[Fastbreak Data] Using Machine Learning to Find the 8 Types of Players in the NBA

Alex Cheng is Founder of Fastbreak Data and a guest contributor for Ball and One. Follow his work at fastbreakdata.com.


Using machine learning, my goal is to uncover the positions that are intrinsic to today’s NBA players and classify players with a position that best encapsulates their skill sets.

Inspired by the topological data analysis of Muthu Alagappan in “From 5 to 13: Redefining the Positions in Basketball” and the “Periodic Table of NBA Elements” by Stephen Shea in Basketball Analytics: Spatial Tracking, this study proposes an alternative method in which to classify players in today’s NBA….

Click the image below to read the full article. Or you can click here to read it on my blog, Fastbreak Data.

Click on the image above to view the full article at fastbreakdata.com

Author: Alex Cheng

A basketball nerd with Front Office dreams. Combining data science and basketball, I want to design revolutionary offensive and defensive schemes in the NBA.