ESPN Home Run Tracker Analysis: The 2016 HR/FB Downsiders – A Review

In addition to the analysis I conduct using my xHR/FB rate equation, I also still look at ESPN Home Run Tracker after the season ends. As usual, I identified a group of hitters before the 2016 season that based on the Home Run Tracker data, appeared to have serious HR/FB downside. Let’s find out how these hitters performed.

The JE+Lucky % HR/FB Downsiders
Name 2015 HR/FB JE+Lucky % 2016 HR/FB 2016 HR/FB – 2015 HR/FB
Billy Butler 10.8% 73.3% 8.2% -2.6%
Brandon Crawford 16.2% 71.4% 7.5% -8.7%
Ryan Howard 18.9% 69.6% 26.6% 7.7%
Brandon Belt 13.6% 66.7% 9.3% -4.3%
Neil Walker 9.9% 62.5% 16.2% 6.3%
David Peralta 17.7% 58.8% 10.8% -6.9%
Kyle Schwarber 24.2% 56.3% N/A N/A
Wilmer Flores 10.3% 56.3% 13.6% 3.3%
Evan Gattis 16.0% 55.6% 24.1% 8.1%
Miguel Sano 26.5% 55.6% 20.8% -5.7%
The average JE + Lucky % was 36.5% for the group I plucked my downside candidates from

It still baffles me how many careers from a power perspective look like Billy Butler’s. Just one year (2012), every fly ball was hopping over the fence. And then it stopped. Was it just a complete fluke where every gust of wind happened to blow out during his at-bat? Whatever the explanation, Butler finally lost his starting job after failing to hit like a designated hitter for a third straight season.

Brandon Crawford is about a year younger than Butler, and his career may end up looking similar from a power trend perspective. In 2015, he suddenly boosted his HR/FB rate from the mid-single digit range to the mid-teens. It didn’t last and the Home Run Tracker data seemed to know a collapse back to previous levels was coming.

Ryan Howard found the fountain of youth and battled both age and ominous Home Run Tracker data to post his highest HR/FB rate since 2012. Too bad it still wasn’t enough to make him any sort of offensive contributor. His .298 wOBA was a career low and finally cost him his starting job.

I, and I’m sure many of you, keep waiting for that big Brandon Belt breakout. AT&T Park obviously hurts — his career home HR/FB rate is about half of his away mark –, and even with a career high fly ball rate and a full season of plate appearances, he was still unable to reach the 20 homer plateau. Since stolen bases may no longer be part of his fantasy game, a power breakout is going to be required to be worth much more than replacement level in shallow mixed leagues.

At age 30, Neil Walker decided to sell out for power and suddenly start pulling everything. His fly ball pull rate sat in the 20% range, never exceeding 27.2%, throughout his entire career, until this year, when it jumped to 31.7%. That kind of change in philosophy is impossible to predict and it’s also difficult to determine whether he sustains the changes. Does he fall back to the mid-20% range of pulled fly balls next year or is 30%+ his new level? Answering that question will tell us whether a mid-teens HR/FB rate next year again is at all a possibility.

Injuries limited David Peralta to just 183 plate appearances and while his HR/FB rate collapsed back near his 2014 mark before his 2015 spike, who knows how much that decline was health related. I’m not sure he has a guaranteed starting role next year.

Does Kyle Schwarber’s busted knee affect his future power output?

In a part-time role, Wilmer Flores matches his home run total from 2015 and his ISO has been in a nice upward trend. If only he could get that BABIP up from his measly .270ish mark, he could enjoy a breakout, contributing in both homers and batting average.

I was a year too early on Evan Gattis enjoying the move from pitcher friendly Atlanta to the more hitter friendly Houston. But Home Run Tracker actually hinted at good fortune keeping him afloat in 2015. The explanation here is obvious — in 2015, his Pull% on flies plummeted to just 20.1%, well below the 30% marks he had previously posted. This year, his Pull% fully rebounded back to 34.6%, which allowed him to take advantage of the friendlier home park. Luckily, he keeps his catcher eligibility for another year.

While we all knew Miguel Sano was not sustaining a .396 BABIP and his batting average was at major risk for collapse, we believed in his power. The Home Run Tracker data didn’t, however, and his HR/FB rate declined by a meaningful rate. Without the boost from a highly inflated BABIP and combined with the power surge the league enjoyed, he was essentially replacement level while actually on the field in shallow mixed leagues. The strikeout rate is obviously the key to his future.

Typically the downside list is easy to hit as players age and HR/FB rates are going to trend down. But the leaguewide home run spike threw all that out the window. Really, the only big name bust that this list helped you avoid (besides Schwarber, but that was injury related) was Sano. I’ll reiterate that I much prefer using my xHR/FB rate equation for this type of analysis and rely on what the Home Run Tracker data suggests far less. It’s really a sample size thing because we’re only looking at home runs and not all fly balls.





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.

4 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments
CRPerry13
7 years ago

Why is “Houston is a hitters park” still being perpetuated? It has played neutral to slightly favoring pitchers for over a decade. It only very slightly helps home run hitters, but not enough to be meaningful when moving from Atlanta (HR PF 99) to Houston (105), a bump of only 5 spots in the HR PF rankings.