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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Study on Momentum Prediction of Tennis Players Based on Logistic Regression Model and ARIMA Model

Suoxuan Zhang, Xinyue Zhang, Yizhuang Zhao
Sports Analytics and Performance
article

A Study on Momentum Prediction of Tennis Players Based on Logistic Regression Model and ARIMA Model

Suoxuan Zhang, Xinyue Zhang, Yizhuang Zhao
article en

Abstract

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.

Harbin Engineering University (CN)
Openalex Percentile: Top 76%
Sports Analytics and Performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.