Quantifying momentum and influencing factors of tennis players using the XGBoost model

Momentum can directly or indirectly affect a tennis player's mentality and the trajectory of the game, thereby changing the outcome of the match. The article provides a clear quantitative description of the concept of momentum in tennis, analyzing the impact of momentum fluctuations on the trajectory of the game and the athlete's scoring; a secondary indicator system is established, and the weights of each indicator are determined through expert analysis method, CRITIC weighting method, and hierarchical analysis method. The final value of momentum is randomly tested with a random walk model. The results show that momentum is not random but influenced by specific factors, indicating that there is a certain correlation between the fluctuation of momentum and the success of the player. Due to the non-normal distribution of momentum, using the XGBoost model and Shap feature importance analysis can determine the significant influence of factors such as the distance run by athletes and the speed at which they hit the tennis ball. Moreover, the model demonstrated excellent performance in five randomly selected matches, with low error indicators and high fitting degrees, and an R<sup>2</sup> coefficient of up to 0.9814, showing the model's high precision and strong generalization capability.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-05-19
DOI
https://doi.org/10.1038/s41598-025-02465-2
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

Quantifying momentum and influencing factors of tennis players using the XGBoost model

Xu Zhang, Donghong Wang, Yue Xie, Qinyan Zhu
Scientific Reports
Sports Analytics and Performance
article

Quantifying momentum and influencing factors of tennis players using the XGBoost model

Xu Zhang, Donghong Wang, Yue Xie, Qinyan Zhu
article en

Abstract

Momentum can directly or indirectly affect a tennis player's mentality and the trajectory of the game, thereby changing the outcome of the match. The article provides a clear quantitative description of the concept of momentum in tennis, analyzing the impact of momentum fluctuations on the trajectory of the game and the athlete's scoring; a secondary indicator system is established, and the weights of each indicator are determined through expert analysis method, CRITIC weighting method, and hierarchical analysis method. The final value of momentum is randomly tested with a random walk model. The results show that momentum is not random but influenced by specific factors, indicating that there is a certain correlation between the fluctuation of momentum and the success of the player. Due to the non-normal distribution of momentum, using the XGBoost model and Shap feature importance analysis can determine the significant influence of factors such as the distance run by athletes and the speed at which they hit the tennis ball. Moreover, the model demonstrated excellent performance in five randomly selected matches, with low error indicators and high fitting degrees, and an R<sup>2</sup> coefficient of up to 0.9814, showing the model's high precision and strong generalization capability.

Scientific ReportsVol. 15(1)
Hubei University Of Economics (CN), Hubei University (CN)
Gender equality
Openalex Percentile: Top 84%
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.