A Study on Momentum Prediction of Tennis Players Based on Logistic Regression Model and ARIMA Model
This was exemplified in the 2023 Wimbledon Gentlemen's Singles final, where the young player Carlos Alcaraz defeated the experienced Novak Djokovic, with the shift in 'momentum' playing a crucial role. In this paper, we modeled real-time prediction of athletes' motor momentum, we constructed a composite predictive model that not only accurately forecasts the dynamic momentum of matches but also provides real-time assessments of player performance. Firstly, the real-time player performance assessment model was developed, and the interaction term and logistic regression prediction model were established for the 2023 Wimbledon men's singles tournament data, and then the ARIMA model(Autoregressive Integrated Moving Average Model) was used to predict the athlete's momentum time series to create a dynamic momentum assessment model to reveal the existence of a certain pattern of momentum change, and then the optimized momentum prediction model was constructed to find that some factors would have a greater impact on the momentum change. Finally, the model was used to measure the accuracy and robustness of the 2023 Wimbledon Men's Open Singles data.
Authors
- Suoxuan Zhang
- Xinyue Zhang (ORCID: https://orcid.org/0000-0001-8919-1664)
- Yizhuang Zhao
Institutions
- Harbin Engineering University (CN)
Publication Details
- Published
- 2025-03-26
- DOI
- https://doi.org/10.1109/edpee65754.2025.00012
- Primary Topic
- Sports Analytics and Performance
- Type
- article
- Field-Weighted Citation Impact
- 0.00