Quantifying Tennis Player Performance: A Linear Regression Approach

Abstract

This paper uses linear regression to quantitatively analyse the performance of players in the men's singles competition at Wimbledon 2023. Firstly, the data is processed by observationally analysing the match data to ensure compliance with the tournament standards and regulations. Next, key metrics were extracted, including short-term and long-term metrics, as well as the introduction of Serve Indicator to consider the impact of serve advantage on player performance. Then, the most important independent variables were identified through Random Forest feature analysis and parameters were calculated using least squares to construct performance indicators for use in linear regression. Finally, through data visualisation and analysis, it was found that player 1 usually performs better at critical moments, showing greater stability and consistency, while player 2 shows greater variability and unpredictability. Overall, the linear regression method in this paper is valuable and practical for quantifying tennis players' performance, and can provide a reference for players and coaches to help them better analyse and improve their performance.