Predicting physical performance after training: insights from machine learning using small samples
Luuk Vos,
Renske Vergeer,
Richie Goulding
et al.
Abstract:Background
Performance optimization is a major goal in sports science. However, this remains difficult due to the small samples and large individual variation in physiology and training adaptations. Machine learning (ML) solutions seem promising, but have not been tested for their capability to predict performance in this setting. The aim of this study was to predict 4-km cycling performance following a 12-week training intervention based on ML models with predictors from physiological profiling, individual tr… Show more
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