SportVu Analysis

This post shares some of the code that I have created for analyzing NBA SportVu data. For background, the NBA SportVu data is motion data for basketball and players taken 25 times a second. For a typical NBA game, this means about 2 million rows of data. The data for over 600 NBA games (first half of the 2015–2016 season) is available. This is over a billion rows of telematics (iOT) type data. This is a gold mine and here are some early pieces from studying that data.

The first is basic EDA on the movement data. This code allows you to start analyzing the ball and player movement.

The next markdown, PBP, shows how to merge play-by-play data with the SportVu movement data. This allows using the annotated data which contains information on the type of play, score, and home/visitor info.

The next set of documents start analyzing the data. The first measures player spacing using convex hulls. The next shows how to calculate player velocity, acceleration, and jerk. (I really wanted to do a post on the biggest jerk in the NBA, but unfortunately, the jerk data is way too noisy.)

The third document offers a few different ways of analyzing player and ball trajectories.

You can find all these files at my SportVu Github repo.

Originally published at http://projects.rajivshah.com on April 2, 2016.