Hitter xwOBA Overperformers — Aug 22, 2022
Last week, I reviewed the five fantasy relevant hitters most underperforming their xwOBA marks. Now let’s flip over to the overperformers.
Name | BABIP | HR/FB | AVG | xBA | SLG | xSLG | wOBA | xwOBA | Diff |
---|---|---|---|---|---|---|---|---|---|
Paul Goldschmidt | 0.384 | 22.3% | 0.341 | 0.266 | 0.640 | 0.506 | 0.450 | 0.375 | 0.075 |
Jeff McNeil | 0.354 | 6.0% | 0.318 | 0.267 | 0.458 | 0.373 | 0.363 | 0.312 | 0.051 |
Nolan Arenado | 0.295 | 13.8% | 0.298 | 0.266 | 0.558 | 0.450 | 0.390 | 0.340 | 0.050 |
Jose Iglesias | 0.346 | 3.4% | 0.312 | 0.269 | 0.411 | 0.329 | 0.333 | 0.286 | 0.047 |
Jose Miranda | 0.321 | 14.6% | 0.285 | 0.248 | 0.477 | 0.410 | 0.352 | 0.309 | 0.043 |
Jose Ramirez | 0.271 | 11.2% | 0.281 | 0.266 | 0.537 | 0.424 | 0.374 | 0.333 | 0.041 |
Manny Machado | 0.343 | 16.1% | 0.302 | 0.270 | 0.533 | 0.454 | 0.385 | 0.345 | 0.040 |
Paul Goldschmidt continues to massively outperform his xwOBA, sitting as the far and away leader of outperformance. It’s not something you would expect from a 34-year-old playing half his games in a pitcher friendly ballpark. Goldschmidt has not been a consistent xwOBA outperformer, so it’s unlikely he’s doing something not captured by the equation, unless he’s suddenly doing something this year he’s never done before that is being ignored. I doubt it. Much of the outperformance is due to his crazy .384 BABIP, which would be a career high for him.
However, Goldschmidt isn’t a stranger to high BABIP marks, as his career mark sits at a hefty .349. It’s bizarre that this is the season his BABIP sits at a career best though, as his LD% (the batted ball type with the highest BABIP) is sitting at a career worst, while his FB% is sitting at a career high (the batted ball type with the lowest BABIP, excluding pop-ups). That combination doesn’t normally result in a career best BABIP. His HR/FB rate has jumped as well, despite posting an identical maxEV and a lower Barrel% versus last year, when his HR/FB rate sat in the mid-teens.
I’m not sure it would be worth trying to trade him, especially with just a month and a half of games left, a sample size in which anything could happen really, especially with BABIP and batting average. But don’t be surprised if he disappoints the rest of the way, particularly compared to his current production.
It’s pretty shocking to find Jeff McNeil’s name ranked second here considering he owns just a 6% HR/FB rate and .141 ISO. So he’s clearly not hitting for more power than he should be, which means that this one is simple — more of his balls in play are falling for hits than Statcast calculates should be. McNeil has outperformed his xwOBA handily in three of his first four seasons, so this would mark the fourth of five seasons. That could be a trend and suggest he’s doing something not captured by the metric, like horizontal direction (spraying the ball the opposite way) and avoiding the shift. The thing is, without much power and little speed, he’s reliant on a high BABIP to deliver any sort of fantasy value, making him a risky bet the rest of the way. If that BABIP doesn’t stay inflated, his fantasy value craters.
Who said Nolan Arenado needed Coors Field to outperform his xwOBA?! He’s hit like vintage Arenado, you would never know he was playing in a pitcher’s park now. What’s really surprising is his rates don’t even stand out. His .295 BABIP is right in line with his career mark, though that’s Coors-inflated, while his HR/FB rate is barely above league average and actually below his career mark (which again, is Coors-inflated). So from just looking at the stats driving his wOBA, nothing seems out of the ordinary.
When you dig a bit deeper, you understand why Statcast might be calculating a lower xBA, and therefore BABIP. He has remained an extreme fly ball hitter, which again, goes for a hit less frequently than grounders and liners, while his IFFB% has exploded to a new career high. When you combine a high rate of pop-ups with a high rate of fly balls, and a low strikeout rate, meaning lots of balls in play, you end up with the most pop-ups in baseball. Arenado has already hit 34 pop-ups, tied for a career high already and one more than last year, in significantly less at-bats. His 34 is ahead of the second most pop-up happy hitter sitting at 29. So perhaps after knowing that, the .295 BABIP might actually look quite fortunate.
It’s interesting to find two Cardinals hitters in the top three, so perhaps the park is playing more hitter friendly this year than in the past.
Speaking of Coors Field, Jose Iglesias is clearly benefiting from his new home digs. Or so you would think. In fact, he has actually posted just a .299 wOBA at home, versus a .369 wOBA in away parks! I’m not sure I’ve ever come across a Rockies hitter with such stark home/road splits, where the better split was away. Iglesias has actually consistently beaten his xwOBA, but only by a marginal degree, so this would mark his biggest outperformance. Since he has hit for little power, the outperformance is due entirely to the .346 BABIP, lifting his batting average well above his xBA. Like McNeil above, he has even less to offer aside from the batting average, so he makes for a risky bet the rest of the way. When/if that BABIP declines, there’s nothing else he’ll be contributing in.
After a slow start, posting just a .232 wOBA in May, Jose Miranda has been superb ever since, posting a wOBA no lower than .369 in any month. However, with a below average LD%, a higher than average FB%, and an IFFB% even higher than Arenado, his .321 BABIP screams fluke. His power doesn’t seem questionable though, so it’s a matter of how many balls in play will find gloves over the rest of the season, which could push his batting average down from contributing positive value to being neutral or even negative. It’s something to consider in keeper leagues if you own him cheap, as he could potentially bring back a lot if you’re trying to win this year.
With a below average BABIP as usual, and his lowest HR/FB rate since 2016, it’s hard to believe that Jose Ramirez is one of the biggest xwOBA overperformers. Amazingly, Statcast isn’t buying his .537 SLG, which is his second lowest mark in the six years he has been the powerful version of himself. Owners haven’t totally noticed his decline in home run power since his FB% has notched a new high just over 50%, while his strikeout rate has dropped to a career best. More balls in play + more of those balls in play in the air = more home runs, offsetting some of the drop in HR/FB rate.
It’s difficult to envision trying to trade him, regardless of what Statcast thinks, given his contribution in steals as well. I’m an owner and will simply continue holding him the rest of the season.
Manny Machado is still running with a career best BABIP, despite a career worst IFFB% and a stable FB% just over 40%. It’s seemingly a worse batted ball distribution than he normally posts, which has generally led to BABIP marks hovering around the league average. In fact, he had only posted a BABIP over .300 once since 2017. It’s why Statcast is skeptical of his batting average.
Statcast also doesn’t believe his power, possibly explained by the loss of maxEV and a drop in Barrel%. Since his strikeout rate has risen to a career worst, he has to perform better on the balls he does put into play, which doesn’t seem to be the case. The results have been there, but it looks more like good fortune. The chance to trade Machado at a significant premium has already passed, so it’s likely far less fruitful to try doing so now. Yup, I missed my opportunity as well.
Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.
Wilmer Flores has emerged as a consisted xwOBA defier year after year. He’s been about a 120 bat since leaving the Mets despite a frankly unimpressive Savant page. The sample size is too big for this to just be a fluke at this point.
Is there any secret sauce as to why?
Pull%, especially in the air. As defined by StatCast, 31.7% of Flores’s batted balls have been fly balls since the beginning of 2020, compared to a league average of 25.4%. Of those fly balls, Flores has hit 37.5% to the pull side, compared to 26.3% league-wide. Over that time, the expected wOBA for all pulled fly balls is .657, while the actual wOBA is .900, not a small difference.
So 11.9% of Flores’s batted balls fall into a subset that outperforms their expected wOBA by 243 points. The league average is 6.7% pulled fly balls. To me, this is StatCast’s most glaring issue, not omitting shifting or speed from xwOBA. Every stadium has a wOBA-xwOBA between .138 (Kaufmann) and .412 (Minute Maid, hello Crawford boxes) for pulled fly balls over StatCast’s lifetime. Conversely, every stadium has a wOBA-xwOBA number between -.021 (Coors) and -.294 (Comerica) for straightaway fly balls. At least a nominal attempt at accounting for horizontal launch angle would be a welcome addition to StatCast.
This is an awesome answer and makes total sense! Thank you so much!!
It’s wild — I didn’t realize xwOBA had this kind of blind spot. It reminds me a bit of how early DiPS didn’t account for soft contact or groundballers, etc.