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Modeling human performance in running
R H Morton1, J R Fitz-Clarke, E W Banister
1School of Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada.
Journal of Applied Physiology (Bethesda, Md. : 1985)
|September 1, 1990
Summary
This study introduces a model where training generates fitness and fatigue, impacting athletic performance. The model accurately predicts performance, aiding in optimizing training for athletes and non-athletes.
Area of Science:
- Sports Science
- Exercise Physiology
- Biomathematics
Background:
- Athletic performance is influenced by training, but the precise relationship between training load, physiological responses, and performance outcomes requires quantitative models.
- Existing models may not fully capture the dynamic interplay of adaptive (fitness) and maladaptive (fatigue) responses to training.
- Understanding these responses is crucial for designing effective training programs and preventing overtraining.
Purpose of the Study:
- To present a mathematical and graphical model that quantifies the effects of training on athletic performance.
- To elucidate the dual responses of fitness and fatigue generated by training impulses.
- To validate the model's predictive capability against actual performance data.
Main Methods:
- Development of a theoretical model incorporating quantified training impulses.
- Mathematical formulation of exponential decay for fitness and fatigue in the absence of training.
- Utilization of recurrence equations for responses during repetitive training.
- Integration of fitness and fatigue into a linear difference equation for performance prediction.
- Correlation analysis between model-predicted and actual performance measures.
Main Results:
- The model demonstrates that training induces both fitness and fatigue, which decay exponentially without training.
- Repetitive training follows individual recurrence equations for fitness and fatigue.
- A strong correlation was observed between the model's predicted performance and actual performance during training and tapering phases.
- The model proved effective for both athletes and non-athletes.
Conclusions:
- The developed model accurately interprets the impact of training on athletic performance by quantifying fitness and fatigue.
- Model validation through correlation with real-world data supports its applicability.
- The model provides a tool for estimating individual training parameters and optimizing future training regimens for enhanced performance.