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Next-Generation Models for Predicting Winning Times in Elite Swimming Events: Updated Predictions for the Paris 2024
Iñigo Mujika1,2, David B Pyne3, Paul Pao-Yen Wu4,5
1Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country, Leioa,Basque Country.
Summary
Statistical models accurately predict swimming performances for the Paris 2024 Olympic Games. These models offer coaches and athletes a data-driven framework for training and strategy development.
Area of Science:
- Sports Science
- Performance Analytics
- Statistical Modeling
Background:
- Accurate prediction of athletic performance is crucial for strategic planning in elite sports.
- International swimming events require robust models to forecast medal-winning capabilities.
Purpose of the Study:
- Evaluate statistical models for predicting international swimming medal performances.
- Generate updated performance predictions for the Paris 2024 Olympic Games.
Main Methods:
- Assessed two statistical models: linear regression with machine learning and a Bayesian framework.
- Models incorporated historical data, performance trends, and event-specific covariates.
- Evaluated prediction accuracy using mean absolute error against the Budapest 2022 World Championships.
Main Results:
- Both models demonstrated high accuracy, with mean absolute errors of 0.80% (linear regression/ML) and 0.85% (Bayesian).
- Predicted and actual times for the 2022 World Championships showed a strong correlation (r = .99).
Conclusions:
- The validated models provide an evidence-based framework for optimizing training and tactics.
- Predictions support coaches and athletes in strategic planning and resource allocation for the Paris 2024 Olympics.
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