ESPN Home Run Tracker Analysis: The 2016 HR/FB Downsiders
Three years ago, I conducted an exhaustive study of ESPN Home Run Tracker data. At that time, it was the primary tool I used to validate a batter’s power, before we got into the sexy new batted ball distance, and then combined that with standard deviation of distance and average absolute angle. The short story is I found that hitters with an unusually high percentage of “Just Enough” (JE) homers saw their HR/FB rates decline the following year, significantly more than the rest of the player population. On the other hand, those who hit a high percentage of “No Doubt” (ND) homers maintained their HR/FB rate much better than the rest of the group.
What’s interesting is that now we have two sources of HR/FB rate validation — this analysis and my xHR/FB rate. The hope is that they agree on the names, but I don’t know yet. So I will be cross-referencing the names I list here and discussing any disagreements. Refresh your memory with the list of downsiders produced by the xHR/FB rate equation.
For the first time, I lumped in “Lucky” homers with the “Just Enough” variety for a clearer picture of fortune. Here are the relevant definitions straight from the source:
“Just Enough” home run – Means the ball cleared the fence by less than 10 vertical feet, OR that it landed less than one fence height past the fence. These are the ones that barely made it over the fence.
“No Doubt” home run – Means the ball cleared the fence by at least 20 vertical feet AND landed at least 50 feet past the fence. These are the really deep blasts.
“Lucky” home run – A home run that would not have cleared the fence if it has been struck on a 70-degree, calm day.
Yesterday, I looked at the hitters with upside. Today, I’ll finish the analysis by taking a look at the hitters whose high JE + Lucky % suggests some major downside. The thinking here is that an errant gust of wind here and there or a millimeter difference in where the bat meets the ball may have assisted some balls to fly over the wall that may not happen again. I only included players who hit at least 15 homers. The average JE + Lucky % was 36.5% for the group.
| Name | JE | Lucky | JE+Lucky | Total HR | HR/FB | JE+Lucky % |
| Billy Butler | 10 | 1 | 11 | 15 | 10.8% | 73.3% |
| Brandon Crawford | 11 | 4 | 15 | 21 | 16.2% | 71.4% |
| Ryan Howard | 11 | 5 | 16 | 23 | 18.9% | 69.6% |
| Brandon Belt | 9 | 3 | 12 | 18 | 13.6% | 66.7% |
| Neil Walker | 8 | 2 | 10 | 16 | 9.9% | 62.5% |
| David Peralta | 8 | 2 | 10 | 17 | 17.7% | 58.8% |
| Kyle Schwarber | 7 | 2 | 9 | 16 | 24.2% | 56.3% |
| Wilmer Flores | 8 | 1 | 9 | 16 | 10.3% | 56.3% |
| Evan Gattis | 12 | 3 | 15 | 27 | 16.0% | 55.6% |
| Miguel Sano | 8 | 2 | 10 | 18 | 26.5% | 55.6% |
Aaaaaand Billy Butler continues to prove that his 2012 home run outburst was a complete fluke. The acquisition of Khris Davis may cut into Butler’s playing time a bit, so he’s just AL-Only material, and not even good material at that.
Well this is certainly interesting. Brandon Crawford’s HR/FB rate nearly tripled to easily set a new career high. The knee jerk reaction is to shout “FLUKE!!!!” and his sky high JE+Lucky % would validate those concerns. HOWEVER! His batted ball distance shot up 27 feet to over 300 feet! And his xHR/FB rate was actually 19.7%. That is completely opposite of what Home Run Tracker suggests. When at odds, I usually side with xHR/FB rate. Guess we’ll have to just wait and see.
…and Ryan Howard might officially be platooned. It’s about time! Also, xHR/FB rate agrees here. I wouldn’t touch him, though I doubt anyone is too excited to roster him.
Brandon Belt is another that we see a discrepancy between Home Run Tracker and xHR/FB. Belt’s xHR/FB rate has actually risen every season and hit a new career high at 17.1%. Obviously, the park is holding him back, and the deep right field wall may be resulting in an inflated JE number. It’s one of the shortcomings of using this method. I don’t think he has the downside his appearance here might suggest, nor the upside of xHR/FB, which fails to account for park factors.
Is it just me, or is Neil Walker super boring? Getting out of Pittsburgh will help, so he should avoid any potential downside.
Well damn, did anyone see a .380 wOBA coming from the bat of David Peralta? Did anyone even have a clue who David Peralta was before spring training? I sure didn’t. His xHR/FB rate validates his actual rate, which means that once again, the two methods are enjoying a heated argument. If he declines, I doubt that renders this method better — it’s simply because he probably just isn’t this good and will have trouble repeating that type of power.
Uh oh, not everyone’s favorite catcher eligible outfielder Kyle Schwarber! His batted ball distance was a robust 307.5 feet. But do you really expect him to sustain a mid-20% HR/FB rate? I think he’s a rather easy call to suffer some regression.
I hope Wilmer Flores isn’t too upset about being relegated to a reserve role. At least he won’t be as embarrassed if his HR/FB rate slips, because no one will really notice it if it comes in just 200-300 at-bats.
Finally, Evan Gattis is another where xHR/FB rate agrees. His distance was down 10 feet, but playing half his games at Minute Maid Park helped, as its home run boosting ways resulted in an 18.8% home HR/FB rate versus a 13.5% mark in away games. I say he remains rather neutral this year.
First Schwarber, now Miguel Sano?! His xHR/FB rate was relatively close to his actual, which is rather important considering his actual was a lofty 26.5%. But just like Schwarber, it’s just the laws of regression. Rookie gets first taste of Majors and puts on power show. League adjusts and he experiences some regression the following year. It’s more prudent to expect some decline than think he will post another top five HR/FB rate this year.
Mike Podhorzer is the founder of ProjectingX IQ, an advanced fantasy baseball analytics platform that transforms projection data and in-season performance signals into actionable intelligence. He 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.
I don’t know that David Peralta should go through much power regression next year, if any.
Is there any merit to look at home/road or RHP/LHP splits?
A ‘Just Enough’ HR in AT&T Park is probably still a decent HR.
Your question illuminates the major flaw with relying on Hit Tracker, as the home park influences the rate of JE homers for sure. Unfortunately they don’t give split data so I can’t use split results to compare them to. It’s why I generally just look at the players at the extremes for these exercises.
However the idea discussed here is still valid assuming the hitter remains in the same park. Regardless of how deep the fence is, if the majority of Belt’s shots barely pass over, there’s a good chance those same shots will just miss the following year.
This is true. It would only matter at let’s say Marlin’s Park.
Love this data Mike.
When playing fantasy I like to incorporate what I know about seasonal changes in parks that I’m familiar with. It’s not scientific but I am a weather buff so I frequently look at weather reports.
I live in the D.C. area and go occasionally to ballgames at both Camden Yards and Nationals Park in the spring (can’t go in the summer—don’t sweat due to neuropathy complications).
The wind at Nationals Park blows almost straight in during the spring most years (I like to start marginal pitchers at that park in the spring after reading the weather report).
The wind during the spring at Camden Yards tends to blow from left to right, pushing balls from right center closer to the foul pole and thus making it easier to clear the fence. It was nice to see Machado go the opposite way more often last year. If it’s a normal spring—and it may not be because of the El Nino effect which in the past has resulted in warmer springs—he might get help from the wind. If not, then a warmer spring should help batted ball distance anyway.
Re: Crawford. I have family in S.F. and the wind there blows west to east in the summer. Even though the park is on the east side of town where the winds are lighter, they are still noticeable in the summer. That park faces the east so I think Crawford will get a boost from the winds. Adding that to his increase in batted ball distance, I’m optimistic that he won’t regress too much.
I own him in one league, so bias is clearly involved too, lol.
How does lucky calculate the weather factors? Is it based off the weather report at the start of the game or somehow real time? I think it’s an interesting metric but probably flawed considering a day with 30MPH gust blowing out does not necessarily mean it’s constant and always helped a batter. A batter could have hit a homerun when there was no gust at the current time and still be discredited for a valid result. It would be interesting to see how they accounted for the weather factors.