The association between internal and external measures of training load in elite rowers during ergometer training

While traditional rowing metrics such as stroke rate and split times offer basic performance feedback, they do not fully reflect individual physiological responses, and the relationship between external and internal training loads remains inadequately characterized in rowing ergometer training. This study systematically investigated the correlations between two key internal load measures-training impulse (TRIMP) and session rating of perceived exertion training load (sRPE_TL)-and three biomechanical external load indicators in elite rowers, with the aim of establishing a more comprehensive training monitoring framework. Thirty elite male rowers (age 22.1 ± 3.6 years, VO₂max 64.5 ± 6.1 mL·min^-1·kg^-1) were monitored throughout a 48-week preparatory training period, with 1196 sessions analyzed. Participants who had missed more than three months of training were excluded. External training load metrics-including duration, stroke rate, stroke count (SC), and 500-m split time-and internal training load measures (TRIMP and sRPE_TL) were collected using standardized procedures. The percentage of boat speed (S%) was calculated by comparing the average boat speed during training to an individually determined maximum speed. Most external load measures, except duration, split time, and stroke rate, showed significant correlations with sRPE_TL (p < .001, FDR-adjusted). Individualized metrics strengthened these relationships, with SC and S% demonstrating moderate correlations with sRPE_TL (r = .41 and r = .40, respectively; p < .001, FDR-adjusted p = .002). TRIMP correlated with all external load metrics except stroke rate and count, most strongly with S% (r = .39, p < .001, FDR-adjusted p = .002). Multivariate regression identified SC, S%, and TRIMP as the strongest predictors of sRPE_TL (marginal R² = .50; model: Y = - 477.8 + 3.477 × S% + 17.262 × SC + 2.156 × TRIMP). In summary, S%, SC, and TRIMP were identified as optimal parameters for monitoring training load, collectively accounting for 50% of the variance in sRPE_TL-outperforming conventional external load metrics. These results support the integration of individualized speed measures with physiological and perceptual indicators to enhance the precision of training prescription in elite rowing programs.