When Salary Caps Rise, Teams Shine: A Regression Analysis of the Effects of the NBA Salary Cap on Team Performance

Abstract

The National Basketball Association (NBA) is a professional men's basketball league in North America that is composed of 30 teams. Like the other 3 major North American league sports (NFL, NHL, MLB), the NBA enforces a salary cap. A salary cap places a limit on the amount of money a team can spend on its players' salaries. Front office personnel must be conscious of the cap when working to assemble a winning team. Salary allocation can be a significant factor of team performance and determining the factors that influence owners to pay players more is important when considering the cap restrictions.

This thesis examines the key metrics used in professional basketball and first uses multiple regression models to determine which of these player metrics are important to salary. Next, the correlation between total team salary cap and win percentage is analyzed. A third multiple regression model is implemented to determine which team statistics are the greatest determinants of total salary cap. Results indicated that average points per game had the strongest statistical significance on both player salary and team salary cap. The regressions found a strong positive correlation between the salary cap and winning percentage, indicating that as total cap rises, the team "shines" more.