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MINI REVIEW article

Front. Sports Act. Living

Sec. Elite Sports and Performance Enhancement

A Mini-Review of Mathematical Methods in Sprint Performance

Provisionally accepted
  • Fujian Normal University, Fuzhou, China

The final, formatted version of the article will be published soon.

Mathematics has established itself as a core analytical tool in sprint performance research within sports science, offering quantitative insights that inform coaching strategies, training methodologies, and athlete development. This mini-review examines eight highly-cited publications by Peter Weyand and colleagues, whose work has significantly advanced understanding of sprint biomechanics through the integration of mathematical and biomechanical modeling approaches. This review analyzes diverse methodological applications, ranging from regression models for predicting athletic potential to differential equations for kinetic and kinematic analysis of sprint mechanics. Critical evaluation of these seminal studies demonstrates how mathematical approaches provide objective frameworks for performance analysis, enhance predictive capabilities, and offer mechanistic insight into sprint performance determinants. Then findings underscore the fundamental role of mathematical methods in advancing spring performance research and highlight opportunities for further methodological development in sports science applications.

Keywords: Mathematics, Sport science, sprint performance, mathematical modeling, Biomechanics, machine learning

Received: 02 Sep 2025; Accepted: 27 Oct 2025.

Copyright: © 2025 Fan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Yuzhou Fan, fan_yz@sz.jnu.edu.cn

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