Analyzing the Impact of Momentum on Tennis Matches Using Decision Tree Classification: A Case Study of Wimbledon

In this paper, a Momentum Scoring Model is developed to quantify the abstract concept of Momentum through a set of important factors such as the base point, the hold point, and the break point. The model has the flexibility to capture player's in-game scoring changes with high accuracy and has a visualization process that is easy for tennis coaches and tennis players to understand. In order to statistically test whether momentum score changes are beyond random fluctuations, this paper validates the data by using the permutation test and shows that momentum plays a role in tennis matches. The paper also extracted several key metrics affecting momentum shifts, such as server, p2_score, etc., through an inductive learning algorithm like decision tree. Based on the above model, this article provides some preparation methods for tennis players. Such as analyzing the opponent's playing patterns, enhancing individual psychological preparation, optimizing serving and receiving strategies, etc.

Authors

Publication Details

Journal
Transactions on Computer Science and Intelligent Systems Research
Published
2024-10-17
DOI
https://doi.org/10.62051/kyjgzg72
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

Analyzing the Impact of Momentum on Tennis Matches Using Decision Tree Classification: A Case Study of Wimbledon

Xueyu Zhu, Kuanjun Liu
Transactions on Computer Science and Intelligent Systems Research
Sports Analytics and Performance
article

Analyzing the Impact of Momentum on Tennis Matches Using Decision Tree Classification: A Case Study of Wimbledon

Xueyu Zhu, Kuanjun Liu
article en

Abstract

In this paper, a Momentum Scoring Model is developed to quantify the abstract concept of Momentum through a set of important factors such as the base point, the hold point, and the break point. The model has the flexibility to capture player's in-game scoring changes with high accuracy and has a visualization process that is easy for tennis coaches and tennis players to understand. In order to statistically test whether momentum score changes are beyond random fluctuations, this paper validates the data by using the permutation test and shows that momentum plays a role in tennis matches. The paper also extracted several key metrics affecting momentum shifts, such as server, p2_score, etc., through an inductive learning algorithm like decision tree. Based on the above model, this article provides some preparation methods for tennis players. Such as analyzing the opponent's playing patterns, enhancing individual psychological preparation, optimizing serving and receiving strategies, etc.

Transactions on Computer Science and Intelligent Systems ResearchVol. 6
Peace, Justice and strong institutions
Openalex Percentile: Top 78%
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.