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Research Article: Session-RPE for quantifying workload in olympic curling athletes

Date Published: 2025-09-10

Abstract:
To investigate the correlation between different workload methods among Olympic curling athletes. Eight curlers were monitored after training during Olympic seasons with three load quantification methods: external load measurements, physiological/biochemical markers, and Omegawave state indices. Intraclass Correlation Coefficient and Bland-Altman plots were used to analyze the Session-RPE index [sRPE workload (RPE?×?session duration), acute:chronic workload ratio (ACWR), etc.], external [number of draws (the number of curling stones thrown during training/competition), training duration, etc.], and internal [physiological and biochemical indices (testosterone, etc.), and Omegawave sport performance evaluation system indices (comprehensive readiness, etc.)] workloads. The sRPE index was significantly correlated with external loads and Omegawave sport performance indicators at the 0.01 level ( p <?0.01); it was significantly correlated with cortisol and creatine kinase at the 0.05 level ( p <?0.05). In the standardized ICC and Bland-Altman plot concordance analyses, the sRPE correlates showed moderate (0.4?<?ICC?<?0.6) to strong (0.6?<?ICC?<?0.8) concordance with the corresponding external loading indices, the Omegawave athletic status indices, and average (0.2?<?ICC?<?0.4) to moderate agreement with the corresponding physiological and biochemical indicators. The sRPE is a valid curling training-load tool capturing sport-specific demands but retains psychosocial limitations. Appropriate methods should be selected based on actual conditions and needs when choosing how to quantify and evaluate training load.

Introduction:
Curling, a strategically guided team sport, exhibits distinct characteristics including prolonged duration, intermittent high-intensity efforts, and significant cognitive demands ( 1 , 2 ). These attributes necessitate specialized load monitoring approaches. Given that tactical decisions substantially modulate in-game load magnitudes, discrete quantification methods (e.g., single-stone presses or sweep frequency) prove inadequate for curling load evaluation. Such metrics become temporally diluted over 2–3?h…

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