ESPN Home Run Tracker Analysis: The Downsiders

Two 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 SDD and 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.

Today I’ll begin by taking a look at the hitters whose high JE% suggests some downside. I only included players who hit at least 15 homers. The average JE% was 32% for the group.

Yoenis Cespedes — 59% JE%

Shocking (not sarcasm). Cespedes managed just a 9.6% HR/FB rate, well below his previous marks between 14% and 15% and now we learn that even those homers were essentially wall-scrapers. Sure enough, his batted ball distance fell precipitously by 15 feet, while his SDD also dropped to a career low. My xHR/FB rate formula spit out 13.2% suggesting that he was still a bit unlucky, but that was a far cry from his previous marks of around 17%. He has now been around 3% less than his xHR/FB rate in his first three seasons, which may suggest that he’s doing something not captured by my formula.

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Or, his home park has hampered his output given its 96 RHH home run park factor. When checking his splits though, that no longer seems like the explanation as he has posted a higher home mark than away. Whatever the explanation here, he’s a question mark next year, as only a career high in both plate appearances and fly ball rate kept his home run total above 20.

Yan Gomes — 57%

Gomes enjoyed an excellent fantasy performance and his HR/FB was seemingly in line with his small sample history. His xHR/FB rate also sat at almost exactly his actual mark and his distance and angle were both strong. The high JE% should certainly give one pause, but nothing else screams fluke. I’d project only very minor regression just given his limited Major League history.

Anthony Rendon — 57%

I was notoriously bearish on Rendon heading into the season, owing to both his lineup position and not enough pop to offset the apparent lack of speed. His 10.4% HR/FB looks quite reasonable and his 13.3% xHR/FB rate driven by a nearly eight foot jump in distance even suggests further upside. But 57% JE homers puts a damper on things. I had personally believed the power was legit, but now I’m a little less certain. And since he you have to assume a dropoff in stolen bases, he’s a huge risk in the second round, where I keep seeing him getting drafted. He’s not going to combine for anywhere close to 194 R+RBI again, so I just don’t see him earning his cost.

Mike Napoli — 53%

Napoli’s batted ball distance was over 300 feet and his xHR/FB rate was right in line with his actual mark, which itself was at its lowest since 2009. Once again the Home Run Tracker numbers are arguing with the other data. His SDD hit a career low, so perhaps that matches with the high JE%. He missed time last year due to various maladies, including a finger and back injury. One might assume that affected his power, but then I must ask why his distance wasn’t down. Obviously, without big-time power, Napoli isn’t much of an asset in fantasy leagues and at age 33, he might not be much more than replacement level in a shallow 12-teamer.

Justin Morneau — 53%

Not surprisingly, Morneau enjoyed a renaissance in his first year with the Rockies, but that was mostly due to an inflated BABIP and a significant cut down on strikeouts. His HR/FB rate was right in line with his previous two seasons. And once again, xHR/FB rate has a different take, thinking that his combination of distance, angle and SDD should have produced a nearly 15% HR/FB rate, versus the 11.5% mark he actually posted. Before looking at this data, I had figured a bit more power this coming year, but a sub-.300 batting average. So now I’m throwing up my hands.

Adam LaRoche — 50%

LaRoche posted his second highest HR/FB rate since 2006, but his xHR/FB rate metrics have been rather consistent since 2012, suggesting the low HR/FB rate in 2013 was the fluke. His JE% suggests downside, but his xHR/FB rate says he posted exactly what he deserved to. Of course, the more important matter is his move from Nationals Park to The Cell. The former sported a LHH HR factor of just 95, while The Cell augmented lefty home runs by 6% for a 106 factor. That’s a nice swing and should offset some of the possible regression he experiences due to aging.

So this didn’t exactly go as planned. Every hitter above had an xHR/FB rate around or above their actual marks, which is totally opposite of what their high JE% suggests. Which data point, the JE% or xHR/FB rate, do you agree with for these hitters?





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.

12 Comments
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Patrick
11 years ago

What is scary about Cespedes is that his average true distance dropped each of the last 2 years, especially last year and 9 of his 22 hrs last year came from center field to right.

SF Dave
11 years ago

It seems likely that these players are indeed living on the edge of HR decline and I would be hesitant to project any further power output from anyone hitting 50% wall scrapers. However, I think a major factor here might be SSS as the Home Run data is based on 15-30 samples while the HR/FB distances and SDD are based on a much larger sample. For this reason I wouldn’t look for too much regression either. It might be a Tacos and Beer thing. Why choose when they are both good and better together. If you find a guy that both numbers like then you can project more power. If you find a guy that both numbers don’t then you might be wary of a decline. I’m looking forward to reading seeing the other side of the coin and then (hopefully) a surgers and decliners article identifying those players that have both numbers in agreement. Keep it up. This is great stuff.

MustBunique
11 years ago
Reply to  SF Dave

Agreed on the sample size statement.

Are you thinking that Home Run Tracker might serve to help us define the distribution curve of balls hit within the SDD range? I think finding that distribution curve would be very useful and help us to further categorize the players that have a chance of increasing or decreasing their HR totals.

novaether
11 years ago

“Just Enough” homers are ones that cleared the fence by 10 feet or less. I imagine a lot of homers over the green monster clear by 10 feet or less, so it might not be fair to ding Napoli here (and maybe Cespedes, just a little).

The converse of this article would seem to indicate that there are players who would have “barely missed” homers. I don’t know if this data is even possible to track down, but it could be a good list of sleepers.

novaether
11 years ago
Reply to  Mike Podhorzer

To be honest, the best approach would probably be to use speed off the bat, vertical angle off the bat, and horizontal angle off the bat. Regress their averages, variances, etc against HR/FB and you’ve got your golden ticket. I know that’s available for home runs, but if you ever find out where to find it for fly balls please let us know!

OT
11 years ago

but Gomes still has pretty significant BABIP regression coming, right?

frivoflava29
11 years ago
Reply to  OT

He hits the ball pretty hard, last year he was at 24% LD even

MustBunique
11 years ago

xHR/FB can be looked at in depth and analyzed as there are more numbers involved vs Home Run Tracker categories really only accounts for the raw number of balls hit into those distance ranges. As novaether said above this doesn’t include Just Missed fly balls, whereas your xHR/FB does. I buy SDD and Abs angle, but Abs angle to a lesser extent even though you have shown a clear correlation between abs angle and HR (maybe I am biased and just have to warm up to the stat after another year of data is under our belts). Your xHR/FB formula makes sense, takes more raw data into consideration, and I would trust it a lot more than the old days of ESPN home run tracker distance categories. I like something that accounts for multiple lines of evidence, and I really like that there are more measureables to track from year to year. Good stuff POD. Keep it up.

Ryan BrockMember since 2025
11 years ago

Is it possible that the missing park factor in xHR/FB is what makes JE% not match up?

@MaineSkin
11 years ago

Rendon JE a product of his FB%? HIs FB% has risen the last 2yrs, so if that trend continues as young power hitters usually do, the HR/FB rate even stabilized, will probably result in more HRs. This guy only swings 40% of the time while making an elite 87% ct%. With that approach, unquantifiable here, we may see a lower 80s ct%, but increase in FB/LD%s with better power numbers. This is a kid who’s always been touted a “pro hitter” (lol), so using scouting and Pods work, I really think Rendon is headed for a 24-27 HR with an this era great BA. Now, he’s had 3 major surgeries before he even debuted, so if the Nats were smart, limiting his SBO% may be smart. I get the JE and agree 100%, but learning loft is a skill and Rendon looks like he’s right in the middle of a Rizzo type 3yr trend in HR output. Anyone see Rizzo’z FG page? 3yr positve gains everywhere! .258 BABIP looks like outlier now in ’13. Another kid to buy high in my book before his lineup boosts his contextual output.