Performance of regression models for each muscle parameter and associated performance metrics.

Standard errors (SE) reflect the precision of the estimated coefficients, while standardized coefficients (Beta) represent the change in the dependent variable’s standard deviations per one-standard-deviation change in the predictor variable [42]. Cohen’s f2 [44] quantifies the effect size in regression, indicating the variance explained by an independent variable. Statistical power [45] denotes the likelihood of correctly rejecting the null hypothesis, with a value of 1.0 indicating sufficient sample size and effect size for detecting significant results.