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Age and performance in masters swimming and running

  • Richard De Veaux , Anna Plantinga and Elizabeth Upton ORCID logo EMAIL logo
Published/Copyright: February 21, 2025
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Journal of Quantitative Analysis in Sports
From the journal Journal of Quantitative Analysis in Sports Volume 21 Issue 2

Abstract

The masters movement in swimming and running has exploded, resulting in an abundance of data to study the impact of age on performance. Analyzing data from masters events in running and swimming for athletes aged 35 to 80, we model the percentage increase in event time (or decrease in performance) by age and sex via stacked models that combine polynomial models, neural networks, and natural splines. To answer fundamental questions on the nature of performance decline for competitive athletes, we bootstrap the procedure to obtain confidence intervals. Cross-sectional masters data from the past decade are used to construct models, and the model predictions are compared to the trajectory of current world records by age and to estimates of decline using longitudinal data. Furthermore, the study explores the impact of constituent year, birth cohort, and participation effects, emphasizing the challenges in distinguishing age-related decline from factors like evolving training practices and varied participation rates. Our results give evidence that men generally decline more slowly than women, performance declines more rapidly for endurance events, athletes who participate more frequently decline more slowly than others, and masters level runners decline at rates roughly equivalent to world record holders.

Keywords: masters events; stacked models; running; swimming; aging; cohort effects
Corresponding author: Elizabeth Upton, Department of Mathematics and Statistics, Williams College, 18 Hoxsey St., Williamstown, MA 01269, USA, E-mail: 

Analytic code to reproduce the analysis is available at: https://github.com/elizabeth-upton/age_and_performance_SwimRun.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Sample code and data are available; websites for data scraping were provided.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/jqas-2024-0018).

Received: 2024-01-31
Accepted: 2025-01-20
Published Online: 2025-02-21
Published in Print: 2025-06-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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  2. Research Articles
  3. A hierarchical approach to modeling golf hole scores with Hardy distributions
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https://doi.org/10.1515/jqas-2024-0018
Keywords for this article
masters events; stacked models; running; swimming; aging; cohort effects

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. A hierarchical approach to modeling golf hole scores with Hardy distributions
  4. Estimating individual contributions to team success in women’s college volleyball
  5. Age and performance in masters swimming and running
  6. A family of solutions related to Shin’s model for probability forecasts
  7. Penalty kicks: an adversarial risk analysis (ARA) perspective
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