2019 HR/FB Rate Decliners

Yesterday, I compared batter HR/FB rates to my xHR/FB rates to identify nine hitters who posted xHR/FB rates significantly higher than their actual marks, suggesting upside this season if they are able to maintain those underlying skills. Today, I’ll check in on those hitters on the opposite end of the spectrum, with a list of six batters who overperformed their xHR/FB rates most. If the underlying skills driving the xHR/FB rates stick in 2019, these hitters are at serious risk of HR/FB rate regression.

2019 HR/FB Decliners
Player HR/FB xHR/FB HR/FB – xHR/FB
Luke Voit 40.5% 30.8% 9.7%
Ryan O’Hearn 25.0% 18.5% 6.5%
Omar Narvaez 14.5% 8.2% 6.3%
Franmil Reyes 29.6% 24.0% 5.6%
David Peralta 23.4% 18.6% 4.8%
Eugenio Suarez 23.4% 18.6% 4.8%

Well duh, no hitter has a true talent 40.5% HR/FB skill, but daaaaamn Luke Voit was still incredibly good. In fact, his 30.8% xHR/FB rate was second highest in baseball to Christian Yelich. The sample size was tiny, of course, as it was over just 37 fly balls. The knee jerk reaction is that this was his Shane Spencer moment, but I am much more bullish.

Ryan O’Hearn might be a trendy sleeper depending on your league, but this was over a similarly small sample as Voit, and he had posted just a 9.6% HR/FB rate in Triple-A before his promotion. Who goes from 9.6% to 25% from minors to Majors?! He also is at risk of being platooned, as he posted a .729 OPS against lefties in the minors in 2018 and a .720 mark in 2017. That wouldn’t get him benched against southpaws in the Majors, but it’s likely to drop, perhaps significantly, at the higher level.

You’re probably not targeting Omar Narvaez, but he does have a starting job, and his sudden power spike might make you believe you’ll get double digit homers. But, the HR/FB rate wasn’t real. Be happy with him as your second catcher in a deep league, and that’s it.

It’s anyone’s guess how the Padres outfield playing time situation shakes out. They have at least four potential starting-worthy options for just two spots. Franmil Reyes is one of those candidates and is quite exciting. While he did outperform his HR/FB rate, his xHR/FB is still impressive and both his barrels per true fly ball and average fly ball distance marks were elite.

David Peralta was one of 2018’s more surprising power surgers, en route to an excellent fantasy performance. But xHR/FB rate isn’t totally buying. The good news — this was his highest xHR/FB rate driven primarily by a spike in average fly ball distance. But he’s already 31 and now in the middle of a Goldschmidtless lineup. He’ll be overvalued this draft season.

I can’t believe I haven’t published a Eugenio Suarez post, because his Statcast power trends are a thing of beauty. He has actually outperformed his xHR/FB in all four seasons on my spreadsheet, so perhaps he’s doing something special not captured by the equation. The last two seasons, his outperformance hovered in the 5% range, which is quite significant. 2018 represented the first year all three of his primary xHR/FB rate components settled in above the league average.

We hoped you liked reading 2019 HR/FB Rate Decliners by Mike Podhorzer!

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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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Uncle Spike
Member
Uncle Spike

I clicked on this article thinking I was sure to see Yelich on it. He went from a 15.3% HR/FB in 2017 to 35% in 2018. I’m not sure what goes into your equation but when I looked into it further, looks like it wasn’t just luck. He ranked in the top 17 in the majors in AVG EV, hard hit %, and brls/PA.

Pirates Hurdles
Member
Pirates Hurdles

Clearly it isnt jump in actual HR/FB it is HR/FB versus xHR/FB. Yelich’s leap must be well supported by batted ball data.