# Exceptionally Well Hit Fly Balls And Home Run Surges

A few weeks ago I delved into the ideal launch angle and exit velocities for home runs, and I discovered balls hit between 21 and 36 degrees vertically and equal to or greater than 96 mph have wound up as home runs nearly half of the time (46.9% to be exact). This was initially somewhat surprising, this seems like a pretty large range of values, but after reflection it seems to check out. When you hit the ball 96 mph in a general upwards sort of trajectory, you’re giving it a ride.

I have spent the past few days playing around with this data to see if it can highlight any more players who may be trending upward or downward with these sort of ideally hit balls, and I have created a few very simple metrics along the way, all of which will be in an attached spreadsheet. You’ll see average exit velocities and batted ball distances for all balls in play along with pushed/pulled splits. I did this again for all batted balls that fit into this ideal launch window, 21-36 degrees and 96+ mph. I have counted how many home runs a player has hit, and how many of those home runs were hit ideally. Finally, I have found the ratio of ideally hit home runs to home runs.

I’m running on the assumption that these ideally hit balls are much less reliant on park and game factors, and instead more representative of a player’s ability to make extraordinary contact on what are, more than likely, pitcher mistakes. Whether this is a true repeatable skill, I don’t know, that is an area to look into. For now, I’m rolling with this assumption, because it might get us somewhere interesting.

With this data, I’ve sorted by the year to year delta for some of these stats. Namely, the ideally hit home run to home run ratio, the exit velocity on ideally balls, and the distance of ideally hit balls. I also eliminated anyone with fewer than 15 home runs, since they probably aren’t particularly interesting for this sort of analysis. In the following table you’ll see a list of the players who have drops in all three of these metrics while also sporting an increased home run total. Before you read this chart, keep in mind the stats that begin with “id” represent the ideally hit balls, ie 96+ mph, 21-36 degree vertical launch angle. So, for example, idFB represents the number of ideally hit fly balls. idEV, is the average exit velocity for ideally hit balls, etc. The delta columns, which I have labeled in orange, represent the change from 2015. Negative delta means the stats decreased in 2016.

Batters With Weaker Ideally Hit Balls
Name PA idFB Avg Dist Avg idDist Delta Dist Avg EV Avg idEV Delta EV HR idHR Delta idHR/HR
Adam Duvall 603 51 237.65 385.94 -4.1 89.1141 101.7431 -1.0 33 26 -.212
Adam Jones 653 43 227.31 387.13 -8.9 89.4028 101.9235 -.3 29 19 -.123
Alex Gordon 482 28 231.31 380.35 -13.3 88.4888 101.3529 -1.3 16 13 -.034
Andrew McCutchen 673 42 233.59 383.69 -1.5 90.2032 101.0088 -.9 24 18 -.120
Brandon Drury 498 23 213.87 385.28 -15.7 89.9207 101.1287 -.9 16 11 -.313
Eric Hosmer 630 29 210.54 388.55 -8.3 93.424 101.4624 -2.9 21 14 -.157
Ian Desmond 662 33 205.36 391.36 -17.0 91.3316 102.9797 -1.8 21 16 -.028
Jedd Gyorko 438 37 227.84 387.41 -1.4 88.1813 101.9078 -.1 30 25 -.104
Jefry Marte 279 18 216.6 400.86 -5.5 89.8183 102.8544 -2.1 15 13 -.133
Joey Votto 677 51 226.72 375.32 -3.9 89.8081 101.2161 -1.3 29 23 -.103
Jonathan Villar 678 28 205.78 385.46 -32.4 91.0238 101.7629 -7.2 19 16 -.158
Jung Ho Kang 363 23 224.45 400.12 -5.4 90.8875 102.7861 -1.5 21 15 -.286
Kyle Seager 663 54 236.66 379.6 -6.2 90.8921 100.2774 -.4 30 23 -.103
Odubel Herrera 647 25 215.09 383.51 -11.0 88.4535 100.4044 -.9 15 11 -.142
Travis Shaw 518 25 228.24 391.22 -6.8 89.389 102.9052 -.2 16 13 -.021
Wil Myers 672 41 222.4 385.03 -19.0 89.1052 101.6722 -.2 28 22 -.214
id= ideally hit ie 96+ mph, 21-36 degree vertical launch angle
delta = 2016 minus, negative delta means 2016 stats were lower than 2015

Guys in this chart are those who saw increases in home run production while decreases in overall ideally hit ball quality. Notice, none of these ideally hit balls are pop ups or ground balls. These are very hard hit line drives and fly balls which a 46.9% chance of being a home run. This is nothing to sneeze at. Drops in performance on these balls should suggest, I think, anyway, a drop in real overall performance at the top end of the quality of contact.

Jung ho Kang pops out of this list as a guy I’m personally worried about. He had a strong funk in the middle of 2016, which included temporarily losing his everyday starting role. There were on and off the field problems leading up to that point, but here we see a significant drop in this ideally hit ball performance. He lost 1.5 mph exit velocity, which is enormous, which translated to around 5 fewer feet on those batted balls. Generally speaking, 1.5 mph would equate to much more than only five feet, so there are other factors at play, such as slight variations in launch angle to make up the lower velocity. However, the real eye opener here is the shift in ideally hit home runs to non-ideally hit home runs. I’m not sure to what extent ideally hit home runs matter in the grand scheme of things, but his xHR rate for 2016 was only 15.6, and drops to 14.8 when adjusted with park factors, compared to the 21 he registered in game so you see again a similar potential issue with his power.

Wil Myers saw a huge surge in home runs in 2016, jumping from 8 in 253 PA in 2015 to 28 in 676 PA in 2016. He also saw a 19 foot drop in average fly ball distance on ideally hit fly balls. This might be a bit misleading, since he also had an up tick in ideally hit balls in general, in addition to his much larger sum of plate appearances. His 2015 totals may have been unduly influenced by statistical noise, so maybe we can ignore some of this. However, his xHR for 2016 was only 24.5, 3.5 fewer than his registered total of 28. If I apply park factors to his xHR, that drops to 23.8 homers, an even larger difference. It seems likely that a large degree of his home run increase is sustainable, while a significant portion may not be. Perhaps it would be more realistic to expect 25 from him next season than the 30 you may be tempted to assume.

Enough of the negativity, though, let’s take a peek at players who maybe perhaps have more sustainable power surges in 2016.

Batters With Stronger Ideally Hit Balls
Name PA idFB Avg Dist Avg idDist Delta Dist Avg EV Avg idEV Delta EV HR idHR Delta idHR/HR
Matt Adams 326 21 256.1 403.8 22.5 90.4 102.3 1.8 16 13 .213
Eugenio Suarez 623 31 222.7 382.8 6.4 87.0 102.0 .9 21 19 .212
Yasmany Tomas 563 41 231.7 398.4 14.8 91.4 102.3 1.8 31 27 .204
Troy Tulowitzki 530 45 228.6 380.0 6.1 91.0 102.0 .9 23 20 .185
Evan Longoria 669 65 243.4 395.0 15.2 91.8 102.1 .5 36 33 .167
Neil Walker 458 32 232.4 386.2 1.6 89.5 101.9 1.8 23 21 .163
Edwin Encarnacion 687 48 224.8 402.5 9.2 91.5 104.6 1.4 42 32 .162
Charlie Blackmon 632 36 233.5 394.8 17.2 88.1 101.9 2.2 29 23 .146
Justin Upton 581 32 233.8 405.4 26.8 92.3 105.1 2.6 28 18 .143
Kendrys Morales 581 53 238.4 393.7 2.4 94.1 102.9 .3 28 26 .129
Jake Lamb 595 34 235.0 406.4 18.1 92.3 103.0 1.6 29 23 .126
Melvin Upton 538 29 213.8 389.6 18.8 88.5 102.3 .1 20 18 .100
Cameron Rupp 409 23 217.8 395.0 13.7 92.3 104.3 2.5 16 14 .097
Carlos Beltran 579 33 220.4 387.9 4.4 90.9 101.1 1.0 29 21 .093
Gregory Polanco 588 22 224.8 390.8 9.5 90.7 101.5 1.3 22 14 .081
Mark Trumbo 658 48 233.4 399.7 5.9 93.9 104.6 .7 47 33 .066
Yasmani Grandal 455 29 232.7 399.4 11.5 92.2 103.4 1.1 27 22 .065
Victor Martinez 577 49 231.7 381.7 9.6 91.1 100.5 .6 27 20 .041
Marcus Semien 608 35 227.7 391.2 12.2 88.2 101.0 1.2 27 22 .029
Rougned Odor 619 43 226.6 396.2 3.9 90.5 102.5 .7 33 26 .023
Zack Cozart 508 23 214.0 384.5 3.8 86.4 99.4 1.4 16 11 .021
Steven Souza 465 20 223.0 385.9 8.7 90.3 103.8 1.1 17 13 .015
Brian Dozier 672 53 223.8 389.6 16.5 88.8 101.3 1.2 40 34 .010
Jason Kipnis 643 46 231.1 382.6 16.0 90.6 100.3 .6 23 18 .005
Kris Bryant 678 47 237.3 391.6 14.0 89.8 104.0 .2 39 28 .004
id= ideally hit ie 96+ mph, 21-36 degree vertical launch angle
delta = 2016 minus, negative delta means 2016 stats were lower than 2015

If you’ve followed me, or perhaps ever looked at this player’s fangraphs page, you’ll probably have a small twinkle in your eye for Cameron Rupp landing on this list. No, I didn’t rig it. I promised to stop writing about him, because it started to feel weird. But man, I can’t help it. He had a great season, and he was underrated. If you picked him up in May, good for you! He fell off towards the end of the season, but for a solid 2-3 months stretch he was a very valuable catcher, and just barely missed out landing in the top 100 position players of 2016 in fantasy baseball. Raise your hand if you predicted that last March! (my hand isn’t raised, but I do have a big smile). Getting to the stats though, he had 2.5 mph increase on his ideally hit balls, and as I’ve written previously, I do feel it is sustainable. With this exit velocity increase he saw a roughly 14 foot increase on his average ideal fly ball distance, and 14 of his 16 homers were ideally hit. Swoon.

Justin Upton had a rough season at the plate, no doubt about it, but his ideally hit stats make you wonder if that was more about bat luck more than anything else. Not only these ideally hit stuff, but all of his statcast data in general. You see here that he had a 2.6 mph increase in ideally hit balls, along with nearly 27 extra feet on ideally hit fly balls. Not pictured, he went from 5% ideal hits in 2015 to 5.5% in 2016. So, he had more ideal hits, those ideal hits were hit harder and farther and to top it off he hit more home runs with them to boot. When I tell you that, it seems particularly odd that he would also, simultaneously, have such a weak season, at least by his standards. It should bode well for Tigers fans, though. He doesn’t appear to have lost much, if anything he appears to be getting better. I can point to how his xOBA in 2016 came out to .343, above the .336 xOBA he had in 2015 almost identical to his .340 wOBA in 2015. Watch out for him in 2017, he should slide right back into the same production you saw prior to 2016 as if nothing happened.

Semien, Walker, Lamb, Blackmon.  All these guys had significant increases in exit velocity on ideally hit balls.  Looking up and down this list you see 10+ foot increases on these batted balls left and right.  These guys all increased their rates of exceptionally well struck balls in 2016.  Again, I don’t know how sustainable some of this stuff may be, I’m only trying to offer a slightly different lens for looking at some of these players.  Take everything with a grain of salt!

Some special mentions from this list: You see Encarnacion sitting happily on the improved players list.  You may be sad to hear Jose Bautista is sitting on the opposite end of the spectrum.  Not quite bad enough to make the cut for the naughty list, but significant drop in performance nonetheless.  A lot of the people on the naughty list don’t seem perhaps as bad off as the list may imply.  A few are jumping from rookie or otherwise limited seasons to full season play, so the change in sample size may be a big factor.  Others, like Joey Votto, seem to have refocused their approach at the plate.  Votto especially, he appears more fixated on contact than selling out for hard contact.  Which is a good thing overall.  Perhaps not the best thing for fantasy, though, and seeing this sort of change in his stats may be a sign that his approach is working.  That feels weird to say.  I mean, he had no drop in actual home runs, so it is probably a lot to do about nothing.

It may be that drops in hard hit contact are subtle and nuanced, whereas increases are more bold and aggressive.  For example, seeing the changes in Rupp were very easy as early as mid to late April.  His exit velocity was through the charts, his launch angles were dramatically improved, on and on down the list.  With statcast, and xStats, finding those guys might be a tad easier, but identifying guys who are getting weaker over time may need a bit more tweaking.

We hoped you liked reading Exceptionally Well Hit Fly Balls And Home Run Surges by Andrew Perpetua!

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Andrew Perpetua is the creator of CitiFieldHR.com and xStats.org, and plays around with Statcast data for fun. Follow him on Twitter @AndrewPerpetua.

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johnsnot20

I’m surprised at no Khris Davis on this list. I was digging around statcast the other day and he was 3rd behind Miggy and Nelson Cruz in crushed barrels%. Isn’t barrel% pretty similar to what you’re doing here?