. So let’s dive into the hitters who have overachieved the most, meaning their BABIP marks are significantly higher than their xBABIPs.

BABIP Overachievers
Name LD% True FB% True IFFB% Hard% Spd Pull GB While Shifted% % BIP Shifted BABIP xBABIP BABIP-xBABIP
Miguel Sano 24.7% 44.4% 2.0% 51.6% 4.0 5.2% 31.7% 0.464 0.353 0.111
Corey Dickerson 20.8% 35.3% 2.3% 34.7% 4.0 6.9% 50.0% 0.394 0.305 0.089
Zack Cozart 21.1% 34.5% 6.3% 30.3% 5.7 0.7% 5.4% 0.385 0.297 0.088
Jean Segura 18.7% 28.0% 2.0% 31.8% 3.9 0.4% 1.5% 0.395 0.312 0.083
Ryan Zimmerman 22.5% 33.2% 2.6% 39.7% 2.8 1.2% 5.9% 0.404 0.329 0.075
Bryce Harper 18.8% 36.8% 2.3% 35.1% 2.4 13.0% 61.5% 0.353 0.280 0.073
Starlin Castro 17.6% 30.1% 3.4% 33.0% 2.0 2.2% 13.5% 0.359 0.289 0.070
Giancarlo Stanton 18.0% 29.3% 8.7% 36.7% 1.1 13.1% 51.1% 0.326 0.259 0.067
Yasmani Grandal 16.0% 32.0% 3.2% 35.7% 1.0 11.4% 46.6% 0.336 0.270 0.066
Matt Kemp 25.2% 32.9% 0.7% 38.5% 1.5 5.0% 24.1% 0.398 0.333 0.065
Carlos Beltran 15.5% 34.5% 4.9% 28.9% 1.8 19.3% 64.2% 0.296 0.231 0.065
Jose Altuve 16.9% 27.7% 2.8% 27.9% 6.7 2.4% 10.8% 0.363 0.302 0.061
Jedd Gyorko 20.5% 38.5% 0.8% 34.4% 5.2 3.1% 9.6% 0.377 0.317 0.060
Nomar Mazara 18.1% 31.6% 5.8% 27.1% 4.2 9.7% 60.8% 0.322 0.264 0.058
Aaron Judge 22.9% 36.4% 0.9% 48.3% 5.8 12.5% 49.5% 0.410 0.353 0.057
Aaron Hicks 18.5% 30.5% 5.6% 30.6% 4.4 3.3% 19.1% 0.343 0.287 0.056
Avisail Garcia 22.1% 23.4% 2.6% 30.5% 4.5 0.0% 5.4% 0.384 0.329 0.055
Charlie Blackmon 18.0% 37.1% 2.1% 38.0% 6.1 6.8% 23.7% 0.364 0.312 0.052
Mark Reynolds 19.6% 30.1% 2.8% 33.6% 2.0 9.9% 28.3% 0.341 0.289 0.052
Matt Wieters 22.5% 35.8% 5.0% 31.7% 2.5 12.6% 62.1% 0.328 0.276 0.052
J.T. Realmuto 16.2% 32.4% 2.8% 29.6% 4.6 0.0% 2.2% 0.341 0.290 0.051

For a reminder of what the Pull GB While Shifted% and % BIP Shifted columns mean, click on back to the original xBABIP article.

I decided to list far more players than I plan to discuss, just so you have the names. And DAMN this is quite the list of good hitters. I could easily see a knee-jerk reaction that assumes my equation is clearly wrong and missing something. My answer is that it is! It’s missing a lot…as have all the previous iterations of xBABIP equations. But it’s the best we got and the extreme guys on either end are still great bets to regress toward their xBABIP marks. The guys with a narrower gap, well, those are harder calls to make.

Part of the reason Miguel Sano was so overvalued heading into the 2016 season was because he was coming off a .396 BABIP during his 2015 debut, which was obviously unsustainable. And given his massive strikeout rate, any sort of significant BABIP decline would mean that his batting average had the potential to kill your fantasy team’s mark. Well, he’s back to his old tricks, after taking a season off to post a BABIP that was only 29 points above the league average. Of course, anyone with an inkling of BABIP knowledge could figure Sano’s BABIP, and batting average, is going to fall. But check the xBABIP…it’s still a hefty .353! That’s seventh highest among qualified batters. He does nearly everything right for a high BABIP, except for hitting tons of fly balls. But you see the downside here as if he regresses to the .353 BABIP that his RoS ZiPS projection calls for, he’s just a .249 hitter. Then is he really all that different than a Chris Davis?

Corey Dickerson is recalling his Coors Field days, but his underlying BABIP skills certainly do not support such an inflated mark. In fact, xBABIP suggests he should be posting just about an average mark. He’s done well to avoid hitting grounders into the shift, since he’s been shifted on about half his balls in play, but he hasn’t been particularly special anywhere else. Furthermore, his 7.5% Brls/BBE is just mediocre, which has fueled a 12.8% xHR/FB rate, well below his 20% actual mark. He’s an obvious sell high candidate.

Through May 12, Zack Cozart’s balls were dropping in for hits at a crazy rate (.407 BABIP), but his power had disappeared, making him look like an easy collapse candidate. But since, he’s socked five homers (plus two last night), and still BABIPing .347 during that time period. Suddenly he’s doing it all, not just bringing along an empty batting average. Since he’s also doubled his walk rate, as his Swing% has declined to a career low, he looks like a new hitter. The BABIP is going to drop, of course, and he’s at risk of being traded into a more pitcher friendly venue. But he probably won’t fetch a whole lot on the fantasy trade market, so you have to just hold and hope.

I guess it should be no surprise that there has been a heaping of good fortune involved in Ryan Zimmerman shockingly amazing start to the season. Because he’s been excellent years ago, it’s easy to convince yourself that this is real. I’d probably just hold him too.

Bryce Harper is getting shifted just as often as last year (which itself was a jump from 2015) and he’s grounding into the shift as frequently as well. And yet, he’s obliterating his xBABIP. You should be aware that Harper has not consistently outperformed his xBABIP. He has underperformed three times and outperformed twice. There are so many great things about Harper as a hitter, but given his ever present risk of injury, the fact that he’s attempted just two steals (getting caught on both of them) after attempting 31 last year, and has seemingly overachieved from both a BABIP and HR/FB rate standpoint, it would make sense to shop him around and see if you can net a king’s ransom. Everyone is going to value him like a first rounder, and I’m not sure he’s going to deliver that value over the rest of the season.

Giancarlo Stanton’s strikeout rate has remained quite stable since 2011, but has dipped to a career low this year so far. It’s allowed him to post a .291 batting average, which would be a career high. But what if that improved strikeout rate was just an early season mirage? And what happens when the rare right-hander that gets shifted half the time is suddenly seeing his balls in play get converted into outs at a rate xBABIP suggests? There’s real downside here and that’s not even mentioning that he has amassed more than 600 plate appearances just twice in his career.

Wowzers! Since becoming the regular catcher, Yasmani Grandal has never posted a BABIP above .277. Suddenly he’s perched above .300. But xBABIP knows better and isn’t fooled. This is the same Grandal he’s always been. Since last year’s HR/FB rate was a fluke, he’s going to return to being just a decent, rather than top tier, catcher once his BABIP and batting average falls back to where they should.

Carlos Beltran’s .296 BABIP looks completely normal, but his xBABIP is just .231! That’s fourth lowest in baseball and fueled by a low line drive rate and lots of grounders into the shift. He’s picked up his production since a slow start, but at 40 years old, this is looking like the end. Obviously, don’t even think about trading for him.

Jose Altuve’s .302 xBABIP is his lowest mark since 2012, the first season on my historical xBABIP spreadsheet. That’s because he has suddenly forgot how to hit line drives. I’m sure it’s just an early season blip, but if he falls into a bit of a slump where his batting average drops from Altuvian levels, this may be the reason why.

Two breakout Yankees appear toward the bottom of the list — Aaron Judge and Aaron Hicks. There must be something about starting your name with an Aa that has provided an offensive boost. Judge has been very Sano-like, though not as extreme from a BABIP standpoint, as they share the same xBABIP. Hicks has clearly optimized his patient approach, translating it into results, but he hits too many pop-ups and not enough line drives to carry a .300+ BABIP.

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.

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Jon L.

When several of the hardest-hitting players in the game (Sano, Harper, Stanton, Judge) are all greatly outperforming their xBABIPs, could it be time to alter the calculation?


It’s already been adjusted. Perhaps the R2 is not as high with a high hard hit%? But a quick perusal of the top 30 hard hit % also includes the following (just their BABIP listed)
Castellanos: 281
K. Davis: 250
E. Thames: 302
L. Morrison: 240
Gallo: 244
Carpenter: 237
Schebler: 223
Smoak: 281
and 6 more below .300.

Francis C.
Francis C.

Not all hard hit% are created equal. That’s why you need to also look at Andrew Perpetua’s statcast based xBABIP equation. That one however, does not take into account data like shifts, pulled ground balls and runner speed, so you should use both xBABIP equations to assess a player.

j Qbe 11
j Qbe 11

Would think the negative correlation of soft% to BABIP would be larger than the correlation of hard% to BABIP, as it would be skewed by balls leaving the yard. Or said another way, a low soft% would probably lead to a higher BABIP than a high hard%.