Analyzing Workload-Monitoring Consistency and Same-Week Injury-Classification Performance in Female Adolescent Swimmers: An Exploratory Session-RPE and Neural Network Study
Xiaodong Zhao, Chunlei Li, Junqi Wu · Life · 2026
Objective: This exploratory study aimed to: (1) verify whether session-RPE (sRPE) can serve as a reliable workload-monitoring indicator in female adolescent swimmers aged 13–17 years; (2) compare the same-week injury-classification performance of sRPE-, exponentially weighted moving average (EWMA)-, and robust exponential decreasing index (REDI)-derived indicators using a multilayer perceptron (MLP) model; and (3) identify candidate indicator combinations for future prospective validation in youth swimming.
Design: A 12-week prospective observational tracking study was conducted with 20 female adolescent 200 m individual medley swimmers (aged 13–17 years) from a single provincial youth swimming team (Zhejiang). Twenty-five injury events were recorded across 240 athlete-weeks. Because repeated athlete-weeks were analyzed as independent samples and injury status was classified within the same week as the load indicators, the classification
Findings: are preliminary internal-validation
Results: that may overestimate model performance; they are not externally validated prospective predictions.
Methods: Pearson and Spearman correlation analyses, intraclass correlation coefficient (ICC), and Bland-Altman plots were used to evaluate associations and agreement between sRPE-derived indicators and traditional training-load indicators (swimming distance and training duration). Twelve sRPE-derived indicators (four each from sRPE, EWMA, and REDI) were used as input features for MLP same-week binary classification models. REDI was included because its natural-logarithmic weighting emphasizes long-term cumulative load, complementing the recency-weighted EWMA. Model performance was evaluated using area under the ROC curve (AUC), with Bootstrap resampling (1000 iterations) to characterize internal stability.
Results: Swimming distance, which shares no computational component with sRPE, was very strongly correlated with sRPE (r = 0.965, p 0.5, red > 0.7) are conceptual, non-optimized boundaries and require prospective derivation and validation in independent cohorts before any operational use.