The Numbers Behind America’s Pastime // USC MS Business Analytics // USC Baseball Team Data Analyst // Former @FirebirdsCCBL Analytics (not affiliated w CCBL)
Ryan Bourassa of @FirebirdsCCBL has one of the nastiest pitches on the Cape
His splitter boasts some absurd numbers:
- .091 BAA, 50% whiff rate
- 800 avg RPM, minimum 640
- 3rd lowest spin score of any pitch in the league (high velo, low spin)
@ryan_bourassa10@GoJacksBaseball
Using batted ball data from savant, we can work to predict whether a ball in play will be a hit/out. Maybe cooler, we can work to predict the exact value we can expect from a batted ball, more on that later. For now, I made a bot that predicts Hit / Out. Check it out below:
As I finish up the xRV model, I wanted to work on some hitting data for fun. I’ll continue to update my code as I begin to include park factors and fine tune my xBA model.
https://t.co/kfmHpo18DE
I'm thrilled to share I've accepted a broadcast/media relations position with the @GoStripers (Braves AAA) for the 2023 season. Special thanks to @DaveLezotte for the opportunity.
Excited to get started! #TakeTheBait
Now, if you'll excuse me, I have a midnight train to catch.
@Johnny_Davis12@RylanDomingues@ckessinger44 I remember looking at some of the Trackman files thinking the numbers looked a little inflated, particularly Wareham home games. The rest of the machines seemed to produce accurate numbers.