Research on Quantifying and Evaluating Tennis Match Momentum Based on Comprehensive Analytical Methods

Momentum is crucial in tennis matches, influencing player performance and match outcomes. However, quantifying and evaluating momentum has long been a challenge in sports science research. This study aims to quantify momentum in tennis matches by establishing a hierarchical analysis-based model for momentum flow. The model analyzes factors affecting momentum through five criteria: Service Level, Catch Level, Competition Result, Finishing Ability, and Winning Streak, with respective weights of approximately (0.1, 0.1, 0.2, 0.4, 0.2). Subsequently, the study assigns scores to these criteria based on different actions within a match. By multiplying the weights and scores, the momentum of each player is quantified, and the ratio of the two players' momentum provides a measure of momentum flow during the match. To assess the impact of momentum on match outcomes, the study employs k-means++ clustering analysis, violin plot analysis, and point-biserial correlation analysis. The point-biserial correlation analysis reveals a positive correlation coefficient of 0.66 between a player's momentum and their victory. Similar results are derived from the violin plot and clustering analysis. Therefore, it can be concluded that there is a significant association between the direction of momentum flow and a player's success in a match.

Authors

Publication Details

Journal
Transactions on Computer Science and Intelligent Systems Research
Published
2024-10-17
DOI
https://doi.org/10.62051/7fyygh87
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
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article

Research on Quantifying and Evaluating Tennis Match Momentum Based on Comprehensive Analytical Methods

Houjiang Liu, Hong Cao, Shi qi Liu
Transactions on Computer Science and Intelligent Systems Research
Sports Analytics and Performance
article

Research on Quantifying and Evaluating Tennis Match Momentum Based on Comprehensive Analytical Methods

Houjiang Liu, Hong Cao, Shi qi Liu
article en

Abstract

Momentum is crucial in tennis matches, influencing player performance and match outcomes. However, quantifying and evaluating momentum has long been a challenge in sports science research. This study aims to quantify momentum in tennis matches by establishing a hierarchical analysis-based model for momentum flow. The model analyzes factors affecting momentum through five criteria: Service Level, Catch Level, Competition Result, Finishing Ability, and Winning Streak, with respective weights of approximately (0.1, 0.1, 0.2, 0.4, 0.2). Subsequently, the study assigns scores to these criteria based on different actions within a match. By multiplying the weights and scores, the momentum of each player is quantified, and the ratio of the two players' momentum provides a measure of momentum flow during the match. To assess the impact of momentum on match outcomes, the study employs k-means++ clustering analysis, violin plot analysis, and point-biserial correlation analysis. The point-biserial correlation analysis reveals a positive correlation coefficient of 0.66 between a player's momentum and their victory. Similar results are derived from the violin plot and clustering analysis. Therefore, it can be concluded that there is a significant association between the direction of momentum flow and a player's success in a match.

Transactions on Computer Science and Intelligent Systems ResearchVol. 6
Openalex Percentile: Top 78%
Sports Analytics and Performance
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Research on Quantifying and Evaluating Tennis Match Momentum Based on Comprehensive Analytical Methods — Houjiang Liu, Hong Cao, et al. · Transactions on Computer Science and Intelligent Systems Research (2024) | TGRS Research Map | TGRS