Exploring the Dynamics of NBA Player Salaries: An Analysis of Influencing Factors

This research paper studies the complex factors that affect the Salary of the player in the National Basketball Association. The study involves the analysis of the linear regression model. The study mainly focuses on the factor of the in-game performance. Multiple databases are involved in the study, including the salary and performances of multiple players. The matrix of player performance and their salary are both analyzed through the Python program. The paper derives the linear correlation between the independent and dependent variables, with a comprehensive expression and reasonable prediction of the player's salary. In particular, the dependent variable in the study is the salary of the NBA athletes, and the independent variable is the multiple factors that are assumed that affect the salary. The main methodoly of the study is linear regression model, which build model to find the correlations between variables with the deviation. The study also incorporates the data from the different seasons of each player, where the analysis is both horizontal and vertical. Moreover, the prediction of the future salaries of several players is made. The study justified that the players with higher averages in the performance category and the attendance tend to have a higher salary.