The Unexplained Home Runs

On Saturday and Sunday I attended my first Saber Seminar, along with a number of other members of the FanGraphs team. It was a great weekend and Dan Brooks and Chuck Korb were excellent hosts and organizers. In a department of chemistry lecture hall on the campus of Boston University, a space where periodic tables flanked the stage, we saw a number of interesting research presentations.

One of the lectures I was most interested in attending was one of dealing with the physical sciences, a presentation by Dr. Alan Nathan, who has of course become a superstar in the field of baseball analysis and research. It is Nathan who, along with others, has helped writers like Ben Lindbergh and Rob Arthur investigate whether the ball is juiced.

Much has been written here and elsewhere about the home run surge that began in the summer of 2015 and has shown no signs of waning, but rather keeps increasing. In part due to the suddenness of the game changing from an extreme run prevention environment to an extreme power environment, it sure seems like the ball has something to do with it — if it was not the primary culprit. Whether MLB and Rawlings are consciously or inadvertently altering the ball — and it would seem like it would have to be a material (and/or size) change since the major league ball is hand-stitched — the ball is playing differently.

But while Nathan has assisted in other research, I was curious to learn the findings of his own study, which he presented at Saber Seminar. I am not going to focus too much on the details or process of Nathan’s study. He may publish an in-depth piece soon himself for those who could not attend his talk. Instead, I want to focus on one aspect of the presentation: the unanswered question — the home runs that the ball cannot account for.

I will share some background of his study. Nathan’s data was taken from games played at Tropicana Field, which is the most pristine testing environment in the majors as it rests at sea level and is of course a climate-controlled dome. Nathan also was only studying balls hit there over a three-year period that had a 90 mph or faster exit velocity and launch angles between 25 and 30 degrees. In other words, Nathan was concerned with balls most likely to become home runs.

(Edit: Nathan was studying how the ball carries from year to year. COR was not studied).

I shot the following photos of the presentation with an iPhone 7:

What Nathan found was that the ball did change, it had less drag, in comparing 2015 to 2016. But what was most interesting to me is the ball has apparently not changed from 2016 to 2017.

But HR/FB rates continue to increase — 13.7% this season compared to 12.8% in 2016 — even as the ball is playing similarly in 2017 compared to 2016, according to Nathan’s research. We can deduce there are reasons behind the spike.

I’m convinced beyond a reasonable doubt that the ball has a role in this surge and perhaps even a leading one, but there are more elements involved and that was a takeaway, for me, from the presentation.

And the other missing variable I strongly suspect continues to be those joining a growing band of air-ball revolutionaries, which can have strong convictions in their swing plane changes thanks to the data tools now available. While pitchers and defenses first enjoyed data-based advantages to understand their own performance and influence strategy, hitters can now easily understand and quantify launch angles and exit velocities, thanks to Statcast and similar tools.

After all, it was not until heat maps based and batted-ball data were widely available — hard evidence in easily digestible forms — that many coaches and players accepted the findings and began to play defense in non-traditional ways. It was not until then that shifts proliferated throughout the game. It was data that reinforced belief with defensive positioning, and I suspect it is doing something similar with hitting.

This is a fun subject for me, and for many us, because there is science involved, but also an element of mystery. And what Nathan, I think, demonstrates is there is not one smoking gun explaining the surge, but multiple smoking guns.

The ball is juiced, hitters are launching more of them into the air, and their unconventional approaches and practices are being backed by hard evidence from Statcast.

The ball is perhaps no longer changing, but perhaps hitters are.

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A Cleveland native, FanGraphs writer Travis Sawchik is the author of the New York Times bestselling book, Big Data Baseball. He also contributes to The Athletic Cleveland, and has written for the Pittsburgh Tribune-Review, among other outlets. Follow him on Twitter @Travis_Sawchik.

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I imagine some, if not all of the continued surge has been cohort replacement, as the upside to pull-heavy three-true-outcomes hitters increased in the juiced ball era at the cost of contact-heavy spray types. When more balls go out, the average value of attempting to pull a ball in the air (at the cost of striking out more) increases and the average value of simply putting the ball in play decreases.

I think if you look at changes hitters have made, rookies coming into the league or who is receiving playing time in positional battles, the pull-heavy power hitters are on top in all three areas. Once the ball was changed, teams have been responding to the new incentives by acquiring and playing players who fit the new ball, driving the game further in that direction.


Yeah this is my thinking as well. More power hitters combined with the noted propensity for most/all hitters to increasingly swing for the fences, results in HR/FB not really being comparable over time. It’s not like it’s some magic number that numbers must revert to – strength, effort and swing plane (which could quite possibly involve more efficient and powerful biomechanics, especially if you watch Josh Donaldson talk) are not measured by it.

I’d love to see a plot of HR/FB rates over time vs strike outs, exit velocity and/or launch angle (or some single batted ball metric that combines probability of a home run). Hell, even average player weight would be interesting to look at. I think those would show a partial explanation for this.