Evidence map›Paper›PMID 42064105›Full record

ArticleJournal of exercise science and fitness2026

Gender and surface effects on tiebreak tactics in Grand Slams: A machine learning-enhanced point-by-point analysis.

Qiushi Wang, Yixiong Cui, Yan Chen, Haoyang Liu, Dapeng Bao, Wangwang Zhai

Abstract read
In one paragraph

Article in Journal of exercise science and fitness, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Qiushi WangSports Coaching College, Beijing Sport University, Beijing, China.
Yixiong CuiAI Sports Engineering Lab, School of Sports Engineering, BeijingSport University, Beijing, China.
Yan ChenEmployment Sports Department, Beihang University, Beijing, China.
Haoyang LiuSports Coaching College, Beijing Sport University, Beijing, China.
Dapeng BaoChina Institute of Sport and Health Science, Beijing Sport University, Beijing, China.
Wangwang ZhaiDepartment of Public Physical and Art Education, ZheJiang University, HangZhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Tiebreaks in professional tennis are high-pressure situations in which tactical execution may influence match outcomes. This study investigated how gender and playing surface are associated with tactical behavior and point outcomes during tiebreaks in Grand Slam singles matches. Methods: Using a dataset of 51,665 tiebreak points from 4347 matches played between 2011 and 2024 across the four Grand Slam tournaments, we applied a two-level analytical framework. First, set-level comparisons were conducted across 12 subgroups defined by gender, surface, and outcome. Second, point-level XGBoost models were developed separately by gender and surface, and SHAP values were used to interpret the contribution of 13 tactical predictors. To examine the effect of within-tiebreak dependency, an additional tiebreak-level grouped validation was performed. Sensitivity analyses were also conducted after excluding super tiebreaks. Results: Set-level analyses showed significant winner-loser differences in several technical-tactical indicators, particularly Serve Points Won, Winners, and Unforced Errors, with patterns varying by gender and surface. Under the original random split, point-level model accuracy ranged from 0.634 to 0.710 and AUC from 0.625 to 0.747 across subgroup models; under tiebreak-level grouped validation, the corresponding ranges were 0.637-0.700 and 0.595-0.752. SHAP analysis identified PointServer as the most consistently important predictor across subgroup models, whereas the relative importance of other variables-including RallyType, ServeWidth, ReturnDepth, and net-related indicators-varied by gender and surface. Sensitivity analyses excluding super tiebreaks showed trivial effect sizes at both the set and point levels. Conclusion: Tactical behavior in Grand Slam tiebreaks was associated with gender and surface context. Male grass-court tiebreaks were more strongly characterized by serve-dominant patterns, whereas female clay-court contexts showed greater relevance of rally control and error management. These findings provide retrospective, interpretable evidence on context-specific tactical tendencies and may serve as a useful reference for match preparation, post-match review, and performance analysis.

Indexed as

Non-linear modelingPlaying surfaceRacquet sportsTactical behaviorXGBoost (eXtreme gradient boosting)

Identifiers

PMID42064105
PMCPMC13125160

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.