The Home Run Conundrum, Part II: Less Is More

In Part I, one of the major observations was that a group of smaller-statured players seemed to be using backspin as a distance tool. I was curious how the increase in home runs would look when broken down by physical size. In addition to using Statcast data from Baseball Savant, I downloaded player heights and weights from MLB rosters and created size quintiles. While I expected to see significant contribution from smaller-sized players, the magnitude of what is occurring was quite surprising:

Size Quintile Home Runs
 (1= smallest) 2015 2016 Change
1 410 522 112
2 714 1,025 311
3 1,036 1,132 96
4 1,277 1,420 143
5 1,469 1,512 43
Totals 4,906 5,611 705

Note: Size based on height * weight. Since pitchers skewed the quintiles due to their above-average size, they were excluded in making the quintile groups; however, their HRs are included in order to tie back to HR totals.

Now that is democratization of power! While interesting, the obvious question is: How are the smaller players hitting all the additional home runs? Is it more distance through exit velocity (EV) and/or launch angle (LA), more pulled balls, more fly balls, or just better-hit fly balls? Let’s take a look:

Distance, EV and LA

Change from 2015 to 2016
Balls Hit >=90 MPH, >=15 Deg.
Quintile EV (MPH) LA Distance (ft)
1 0.08 -0.09 -0.96
2 0.26 0.32 2.99
3 0.54 -0.56 3.75
4 0.44 0.16 3.88
5 0.58 0.46 3.06

Note: Balls hit at Coors Field excluded

Although the data above would support a slight increase in homers overall, there is no smoking gun as to what might be happening within the smaller player groups. If smaller players are not hitting the ball that much harder or further, maybe it could be that they are hitting more homers to the pull side.

Pulled HR and Hits

Pulled Home Runs Change and Mix
Quintile            Change 2015 2016
1                   63 85% 78%
2                242 77% 77%
3                   69 77% 77%
4                153 68% 71%
5                   18 65% 64%
Total/Avg                545 71.8% 72.2%

Although the location mix of homers did not change significantly from the prior year, smaller players in both years hit a much higher percentage of their homers to the pull side than average. The more important metric to consider with respect with the pull factor is what is happening to the mix of well-hit fly balls.

            Pulled Balls Hit >=90 MPH And >=15 Deg
Quintile 2015 2016 Change
1 35.7% 36.2% 0.5%
2 36.3% 38.4% 2.1%
3 38.1% 40.3% 2.2%
4 35.0% 37.0% 2.0%
5 35.6% 36.7% 1.1%

Again, more data supporting a slight overall increase in homers – More well-hit fly balls hit to the pull side and more of those balls going for homers. No real support here for what might be happening with the smaller players. What about well-hit fly balls in general:

Size Quintile Well Hit Fly Balls >=90 MPH + >=15 Deg.)
 (1= smallest) Change % Change
1 442 16%
2 881 22%
3 -175 -3%
4 66 1%
5 13 0%

Now we’re getting somewhere! Smaller players experienced a significant increase in well-hit fly balls in 2016. What about fly balls in general, not just those of the well-hit variety:

Change in Total Fly Balls

2015 – 2016

Quintile Change % Chng
1 385 10.4%
2 979 20.5%
3 -146 -2.5%
4 127 2.1%
5 199 3.4%

The last two charts kind of sum it up – smaller players are hitting more fly balls in general as well as more well-hit fly balls that are going for homers. Before closing, I’d like to show two other tables which I believe are meaningful for both the home-run question as well as hitting in general. In a certain respect, it appears hitters are making better contact. The following chart shows the volatility (via standard deviation) for EV, LA, and Distance.

Changes in Volatility
Changes in Std. Dev.    2015-2016
Quintile EV LA Distance
1 -0.65 0.18 -5.44
2 -0.31 0.60 -4.56
3 -0.36 0.46 -5.22
4 -0.21 0.56 -5.77
5 -0.18 0.67 -5.43

Since EV is up in terms of MPH but down in terms of volatility, this would indicate players in general are making better contact. The same is true for distance – higher average distance but lower volatility. However, the increase in volatility of launch angle would seem to indicate quite the opposite – that players are using a lower ball-contact point in order to achieve the higher number of fly balls. Take a look at pop-ups over the past two seasons:

Change in Pop-Ups
Quintile Change % Chng
1 59 4.9%
2 211 13.7%
3 -34 -1.8%
4 41 2.2%
5 -8 -0.4%

While not up across the board, it is very interesting that there is a significant increase in pop-ups in the group responsible for the largest increase in homers.

After considering the data above, I was curious how the homers looked broken down by age. The increase in homers of the younger players was equally surprising:

         HR Breakdown By Age
Age 2015 2016 Change
21-23 125 285 160
24-26 905 1,474 569
27-29 1,321 1,352 31
>=30 2,555 2,500 -55

I checked for the obvious relationship between size and age; however, the 24-26 age group was reasonably well distributed in terms of size so there is likely something additional going on with the younger players. Whether it is a power focus earlier in their development, a selection bias through the draft or some other factor I’m not sure. Maybe I’ll get into that another time.


This is a very interesting issue to consider and while I’m sure there will be much more written on the topic, it certainly takes some possibilities such as a juiced ball completely out of consideration. Now that would be a conspiracy! That umpires are throwing out juiced balls for the little guys! Except that the balls would have to be so stealthy that they don’t get hit significantly harder or further – they just hit bats of the smaller players for well-hit fly balls more often.

For me, the really interesting part is the underpinning driver – that advanced metrics have changed the market which values the players. Whether consciously or not, players are changing to align with the market to maximize their value. Even more interesting is what the future holds – what is the cost of the hyper-focus on power and loft and what are the unintended consequences that have yet to come to light?  As far as the home-run issue, at least in terms of player size and age, less certainly has been more.

D.K. Willardson enjoys research connecting data, mechanics, and technology and is the author of Quantitative Hitting: Surprising Discoveries of the Game’s Best Hitters. He is also the developer of the Quant Tee and SwingGraphs.

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