in order to quantify tunnelling, you need some kind of model to know just based on plain singular pitch data how good a pitch is. and after some headbashing, i threw together a xgbclassifier pitch quality model (here's 2023's best pitches)
in order to quantify tunnelling, you need some kind of model to know just based on plain singular pitch data how good a pitch is. and after some headbashing, i threw together a xgbclassifier pitch quality model (here's 2023's best pitches)
a hitter (or theoretical machine learning powered hitter) can predict final plate x (r2 = .78) and final plate z (r2 = .94) just from ball flight positions within the first 15 feet decently well (30 feet was too well)
a hitter (or theoretical machine learning powered hitter) can predict final plate x (r2 = .78) and final plate z (r2 = .94) just from ball flight positions within the first 15 feet decently well (30 feet was too well)