ESPN Home Run Tracker Analysis: The 2016 HR/FB Upsiders
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 upsiders produced from 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.
Today I’ll begin by taking a look at the hitters whose low JE + Lucky % suggests some major upside. The thinking here is that an errant gust of wind here and there or a millimeter difference in where the bat meets the ball could push balls that had been fly outs to head just over the wall. 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 % |
| Jedd Gyorko | 2 | 0 | 2 | 16 | 13.7% | 12.5% |
| Jonathan Schoop | 1 | 1 | 2 | 15 | 17.4% | 13.3% |
| Brian McCann | 4 | 0 | 4 | 26 | 14.9% | 15.4% |
| Chris Carter | 3 | 1 | 4 | 24 | 18.9% | 16.7% |
| Justin Bour | 4 | 0 | 4 | 23 | 21.5% | 17.4% |
| Albert Pujols | 7 | 0 | 7 | 40 | 17.8% | 17.5% |
| Giancarlo Stanton | 4 | 1 | 5 | 27 | 32.1% | 18.5% |
| Adam Jones | 4 | 1 | 5 | 27 | 16.8% | 18.5% |
| Rougned Odor | 3 | 0 | 3 | 16 | 11.8% | 18.8% |
| Nolan Arenado | 8 | 0 | 8 | 42 | 18.5% | 19.0% |
Poor Jedd Gyorko. His power finally returned in the second half of last season, so he got rewarded with…a trade to the Cardinals, where he’ll serve on the weak side of a platoon. Unless Kolten Wong suffers an injury, there’s no fantasy value here outside of NL-Only leagues.
A serious knee injury limited Jonathan Schoop to just 321 plate appearances last season, but his power surged and he got his balls in play to fall for hits at a better than league average clip this time around. It’s hard to believe there’s a whole lot of upside left given his 17.4% HR/FB rate. But get this — his batted ball distance finished at just above 300 feet, good for an exciting 20.2% HR/FB rate. He also plays in a home park that boosts right-handed home runs. So here, Home Run Tracker and xHR/FB rate agree that there is further upside. Given the time he missed that artificially reduced his counting stats, he could very well be undervalued and prove to be a nice source of profit in all league formats.
We all assumed that a move to the second best home run park for left-handed hitters would boost Brian McCann’s HR/FB rate when he arrived at Yankee Stadium in 2013. But that didn’t happen, as his HR/FB rate actually fell to its lowest mark since 2008. However, it then jumped in 2015, which we initially expected it to, and he posted the second highest mark of his career. Entering his age 32 season, we wouldn’t normally expect another bump in HR/FB rate, but there’s seemingly a greater possibility than one would assume.
Chris Carter leaves one good home run park for another, even better home run park. His HR/FB rate hit a career low last year and he has a good chance of rebounding. Unfortunately, there’s little you could do to prevent the damage he will do to your batting average.
Justin Bour?! I’m still not sure where this man came from, but an xHR/FB rate of 20% suggests that his power was no fluke. Whether he could replicate the components of his xHR/FB rate is anyone’s guess though. The fences moving closer at Marlins Park will provide an assist in helping him sustain that power output at least.
Just when we thought that Albert Pujols‘ days of elite power were over, he goes out and posts his highest HR/FB rate since 2011. His xHR/FB rate agrees that his power has rebounded, but not quite to the degree he displayed. Despite what Home Run Tracker suggests, his age plus recovery from foot surgery means that it would be more prudent to bet on a decline than any sort of upside from his 2015.
Jeez, Giancarlo Stanton, are you serious? Are you not satisfied with a 30%+ HR/FB rate? Between his appearance on this list and the fences moving in at Marlins Park, it’s scary to think there’s a non-zero chance of even greater power output.
Adam Jones battled injuries, but all his performance metrics were generally in line with his history. Only a career low BABIP pushed his wOBA down to its lowest mark since 2008. Coming off the second highest batted ball distance of his career, xHR/FB rate (21.9% 2015 mark) agrees that Jones was due for some better HR/FB rate fortune in 2015. I would bet against though, just because I don’t see a 30-year-old maintaining that inflated distance.
The cat’s out of the bag, Rougned Odor, and the scent smells wonderful. Having looked at few, if any, sleeper lists, I can still guarantee he makes the majority of them. He’s that fun “sleeper who isn’t” this year whose cost essentially requires a breakout just to break even for his owners. When everyone is targeting the same sleeper, the cost rises and he no longer qualifies as one. His expected lineup slot toward the bottom of the order hurts, but I’m forecasting a 20 homer/10 steal season, which is worth significant value, even if the runs scored and runs batted in totals aren’t overwhelming.
Ha, Nolan Arenado, you’re silly. You mean there is potentially even more growth in that bat according to this analysis?! You’d think that after jumping from a 7.1% HR/FB rate to 11.4% to 18.5%, that he would be done and take a rest. Once again, xHR/FB rate agrees there may very well be the slightest hint of additional upside, as it calculated a mark of 21.1%. He’s already going in the first round, so there’s not a whole lot of profit opportunity, but he does appear to be a relatively safe investment.
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.
In the first paragraph, you state that players with a lot of ‘just enough’ HRs saw their HR/FB rates decline the following year. Then you go on to identify players with a lot of JE and lucky homers, and suggest (I think) that these players might improve next year. What am I missing? Thanks.
Never mind…I see that these players were selected because of their LOW JE + lucky HRs.
I think you missed this sentence from the paragraph before the table:
Today I’ll begin by taking a look at the hitters whose low JE + Lucky % suggests some major upside.
Essentially, it’s the opposite of what I wrote in the first paragraph about high JE% leading to decline. So low JE% would lead to upside.
Mike,
I know this has nothing to do with the article, but I’m wondering what you’re projecting for Billy Hamilton this year. I’ve got him for a .250 average, 7 HR, 70 SB and 65 runs with 45 RBI. To me, this seems very reasonable. Last year he significantly improved on his stolen base success rate and if he would’ve had 550 ABs he would’ve stolen 70 bases. This year, if he can maintain that success rate and get more at bats-which he should as long as he’s hitting .250-he should be able to easily get 70 bags. Aldo, your xBABIP formula had him improving, and because of that I think .250 is almost a pessimistic projection for Billy. When I run that through my SGP formula he ends up as one of the top15 hitters. But everywhere else I look, he doesn’t even seem to crack the top 15 outfielders! I don’t know if this is due to a difference in projections, I know Steamer has him with just 60 steals, or if I’m over valuing steals or something like that. Whatdya think?
I worry about all projections when it comes to Hamilton because of his extremely low power, things like xBABIP may not do well at the extremes. His exit velocity on FB/LD was the lowest in MLB, and he’s in the bottom 20% on grounders. He’s fast, but most hits leave the bat between 85-95 mph, and that’s well below the cutoff for good outcomes.
http://www.fangraphs.com/blogs/exit-velocity-part-i-on-the-import-of-exit-velocity-for-hitters/
Plus you’re looking at coming off a shoulder injury/surgery. I think its a big risk to assume 45 RBI or 7 HR, and maybe even .250, especially if he hits at the bottom of the order.
He’s expected to hit at the bottom of the lineup, so I’m only projected 551 PA and 511 AB. 5 HRs, 70 runs, 36 RBI, 60 steals, batting .253. I think your projections are optimistic and essentially his ceiling. That said, I would ignore the rankings.
Most rankings list don’t use calculated values mathematically. Instead the rankers just look at player names and move players up and down, guessing at value. That’s pretty useless. You’ll notice that any time you use an actual auction value calculator, Hamilton will be worth much more than on a rankings list. That’s why – the math says he’s worth a lot, but rankers aren’t doing the math. It depends on the format whether he’s top 15 or not. In a deeper league, he is since you can’t find steals on free agency. In shallower leagues where the Anthony Goses and Rajai Davises of the world are free, Hamilton is worth less.
Thanks much Mike!
This list is so full of guys that I would pick for less homers than last year, are you totally sure you didn’t read these percentages backwards or something??
Hey Mike. Have you looked back at your under and over achievers to see how the actual results compared to expectations based on this methodology?
You betcha. The 2015 recap links are below, can’t remember if I wrote any articles about it before 2015.
http://www.fangraphs.com/fantasy/reviewing-espn-home-run-tracker-analysis-the-2015-upsiders/
http://www.fangraphs.com/fantasy/reviewing-espn-home-run-tracker-analysis-the-2015-downsiders/
As expected, downside list did much better than upside list. Of course, the sample size is tiny with few names on each, so can’t take much meaning from one year of results.
Thanks, much appreciated. Looking forward to more seasons and more data. Great stuff as always.