NBA Analytics With Python: A Tutorial

by Gene Li

 

Students just getting into the world of sports analytics have a lot of questions, and this guide will serve as a starting point for understanding the big picture overview of the data science process for getting data, processing it, visualizing it, and applying interesting learning models to it.

While this guide was originally written with NBA analytics in mind, it is a good resource for other areas of sport analysis.

Any questions, comments, or suggestions can be directed toward the author at gxli@princeton.edu.

See guide here: https://gxli97.github.io/

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