Predicting National Basketball Association Success: A Machine Learning Approach

Authors

Adarsh Kannan, Southern Methodist UniversityFollow
Brian Kolovich, Southern Methodist UniversityFollow
Brandon Lawrence, Southern Methodist UniversityFollow
Sohail Rafiqi, Southern Methodist UniversityFollow

Abstract

In this paper, we present a machine learning based approach to projecting the success of National Basketball Association (NBA) draft prospects. With the proliferation of data, analytics have increasingly be- come a critical component in the assessment of professional and collegiate basketball players. We leverage player biometric data, college statistics, draft selection order, and positional breakdown as modelling features in our prediction algorithms. We found that a player's draft pick and their college statistics are the best predictors of their longevity in the National Basketball Association.

Recommended Citation

Kannan, Adarsh; Kolovich, Brian; Lawrence, Brandon; and Rafiqi, Sohail (2018) "Predicting National Basketball Association Success: A Machine Learning Approach," SMU Data Science Review: Vol. 1: No. 3, Article 7.
Available at: https://scholar.smu.edu/datasciencereview/vol1/iss3/7

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License