Can New Data on Launch Angles and Exit Velocities Predict Future Results? Introducing xSLGBB
he other day, I explored the slow start of Minnesota Twins slugger Miguel Sano and I used a chart that outlined, as a percentage, how many home runs we would expect a player to have based solely on a hitter’s homer rate as it related to hard hit balls. The article is pretty good and you should definitely go read it if you care at all about me or Miguel Sano or climate change, but the mathy bits that I glossed over were arguably even more interesting than Mr. Sano. (Editor’s Note: I don’t think there’s any climate change stuff in the Miguel Sano piece, but it’s super important. After you read this go google some stuff about the transition to a low carbon, climate resilient economy. )
Can we use Statcast data to predict how lucky a hitter has been given their exit velocities and launch angles? What I’m working towards is something like the following:
The Set of Launch Angles and Exit Velocities = An expected number of Total Bases
Those two variables sure seem like they should predict something, and we’ve never had access to this granularity of statistical detail before. The set of launch angles and exit velocities should yield some insight into how lucky/unlucky a player has been. A batter can control little else than how hard and at what angle he hits a ball. With the idea that the baseball gods even everything out eventually, that level of knowledge should allow us to predict marginal breakouts that make all the difference.
The attempt here is to normalize those annoying defensive anomalies. How many flyouts should have been doubles, or even homers? How many line drives could have been triples if they were hit 5 feet further from a defender? That 390 foot blast that hit off the right-center wall at Turner Field for a double would have been a homer if only slugged in any of the other 29 parks. Or even if a batterbarely mishit a ball and it turned into one of those really high, really not so deep, yet really exciting flyouts (like what Bryce Harper did to Jose Fernandez earlier this year).
I’ll present a few graphs and then propose a new stat. The graphs are intended to prove to you that there are trends here. While there are roughly a bajillion variables at play here, I’m just trying to sift through the physics noise and bring some of what you care about.
To continue reading, including a link to the full leaderboard, visit the post about Slugging Percentage on Batted Balls