Analysis of Influencing Factors of Basketball Match Based on Multiple Regression Model

Basketball competitions attract numerous fans with their exciting physical encounters, strategic tactical adjustments, and collaborative teamwork. Amidst a competition that seems to be full of uncertainties, one might inquire whether there exist some basic and precise rules that can be systematically analyzed. Therefore, this paper focuses on exploring mathematical patterns present in basketball competitions. First, based on the existing data, we analyze the relevant factors that affect the outcomes of basketball competitions and establish a multiple regression model. Then, the regression coefficients of the model are solved and analyzed using Stata software. Based on the principles of multiple regression equations, the influence factors of each factor are calculated via the normalization method. Finally, according to the results of multiple regression equations and the influence factors of individual factors, we aim to forecast competition outcomes in advance, thus providing actionable insights for the professional training of teams. The analysis and calculation in this paper quantify the determinants of victory and outcomes in basketball competitions. As a result, athletes may tailor their daily training regimens in accordance with the relative significance of each factor influencing the team's success.