National Basketball Association Salary Prediction: A Data-Driven Linear Regression Analysis

Jiahe Zhang

doi:10.54097/c966f539

Authors

Jiahe Zhang

DOI:

https://doi.org/10.54097/c966f539

Keywords:

National Basketball Association; player salary prediction; supervised machine learning

Abstract

National Basketball Association (also known as NBA which will be used as an abbreviation throughout this essay) as one of the few most successful professional sports leagues in the world, it has been well known by the fierce physical competition among the most talented and competitive players in the realm of basketball. However, there is something else to discover behind the dazzling crossovers and sensational clutches, hidden in the reflection on the O 'Brien Cup, for example, the salary. This essay will be discussing the prediction on NBA players’ salary using multiple supervised machine learning algorithms based on a dataset of players’ on-court data and achievements, aiming for an objective result that can be used for both prediction and evaluation of players’ contracts. The result of this essay reveals which specific variables are useful for predicting players’ salary.

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