The xHR/FB Rate Overachievers

On Monday, I unveiled the xHR/FB rate equation I devised a year ago. Yesterday, I began my look back at 2014, discussing a selection of hitters whose xHR/FB rates suggest serious HR/FB rate upside this year. Today, I finish my look back, this time at the overachievers. These are the bust candidates, at least when it comes to home runs, assuming of course they sustain similar batted ball distances, average absolute angles and standard deviation of distances (SDD). Since my formula ignores home ballpark which absolutely plays a major role, I will mention it as a possible explanation for such overperformance as warranted.

Chris Carter — 15.3% xHR/FB vs 21.9% actual HR/FB

Through May, Carter had hit just eight homers and his HR/FB sat below 14.0%. He then went on to post rates above 22% every month since, finishing the season with a new career high of 37 homers, tied for second in baseball. But his batted ball distance fell about 10 feet and his SDD fell to a career low. Minute Maid Park does sport a 104 RHH home run park factor and he has seemingly benefited greatly from calling the park home last year. His home HR/FB rate sat at 25.9% vs 18.2% in away parks in 2014, but he posted opposite splits in 2013. While I would be he improves on the components driving his xHR/FB rate mark, be aware that there is some hidden downside here from a power perspective.

George Springer — 21.4% xHR/FB vs 27.8% actual HR/FB

Immediately below Carter on the biggest overachievers list is his teammate, former uber prospect George Springer. His appearance here could be taken two different way. The pessimistic side views his inflated HR/FB rate the result of a heaping amount of luck. Considering his issues with making contact and the threat of the league making additional adjustments to combat his power during his sophomore season, he could be a prime bust candidate.

On the other hand, the optimist would argue that a 21.4% xHR/FB is still darn good!That ranked ninth in all of baseball, which includes a couple of part-timers. He also ranked third in baseball in batted ball distance…as a rookie. His xHR/FB isn’t higher because his angle was a bit below the league average.

I most certainly land in the optimistic camp. I don’t think anyone is really expecting him to maintain a near 28% HR/FB rate, but his distance and xHR/FB validate that he possesses immense power. My only question revolves around his speed and willingness to steal bases. His value changes drastically if he’s a 20-30 steal guy like his minor league numbers suggested, versus struggling to reach double digits.

Jose Abreu — 22.8% xHR/FB vs 26.9% actual HR/FB

Abreu surpassed even the most optimistic of expectations during his rookie campaign and the knee jerk reaction would to expect some regression now that the league has a full season’s worth of data on him. He finished ninth in baseball in batted ball distance and third in xHR/FB, behind just Giancarlo Stanton of the full-timers. He was also rather strong in SDD, mixing in serious blasts with his garden variety flies and was just above average in angle.

Here’s another example of a home park that might explain some of his xHR/FB rate outperformance. U.S. Cellular Field sports a RHH home run factor of 114, which was tied for second highest in baseball last year. But, Abreu actually posted a higher HR/FB rate in away parks. I would project some regression just given our limited sample of Major League data and that BABIP is surely due for a decline. But I wouldn’t avoid him and can’t say whether he’s looking overvalued just yet.

Oswaldo Arcia — 15.8% xHR/FB vs 19.4% actual HR/FB

I was a big fan of Arcia heading into 2014, boldly predicting he would hit 30 homers and then landing on him as my bold home run league leader. I was right about his power, at least directionally — his HR/FB rate spiked from 14.7% to 19.4%, but injuries and continued strikeout problems limited him to just 20 homers.

But that HR/FB rate surge looks a bit fluky. His distance actually fell by over 10 feet, while his angle declined, offset by a jump in SDD. It led to an xHR/FB rate that was a bit worse than his 2013 mark. And Target Field sports a 91 LHH home run factor, meaning we wouldn’t expect the park to boost his actual HR/FB rate above his expected mark. Perhaps more troubling, however, is that he is still dealing with the back issues that plagued him last season. That’s the type of problem that tends to linger and it could really sap power. As badly as I want to get behind him as a sleeper again, I’m staying away this time since he’s unlikely to come as cheap as he did heading into 2014.





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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novaether
9 years ago

Regarding Abreu, I wonder if the big SDD was due to the way he was pitched. As previous articles on this very site have pointed out, pitchers often tried to beat Abreu with good inside fastballs. In the event they got the pitch sufficiently up and inside, I’m guessing he gave up the “garden variety fly”. In fact, he hit zero homers on pitches in the inner-upper 1/9th of the zone according to baseball savant. However, he crushed fastballs accidentally left over the plate (as noted by his league-leading wFB/C). This could mean that his large SDD is more sustainable than the regressed equation assumes.

novaether
9 years ago
Reply to  Mike Podhorzer

You’re right. I misspoke. I’ll rephrase my argument, then, to say that it’s plausible that Abreu’s distribution of batted ball distances may not follow the same general shape as the average batter’s distribution of batted ball distances. More specifically, the kurtosis of Abreu’s distribution of batted ball distances may be more negative (flatter) than the average batter’s kurtosis. A batted ball distance distribution with a deviant kurtosis (and skew, for that matter) would explain a lot of the over/under-achieving-ness. It may be overkill, but it may be interesting to regress the third and fourth moments of batted ball distance to HR/FB rate. You’ve already done the first moment (average distance) and second moment in a round-about way (SDD). Seeing a regression for each moment individually and a year-to-year correlation for each might be enlightening.

Poncho Villa
9 years ago
Reply to  Mike Podhorzer

Solid article. I am interested to hear your opinion on what novaether is saying. His second half split seems odd and superficial could support the argument because his BABIP skyrocketed to plus 400s and his HRs dropped precipitously.

Thoughts?