Fastball or Cutter? How to Classify a Pitch | Dr. Adam Maloof of Princeton

In this week's podcast, I sit down again with Dr. Adam Maloof, Princeton professor of Geosciences and athletics fellow for the baseball team.This time he’s tackling one of the most overlooked problems in baseball analytics: pitch classification.If you’ve ever looked at a scouting report and thought, “This guy doesn’t throw seven pitches,” you’re not alone. Dr. Maloof explains why existing pitch tagging data from popular systems (TrackMan, Synergy, and MLB’s StatCast) are often inconsistent, inaccurate, and difficult to use for data analysis.Together, we discuss:Why MLB’s pitch classifier is trained on what pitchers call their own pitches (and why that’s a problem for hitters and analysts)How Dr. Maloof analyzed nearly 5 million college pitches using a “blank slate” approach inspired by geologyThe “color wheel” analogy: why pitches within a category (fastballs, breaking balls, changeups) exist on a continuous spectrum with no natural boundariesHow Princeton’s staff uses reclassified data for scouting, pitch design, and pitching machine programmingPitch tunneling: what it is, how they measure it, and how they’re teaching it to pitchersThe role of arm slot, biometrics, and what’s next for this researchRead Dr. Maloof's article on pitch tagging: How to Classify a Pitchhttps://medium.com/sabr-tooth-tigers/how-to-classify-a-pitch-a4805ce35082Connect with Patrick Jones Baseball:On X: @pjonesbaseball📬 Sign up for the Recruiting Times, my weekly baseball recruiting newsletter – Get insights on college recruiting, player spotlights, and advice for parents and coaches.https://www.patrickjonesbaseball.com/blog⚾ Need help with college recruiting? – We help serious baseball players get recruited. Book a 1-on-1 consult.https://www.patrickjonesbaseball.com/recruiting Hosted on Acast. See acast.com/privacy for more information.