A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise

TL;DR

This study demonstrates that a hydraulic model more accurately predicts recovery kinetics from intermittent exercise than traditional work-balance models, even with small datasets typical in sports science.

Contribution

The paper introduces a hydraulic model that outperforms existing work-balance models in predicting recovery dynamics using limited data points.

Findings

Hydraulic model outperforms work-balance models on all metrics

Hydraulic model requires similar data points as work-balance models

Results suggest hydraulic model as a promising new alternative

Abstract

Data Science advances in sports commonly involve "big data", i.e., large sport-related data sets. However, such big data sets are not always available, necessitating specialized models that apply to relatively few observations. One important area of sport-science research that features small data sets is the study of recovery from exercise. In this area, models are typically fitted to data collected from exhaustive exercise test protocols, which athletes can perform only a few times. Recent findings highlight that established recovery such as the so-called work-balance models are too simple to adequately fit observed trends in the data. Therefore, we investigated a hydraulic model that requires the same few data points as work-balance models to be applied, but promises to predict recovery dynamics more accurately. To compare the hydraulic model to established work-balance models, we retrospectively applied them to data compiled from published studies. In total, one hydraulic model and three work-balance models were compared on data extracted from five studies. The hydraulic model outperformed established work-balance models on all defined metrics, even those that penalize models featuring higher numbers of parameters. These results incentivize further investigation of the hydraulic model as a new alternative to established performance models of energy recovery.