Subjective monitoring of professional soccer players: validation and application using big data analytics

The first aim of the research program reported in this thesis was to develop predictive models of daily and match-related fatigue and investigate the factors associated with subjective recovery in professional soccer players by analysing the commonly used wellness measures. The second aim was to explore the validity and reliability of five single-item scales widely used in research and practice to measure the subjective status of professional soccer players. In the first study we found, using big data analytics, that daily and match-day fatigue can be predicted with reasonable accuracy in six professional soccer teams monitored throughout the entire season (53,294 observations). This study also shows that psychological factors like stress and mood are important predictors of fatigue (mental fatigue). In the second study of four professional soccer teams (36,381 observations), we found that subjective recovery is primarily associated with fatigue and muscle soreness, and that these variables mediate 55% of the relationship between training load and subjective recovery. Albeit correlative, our findings also suggest that reducing mental fatigue and muscle soreness may help subjective recovery and performance of professional soccer players. In the third study involving 186 Italian soccer players, we investigated the validity and reliability of single-item measures of subjective Fatigue, Sleep Quality, Muscle Soreness, Stress and Mood. Although correlated to their criterion measures, these scales do not show a convergent validity to the criterion measures themselves. In conclusion, these practical and inexpensive single-item scales commonly used to monitor soccer players daily, do not appear to be a valid assessment of the variable they purport to measure.