Week-by-Week Predictive Value of External Load Ratios on Injury Risk in Professional Soccer: A Logistic Regression and ROC Curve Analysis Approach.

Logistic regression analysis yielded highly significant associations (χ 2 = 14.5, p < 0.001) and strong model fit metrics (AUC = 0.811; R 2 McF = 0.262), validating the discrimination power of this variable.

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ACWR TD W3 showed a trend toward an association with injury risk (χ 2 (1) = 5.24, p = 0.022; R 2 McF = 0.094; AUC = 0.675; OR = 236.33, 95% CI [0.91, 61,385.02], p = 0.054), while ACWR TD W4 also demonstrated a marginal trend ( p = 0.076; AUC = 0.665).

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ACWR TD W3 showed a trend toward an association with injury risk (χ 2 (1) = 5.24, p = 0.022; R 2 McF = 0.094; AUC = 0.675; OR = 236.33, 95% CI [0.91, 61,385.02], p = 0.054), while ACWR TD W4 also demonstrated a marginal trend ( p = 0.076; AUC = 0.665).

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For predictors approaching significance, Estimated Marginal Means (EMMs), formerly known as Least Squares Means (LSMeans), were calculated at standardized levels (−1 SD, mean, +1 SD) to visualize the probability of injury associated with varying workload ratios.

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