Analysis Of The Worst-Case Scenarios In An Elite Football Team: Towards A Better Understanding And Application

Novak A.R., Impellizzeri F.M., Trivedi A., Coutts A.J., McCall A.

This study investigated the variability in the worst-case scenario (WCS) and suggested a framework to improve the definition and guide further investigation. Optical tracking data from 26 male players across 38 matches were analyzed to determine the WCS for total distance, high-speed running (>5.5 m/s) and sprinting (>7.0 m/s) using a 3-minute rolling window. Position, total output, previous epoch, match half, time of occurrence, classification of starter vs substitute, and minutes played were modeled as selected contextual factors hypothesized to have associations with the WCS.

Linear mixed effects models were used to account for cross-sectional observations and repeated measures. Unexplained variance remained high (total distance R² = 0.53, high-speed running R² = 0.53, and sprinting R² = 0.40). Intra-individual variability was also high (total distance CV = 4.6–8.2%; high-speed CV = 15.6–37.8%, and Sprinting CV = 21.1–76.4%). The WCS defined as the maximal physical load in a given time-window produces unstable metrics lacking context, with high variability.

Furthermore, training drills targeting this metric concurrently across players may not have representative designs and may underprepare athletes for complete match demands and multifaceted WCS scenarios. Using WCS as benchmarks (reproducing similar physical activity for training purposes) is conceptually questionable.

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