Monitoring the Athlete Match Response: Can External Load Variables Predict Post-match Acute and Residual Fatigue in...

Monitoring athletes' external load during a soccer match may be useful to predict post-match acute and residual fatigue. This estimation would allow individual adjustments to training programs to minimize injury risk, improve well-being, and restore players' physical performance and inform the recovery process.

Using a systematic review and meta-analysis of the literature, the aim is to determine which monitoring variables would be the strongest predictors of acute (immediately) and residual (up to 72 h) fatigue states in soccer. PubMed, SPORTDiscus, and Web of Science databases were searched (until September 2018). Studies concurrently examining soccer match-related external load metrics and subjective and/or objective measures were selected to determine pooled correlations ([Formula: see text]) with confidence intervals (CI). The quality and strength of the findings of each study were evaluated to identify overall levels of evidence.

Eleven studies were included (n = 165 athletes). Acute ([Formula: see text] = 0.67; 95% CI = [0.40, 0.94]) and residual (24 h post-match, [Formula: see text] = 0.54; 95% CI = [0.35, 0.65]) changes in muscle damage markers and countermovement jump peak power output (CMJ_PPO) were, with moderate to strong evidence, largely correlated with running distance above 5.5 m s^-1. No other external load metric was largely correlated with both biochemical and neuromuscular markers. For every 100-m run above 5.5 m·s^-1, CK activity measured 24 h post-match increased by 30% and CMJ_PPO decreased by 0.5%. Conversely, the total distance covered did not present any evidence of a clear relationship with any fatigue-related marker at any time-point.

Running distance above 5.5 m·s^-1 represents the most sensitive monitoring variable characterizing biochemical and neuromuscular responses, at least when assessed during the initial 24 h (not at 48 h/72 h) post-match recovery period. In addition, total distance covered is not sensitive enough to inform decision-making during the fatigue monitoring process.