Predicting NBA Salaries with Machine Learning

<p>The NBA stands out as one of the most&nbsp;<strong>lucrative&nbsp;</strong>and&nbsp;<strong>competitive&nbsp;</strong>leagues in sports. In the last few years, the salaries of NBA players have been on an&nbsp;<strong>ascending&nbsp;</strong>trend, but behind every awe-inspiring dunk and three-pointer lies a complex web of factors that determine these salaries.</p> <p>From&nbsp;<strong>player performance</strong>&nbsp;and&nbsp;<strong>team success&nbsp;</strong>to&nbsp;<strong>market demand</strong>&nbsp;and&nbsp;<strong>endorsement deals</strong>, numerous variables come into play. Who never pondered why their team spent so much on an underperforming player, or marveled at the strategy behind a particularly successful deal?</p> <p>In this article, we use the capabilities of machine learning with Python to&nbsp;<strong>predict NBA salaries</strong>&nbsp;and uncover the&nbsp;<strong>crucial factors</strong>&nbsp;with most impact on players&rsquo; earnings.</p> <p>All the code and data used are available on&nbsp;<a href="https://github.com/GabrielPastorello/NBASalaryPrediction" rel="noopener ugc nofollow" target="_blank"><strong>GitHub</strong></a>.</p> <h1>Understanding the problem</h1> <p>Before diving into the problem, it is essential to grasp the fundamentals of the league&rsquo;s salary system. When a player is available on the market to sign a contract with any team he is known as a&nbsp;<strong>free agent</strong>&nbsp;(FA), a term that will be used a lot in this project.</p> <p>The NBA operates under a complex set of rules and regulations that aim to maintain competitive balance among teams. Two key concepts are at the core of this system: the&nbsp;<strong>salary cap</strong>&nbsp;and the&nbsp;<strong>luxury tax</strong>.</p> <p>The&nbsp;<strong>salary cap</strong>&nbsp;serves as a spending limit, restricting how much a team can spend on player salaries in a given season. The cap is determined by the league&rsquo;s revenue, and it is updated every year to ensure that teams operate within a reasonable financial framework. It also intends to prevent large-market teams from significantly outspending smaller-market counterparts, promoting parity among franchises.</p> <p><a href="https://towardsdatascience.com/predicting-nba-salaries-with-machine-learning-ed68b6f75566">Click Here</a></p>