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Week-by-Week Predictive Value of External Load Ratios on Injury Risk in Professional Soccer: A Logistic Regression
Andreas Fousekis1, Konstantinos Fousekis2, Georgios Fousekis2
1Laboratory of Evaluation of Human Biological Performance, Department of Physical Education and Sports Science, Aristotle University of Thessaloniki, 57001 Thessaloniki, Greece.
None:
Background and Objectives: This study aimed to assess the week-by-week predictive value of Acute:Chronic Workload Ratios (ACWRs) for non-contact injury risk in professional soccer players. Materials and Methods: A cohort of 40 elite players was monitored using GPS over two competitive seasons. Binomial logistic regression and ROC curve analyses were performed on ACWR metrics-including total distance, moderate-to high-speed running, sprinting, acceleration, and deceleration-during the four weeks prior to injury (W4 to W1). p-values were further adjusted for multiple comparisons using the false discovery rate (FDR) correction (q < 0.05). Results: Significant predictive models emerged mainly for ACWR metrics related to moderate-speed running (15-20 km/h), sprinting (>25 km/h), and acceleration/deceleration. The ACWR for 15-20 km/h (DSR15-20) demonstrated the highest predictive accuracy, particularly in Week 3 (AUC = 0.811, p = 0.004). Sprinting (DSR>25) was also significantly associated with injury occurrence across Weeks 1-4 (AUC = 0.709-0.755, p = 0.011-0.024). Acceleration (ACC) and deceleration (DEC) metrics showed significant associations prior to correction-ACC in Weeks 3-4 (AUC = 0.737-0.755, p = 0.020-0.026) and DEC in Weeks 3-4 (AUC = 0.720-0.741, p = 0.029-0.043)-but these associations did not retain significance following FDR adjustment (q = 0.052-0.086). In contrast, total distance (ACWR TD) and high-speed running (20-25 km/h) were weaker predictors, reaching only marginal or nonsignificant levels (e.g., Week 3, AUC = 0.675, p = 0.054). After FDR correction, only DSR15-20 and DSR>25 remained statistically significant (q < 0.05), confirming them as robust predictors of non-contact injury risk. Multivariable models adjusted for age and playing position confirmed these findings, with DSR15-20 and DSR>25 retaining their predictive value independent of confounding factors. Injury risk thresholds were established through Estimated Marginal Means (EMMs), defining the "Sweet Spot" and "Danger Zone" for each metric, whereas the "Low Load" zone was treated as exploratory. Conclusions: This weekly ACWR monitoring approach enables practical injury risk profiling, helping training staff optimize load management and minimize non-contact injury risk in elite soccer.
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