# A mini-review of mathematical methods in sprint performance

## TL;DR

This paper reviews how math helps understand and improve sprint performance in sports science.

## Contribution

It highlights novel uses of mathematical models in analyzing and predicting sprint biomechanics.

## Key findings

- Mathematical methods provide objective frameworks for analyzing sprint performance.
- Regression and differential equations enhance predictive and mechanistic insights.
- The review identifies opportunities for further methodological development in sports science.

## Abstract

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 Wey and 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.