Visualizing Kluber's 18 K's in Python

Using a pitch's start and end location, as well as initial velocity and acceleration, we can extrapolate the complete path of a pitched ball in three dimensions.

By Daniel Meyer May 19, 2015, 5:05pm EDT

Cory Kluber strikes out Peter Bourjos with a slider, sinker, curveball, fastball sequence.

Since debuting in late 2006, PITCHf/x data has become an integral part of our consumption of baseball. PITCHf/x opens the doors to analysis that was previously not possible in an objective manner, but it can also enhance our enjoyment of the game we love.

I am proud to unveil the final product of my Data Visualization and Analysis course at Colby College. In partnership with Ian Tibbetts '15, we have modified our semester work to create an application with the specialized purpose of viewing and animating PITCHf/x pitch trajectories. Previous applications such as MLB Gameday allow the user to view the trajectory of a pitched ball from a fixed angle. Our application allows the user to view any pitch or set of pitches from PITCHf/x archives in three-dimensions with full ability to pan, zoom, and rotate making it a truly novel way to enjoy the filthiest pitches of your choice.

Without further ado, submitted for your enjoyment, Cory Kluber’s 18-strikeout masterpiece.

1. Kolton Wong swinging on a fastball up in the zone.