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Since reading @enosarris' article about MLB deadening the ball in 2021, I've done some work exploring who this (likely) impacts the most. I won't bury the lede by describing the method up front, let's start with the juicy stuff: From left to right, the 30 greatest HR reductions.
Here's every player (min 10 HRs). Horizontal axis shows total expected HRs lost, while vertical axis shows proportion of HRs lost. As you can see, guys with high HR/FB% are more resilient to a deadened ball, so the effect is not uniformly distributed.
Speaking of the effect not being evenly distributed, which BBEs are most affected? The model takes exit velocity, launch angle and spray angle as predictor variables, but we'll just visualize EV and LA (two most important). The more red, the greater the impact a deadened ball has
Let's take that same plot but overlay every home run from 2019-2020. Each HR is a dot. As you can see, the vast majority of HRs are impacted, many see a reduction > 10% (roughly what 3 ft of deadening will impart). Again, some players are more in the "reduction zone" than others.
The EV/LA map isn't perfectly representative, as it changes with different spray angles. Pull hitters are less impacted by a deadened ball. So not only are some players hitting the ball so hard they aren't impacted by a deadened ball, but some also pull efficiently.
One player that sticks out is Mookie Betts. Mookie does pull the ball, but he pulls less often than you'd think. Here's his LA/EV map overlayed with each home run and a vector indicating spray angle - left to left field, right to right field. I love this representations, bty.
Another is Nick Castellanos, and you can see why. So many of his HRs were in the impacted region. He's also not really a pull hitter and a lot of those center field HRs would simply land in the warning track.
Like I said, the map isn't perfect. You might think Nelson Cruz is resilient to a deadened ball. I mean, he hits so many balls so hard, they're out of the danger zone, right? The thing is, he hits so many balls straight away to center, he's elongating his own danger zone.
The next question is obvious: Which teams are most impacted by a deadened ball? I ran out of time to examine this today, but I'll get to it ASAP.
Also, for those interested: the model is fairly simple. It's a GAM taking exit velocity, launch angle, spray angle as predictor variables, and HRs as response variable with binomial distribution. Training was conditional on LA > 0 deg, EV > 80 mph.
