Continuing my pattern of enjoying the festivities around the All-Star Game the most, I've always loved the Home Run Derby. As a kid, when I'd come home from school, the old reruns of Home Run Derby from the 1960s were on. Because I was born in 1978, I got to see a lot of players whose careers I had missed out on, like Hank Aaron, Willie Mays and Mickey Mantle. This was before ESPN Classic was launched and the internet was really a thing.
<aside class="inline float-r inline-track" style="box-sizing: border-box; font-family: -apple-system, BlinkMacSystemFont, Roboto, Arial, "Helvetica Neue", Helvetica, sans-serif; border: 1px solid rgb(220, 221, 223); clear: none; margin: 6px 0px 15px 18px; padding: 15px; width: 282.5px; float: right; color: rgb(0, 0, 0); font-size: 16px;">[h=1]2018 MLB Home Run Derby[/h]
Who will reign supreme at Nationals Park? (8 p.m. ET, Monday on ESPN & ESPN App)
Bracket & facts »
</aside>Recently, in a discussion, I was asked "Dan, can you predict a Home Run Derby?" My first answer was an extremely helpful "Dunno," but it got me thinking if we could predict a Home Run Derby, using both the matchups and results. We don't have a lot of data, but modeling these things always gives an interesting glimpse into the inner workings of things.
So, I found variables for the three most recent Home Run Derbys -- I'd love more years, but the formats shift a lot and I wanted to see first if Statcast data would be helpful -- and started from there. A few variables, some surprising, some not, came up as useful predictors of Derby performance. Sixteen of the 21 matchups from 2015-2017 were won by the player with the higher average exit velocity and the margin tended to be correlated with their difference in the rankings. Also helpful were things like home runs-per-ball hit, and even recent performance seemed to have more predictive value in a Derby than in real life.
I'll spare the nitty-gritty ins-and-outs of dimensionality reduction and go right to the results, plugged in for this year's Home Run Derby, matchup by matchup.
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[h=2]Round 1[/h]
No. 1 Jesus Aguilar (59 percent) over No. 8 Rhys Hoskins (41 percent)
Hoskins is coming on lately, with seven home runs over the past 28 days after only six total for April and May. But Hoskins is just barely in the top 100 for average FB/LD velocity (fly ball and line drive) and rate of "barrels." For those not familiar with barrels, it means hits that have the exit velocity and launch angle that average at least a .500 batting average and 1.500 slugging percentage.
No. 5 Kyle Schwarber (61 percent) over No. 4 Alex Bregman (39 percent)
Jonah Keri didn't coin the Super Nintendo nickname for Schwarber for no reason. Schwarber has the second-most barrels of the eight contestants, behind just Max Muncy, as a percentage of batted balls hit. This is the year. Bregman has advanced to be a true superstar, but in terms of raw power, Schwarber has the edge.
No. 7 Freddie Freeman (55 percent) over No. 2 Bryce Harper (45 percent)
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No. 3 Max Muncy (67 percent) over No. 6 Javier Baez (33 percent)
As unlikely as Muncy's emergence has been in 2018, it's hard to say from his Statcast data that the power isn't real. When it comes to the barrel rate, Muncy is third in baseball among all players with at least 100 batted ball events, behind just two others known for raw power (Joey Gallo and J.D. Martinez) and edging out Eric Thames, Matt Davidson and Aaron Judge.
[h=2]Round 2[/h]
Aguilar (53 percent ) over Schwarber (47 percent)
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</article>Aguilar's run, which has seen him hit 14 home runs in his most recent 32 games, is enough to just squeeze over Schwarber in the projections here. It's close, though -- Aguilar may have more homers, but Schwarber's fly balls and line drives have more velocity.
Muncy (66 percent) over Freeman (34 percent)
Freeman is projected to beat Harper in the first round, but Freeman's offensive value is still more of the all-around type than simple raw power. Muncy pretty much sweeps the Statcast data, and while I would happily trade Muncy for Freeman in real life, M-squared has the edge.
[h=2]Finals[/h]
Muncy (55 percent) over Aguilar (45 percent)
<aside class="inline float-r inline-track" style="box-sizing: border-box; font-family: -apple-system, BlinkMacSystemFont, Roboto, Arial, "Helvetica Neue", Helvetica, sans-serif; border: 1px solid rgb(220, 221, 223); clear: none; margin: 6px 0px 15px 18px; padding: 15px; width: 282.5px; float: right; color: rgb(0, 0, 0); font-size: 16px;">[h=1]2018 MLB Home Run Derby[/h]
Bracket & facts »
</aside>Recently, in a discussion, I was asked "Dan, can you predict a Home Run Derby?" My first answer was an extremely helpful "Dunno," but it got me thinking if we could predict a Home Run Derby, using both the matchups and results. We don't have a lot of data, but modeling these things always gives an interesting glimpse into the inner workings of things.
So, I found variables for the three most recent Home Run Derbys -- I'd love more years, but the formats shift a lot and I wanted to see first if Statcast data would be helpful -- and started from there. A few variables, some surprising, some not, came up as useful predictors of Derby performance. Sixteen of the 21 matchups from 2015-2017 were won by the player with the higher average exit velocity and the margin tended to be correlated with their difference in the rankings. Also helpful were things like home runs-per-ball hit, and even recent performance seemed to have more predictive value in a Derby than in real life.
I'll spare the nitty-gritty ins-and-outs of dimensionality reduction and go right to the results, plugged in for this year's Home Run Derby, matchup by matchup.
<offer style="box-sizing: border-box;"></offer>
[h=2]Round 1[/h]
No. 1 Jesus Aguilar (59 percent) over No. 8 Rhys Hoskins (41 percent)
Hoskins is coming on lately, with seven home runs over the past 28 days after only six total for April and May. But Hoskins is just barely in the top 100 for average FB/LD velocity (fly ball and line drive) and rate of "barrels." For those not familiar with barrels, it means hits that have the exit velocity and launch angle that average at least a .500 batting average and 1.500 slugging percentage.
No. 5 Kyle Schwarber (61 percent) over No. 4 Alex Bregman (39 percent)
Jonah Keri didn't coin the Super Nintendo nickname for Schwarber for no reason. Schwarber has the second-most barrels of the eight contestants, behind just Max Muncy, as a percentage of batted balls hit. This is the year. Bregman has advanced to be a true superstar, but in terms of raw power, Schwarber has the edge.
No. 7 Freddie Freeman (55 percent) over No. 2 Bryce Harper (45 percent)
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[h=2]2018 Home Run Derby: Bracket and other top things to know[/h]From Washington's homegrown superstar to a pair of Cubs teammates, here's what you need to know about the field that will be swinging for the fences at Nationals Park.
- [h=2]Aguilar, Harper, Muncy highlight HR Derby field[/h]Milwaukee Brewers first baseman Jesus Aguilar leads seven first-time participants in this year's Home Run Derby, which will be contested Monday at Nationals Park. The newcomers will be joined by Washington outfielder Bryce Harper, the No. 2 seed.
- [h=2]When Futures Game prospects will become MLB All-Stars[/h]All-Star Week's prospect showcase provides a peek at some of baseball's phenoms. When will they be back for the main event?
No. 3 Max Muncy (67 percent) over No. 6 Javier Baez (33 percent)
As unlikely as Muncy's emergence has been in 2018, it's hard to say from his Statcast data that the power isn't real. When it comes to the barrel rate, Muncy is third in baseball among all players with at least 100 batted ball events, behind just two others known for raw power (Joey Gallo and J.D. Martinez) and edging out Eric Thames, Matt Davidson and Aaron Judge.
[h=2]Round 2[/h]
Aguilar (53 percent ) over Schwarber (47 percent)
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</article>Aguilar's run, which has seen him hit 14 home runs in his most recent 32 games, is enough to just squeeze over Schwarber in the projections here. It's close, though -- Aguilar may have more homers, but Schwarber's fly balls and line drives have more velocity.
Muncy (66 percent) over Freeman (34 percent)
Freeman is projected to beat Harper in the first round, but Freeman's offensive value is still more of the all-around type than simple raw power. Muncy pretty much sweeps the Statcast data, and while I would happily trade Muncy for Freeman in real life, M-squared has the edge.
[h=2]Finals[/h]
Muncy (55 percent) over Aguilar (45 percent)