National Basketball Association Most Valuable Player prediction based on machine learning methods

Xinyang Li

doi:10.1117/12.2623094

1 December 2021 National Basketball Association Most Valuable Player prediction based on machine learning methods

Xinyang Li

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 120791Q (2021) https://doi.org/10.1117/12.2623094
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

The NBA (national basketball association) is one of the most well-known sports associations worldwide. Although under the influence of the epidemic, there are still 12.52 million people watching the sixth game of the final, and this number is only for the United States. Also, apart from the fascinating games, what is more interesting is the tremendous amount of data generated by the hundreds of games played per season. Lots of analyses and predictions using the data could be done in various ways. What we did in this essay was to make predictions that may help people win money in betting for MVP per season. More than thirty years of NBA games with fifty columns of features were used for analysis. Then four models for prediction were built. The result turned out to be 67% in winning a bet on MVP, which is quite good.

Citation Download Citation

Xinyang Li "National Basketball Association Most Valuable Player prediction based on machine learning methods", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 120791Q (1 December 2021); https://doi.org/10.1117/12.2623094

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