Taking Home Runs Back to 2015 by Ben Clemens August 21, 2019 If you’re reading this article, you’re probably not dead, and if you’re not dead, you’ve heard all the fuss about soaring home run rates. I’m not here to judge your perspective on it — I think reasonable people can disagree on how they like their baseball, though I will say that I love a good strikeout and feel pretty neutral about home runs. But I think one thing everyone wonders about is who this all helps. It’s not the pitchers, clearly. It doesn’t seem to be the big boppers — despite the stupendous home run totals, no one is threatening to hit 73 home runs any time soon. Heck, no one has approached 61 since Giancarlo Stanton’s chase in 2017, and that was a singular event rather than a wave of history-chasing sluggers. Is it the little guys? Freddy Galvis has 20 dingers on the year — that has to count for something. There’s a lot of chicken-and-egg going on here and no real answers to the answer of who benefits the most from the livelier ball. That’s why I looked to the minor leagues to see which players were most affected by the new ball. That study was basically inconclusive, aside from showing that players with absolutely no power are barely affected. I thought I’d take a different look at it today. It’s hard to say who has benefited the most from the new ball, but what if we could answer a different question: who would be most affected if the league surreptitiously replaced today’s baseballs with old ones overnight? There’s been plenty of research about what’s changed with the new balls, but the general consensus among scientists is that the key change has been to the drag coefficient of a baseball in flight. In other words, a ball hit at the same angle and speed will carry farther, on average, now than it did before. If the only thing that has changed is how far the ball carries, we can use that data to do a little mathematical trickery. I recently came up with expected home run rates based on exit velocity of line drives and fly balls, which lets us know how many home runs a player “should” hit based on the actual balls they hit, rather than just using average exit velocity or ignoring that data altogether. That data, of course, is based on how often balls of a given velocity leave the park in 2019. There’s no reason we have to leave it that way, though. We have launch angle and exit velocity data going back to 2015, when there were 4,909 home runs all year — we’re at 5,274 (as of Monday) this year already, on pace for 6,835. As you would expect given the changing aerodynamics, hitting a ball in the air is a lot more valuable this year. To explain just how valuable, I took all the balls hit in the air this year and refined them a little bit — I defined the balls that could become home runs as anything hit between 15 and 45 degrees, essentially line drives and fly balls excluding low line drives. This is slightly different than the Statcast definition (10 to 50), but it only excludes regions with almost no home runs, so it should make the study work somewhat better. With that in mind, let’s look at how often air balls at each exit velocity turn into home runs, both in 2015 and now: Home Run Rate Changes by EV Exit Velocity (mph) 2015 HR% 2019 HR% Increase 90 0.50% 0.90% 0.40% 91 0.80% 1.40% 0.60% 92 2.00% 3.50% 1.50% 93 2.40% 4.00% 1.60% 94 4.40% 6.10% 1.70% 95 6.20% 6.80% 0.60% 96 8.50% 9.40% 0.90% 97 10.70% 11.70% 1.00% 98 13.80% 17.00% 3.20% 99 17.70% 21.00% 3.30% 100 24.20% 29.40% 5.20% 101 28.60% 36.10% 7.50% 102 41.20% 43.40% 2.20% 103 46.70% 48.80% 2.10% 104 48.60% 52.40% 3.80% 105 52.90% 53.30% 0.40% 106 56.70% 57.50% 0.80% 107 57.00% 61.00% 4.00% 108 61.90% 66.30% 4.40% 109 64.70% 68.30% 3.60% 110 70.40% 71.60% 1.20% The data isn’t perfect, of course: we’re excluding the exact launch angle of each ball, as well as any back- or top-spin. It’s still a good approximation though, and it shows that every ball hit in the air is more likely to become a home run now than it was in 2015; even the puny 90-mph bucket gets a boost. With that transformation done, we can take every air ball hit this year and apply 2015 expected home run rates to it. Then we simply compare to the 2019 expected home run rates, and we have our biggest losers if the ball were to be rolled back. There doesn’t appear to be much of a pattern: Biggest Losers (By Change in xHR%) Player 2019 xHR% 2015 xHR% Change Mitch Moreland 24.07% 21.75% -2.32% Brandon Lowe 25.98% 23.68% -2.31% Nelson Cruz 35.77% 33.51% -2.26% Josh Donaldson 29.45% 27.23% -2.22% Marcell Ozuna 31.05% 29.03% -2.03% Ryon Healy 17.06% 15.04% -2.02% Lourdes Gurriel Jr. 21.84% 19.84% -2.01% Miguel Sanó 34.15% 32.15% -2.01% Wil Myers 27.97% 25.97% -2.00% José Altuve 19.16% 17.19% -1.96% There are a good number of big boppers in there; Nelson Cruz and Miguel Sanó don’t exactly seem like the kind of people begging for a little extra juice to let them hit the ball over the wall. Donaldson and Ozuna are interesting names: my pre-2015 brain still thinks of them as well-rounded offensive players who hit 20-30 home runs a year, but Donaldson has 41 and 37 home run seasons in the past five years, and he will probably settle in around that range again this year. Ozuna launched 37 in a power-mad 2017, and if it weren’t for injury this year, he’d be threatening that mark again. Altuve is the player we all expected to see on this list: he’d never hit more than seven home runs in a season before 2015. Though the ball was already jumping in 2015, he only hit 15 that year. Since then though, he’s had 24, 24, 13 in a down year, and 22 (and counting) this year. That seems like the kind of player who should be affected most. Still, no one’s losing more than 2.5% — it’s not a sea change by any means. How about the other end of the spectrum, the hitters who aren’t getting any value out of the newly explosive baseball? It’s basically who you’d expect, with one exception that we’ll get to in a minute: Least Affected (By Change in xHR%) Player 2019 xHR% 2015 xHR% Change Billy Hamilton 0.81% 0.60% -0.21% Nicky Lopez 3.60% 3.15% -0.46% Dee Gordon 2.62% 2.08% -0.54% J.P. Crawford 6.64% 6.06% -0.58% David Fletcher 3.75% 3.17% -0.59% José Peraza 3.92% 3.32% -0.59% Tony Wolters 4.37% 3.74% -0.63% Eric Sogard 4.20% 3.49% -0.71% Ender Inciarte 4.24% 3.50% -0.74% Hanser Alberto 4.21% 3.46% -0.75% Wait — Eric Sogard? He’s the kind of person who you’d expect to be helped most by the new baseball. You can’t tell me that Eric Sogard having 13 home runs isn’t due to a change in the baseball. Here’s the thing, though — even with the 2019 baseball, Sogard’s air balls shouldn’t lead to this many home runs. Per my xHR%, he would only have 4.8 home runs on the year. Whatever he’s doing, it’s not picked up by exit velocity. Maybe it’s luck, maybe it’s backspin, maybe he’s hitting the ball on the perfect trajectory. Whatever it is, this model isn’t picking it up in either 2015 or 2019. Rates are only part of the game. Let’s look at the most-hurt list again, only with home runs as the sorting mechanism rather than home run rate change. This is another interesting thing to consider; if the ball changed, launch angle changers might be left high and dry: Most Home Runs Lost Player xHR’s Lost xHR% Decrease Air Balls Anthony Rendon -2.89 -1.90% 152 Cody Bellinger -2.88 -1.81% 159 Freddie Freeman -2.80 -1.74% 161 Mookie Betts -2.78 -1.60% 174 Eduardo Escobar -2.74 -1.27% 216 Justin Turner -2.65 -1.71% 155 Alex Bregman -2.60 -1.70% 153 J.D. Martinez -2.53 -1.70% 149 Brandon Belt -2.50 -1.52% 165 Nicholas Castellanos -2.47 -1.55% 159 Okay, so the effects on expected home run rate aren’t huge. Two or three home runs is a big deal, but no one’s losing 10 jacks or anything. Rendon has become much more of a fly ball hitter over the years, so he seems like a reasonable biggest loser. The other side of the ledger is uninteresting, so I’ll skip it. Hamilton only loses .15 home runs of expectation, for example, but he was only expected to hit .5 in the first place, so he’s bounded by zero more than anything. More interesting, to me, is that even with speed translating to home runs at the decreased 2015 level, we’d be on pace for 6,422 home runs this year, easily a record. The 2015 season wasn’t exactly the dead ball era, but this year’s batted balls would produce a lot more home runs regardless of the ball. That leads us to a question: hey, didn’t the baseball change during 2015? The general narrative is that there was a clean break in home run rate at the All-Star break. That checks out — HR/FB% went from 10.7% in the first half to 12.1% in the second half. Despite that, increased carry doesn’t seem to be to blame — I ran both halves separately, and the exit velocity buckets were nearly indistinguishable. Why is that? Alan Nathan to the rescue again — his study showed that exit velocity increased by roughly 1 mph for relevant batted balls in the time period in question. The cause of that increase is tough to pin down, and there’s no clear evidence that the exit velocity boost was caused by the ball rather than by something else — batters getting better, the grip making pitchers throw more hittable pitches, or anything else you can think of. It could be, unlikely as it seems based on Nathan’s and Meredith Wills’ later studies, that the changed balls somehow increased exit velocity, rather than only decreasing drag. The evidence doesn’t point that way, but it’s certainly not impossible. Fine then! Let’s cut 1 mph off of every batted ball this year, then translate those batted balls through our 2015 exit velocity buckets. Now the list of home runs lost is getting serious: Most Home Runs Lost, Take 2 Player xHR’s Lost xHR% Decrease Air Balls Anthony Rendon -7.64 -5.02% 152 Cody Bellinger -7.37 -4.63% 159 Mookie Betts -6.99 -4.01% 174 Nicholas Castellanos -6.76 -4.25% 159 Freddie Freeman -6.63 -4.12% 161 Alex Bregman -6.49 -4.24% 153 J.D. Martinez -6.42 -4.31% 149 Justin Turner -6.41 -4.13% 155 Eduardo Escobar -6.16 -2.85% 216 Ozzie Albies -6.05 -3.58% 169 Though the names are mostly the same, the losses are deeper. There are a collective 1,174 home runs lost across the sport in this hypothetical. Being a fly ball hitter would be significantly worse in this environment. And yet, we’d still be on pace for 5,535 home runs this year. That’s more than were hit in 2015, even after average exit velocity ticked up in the second half. It’s nearly as many as were hit in 2016 and 2018. What this says, to me, is that the cause of all these home runs isn’t as simple as a changing baseball. Players have changed what they do pretty markedly, trying to lift more balls in the air in the velocity bands that most translate to home runs. Pitchers have done their part too by leaning more on pitches with low ground-ball rates and less on sinkers. At the current pace, hitters will end the year with nearly 3,000 more balls that fit my criteria — exit velocity over 90 mph, launch angle between 15 and 45 degrees. Almost all of those come in the super-high-value band of balls hit more than 100 mph; in fact, even if you took 1 mph off of every hit in 2019, there would still be a thousand extra-high-velo air balls in 2019 as compared to 2015. Hitters are hitting more balls with the potential to become home runs, and the rabbit ball is launching those potential home runs into the stratosphere, both literally and figuratively. As is often the case in baseball, the story isn’t quite as simple as “the ball changed, and home runs exploded.” Those two things happened, sure, and the ball has caused a lot more home runs, but it hasn’t caused all the extra home runs. Hitters aren’t dummies, and they’ve started trying to hit more long balls. Pitchers have compensated by going for more whiffs, and the pitch at the forefront of that movement, the four-seam fastball, happens to allow a lot of fly balls. I set out, in this study, to show which home runs the ball had created in the last four years. I think I’ve accomplished that, but the real revelation is that hitters have done their part to add to the dingerization of baseball. Strip away exit velocity, make the ball less aerodynamic, and they’d still be out-homering 2015 by a decent amount. In idyllic first-half 2015, batters hit an annualized 4,361 home runs. This year’s batters, even arbitrarily robbed of a mile of speed and using a less aerodynamic ball, would hit an extra 1,200 home runs. It’s the ball, but it’s not just the ball.