From 6,000 m to 2,000 m: A Field-Based Model to Predict Rowing Ergometer Performance in Female National-Selection Athletes

Abstract Rowing selection and monitoring rely on 2,000-m ergometer time, yet repeated maximal 2,000-m trials are physically and logistically costly, and laboratory maximal-oxygen-uptake testing is rarely feasible across a national programme. This study aimed to predict 2,000-m ergometer time from tests already administered in the Indonesian National Rowing Selection (SELEKNAS). Using verified records from 22 female national-selection rowers, the average power and stroke rate of the 6,000-m, 1-minute, and 150-m ergometer tests were entered into a forward stepwise multiple regression, and all model assumptions were examined. Mean 6,000-m power was the dominant predictor, explaining 72.6% of the variance in 2,000-m time; adding 1-minute stroke rate raised the total to 79.5% (adjusted R² = 0.773; standard error of the estimate = 5.07 s; p < 0.001), with normally distributed residuals, no multicollinearity (VIF = 1.00), and independent residuals. The model predicted 90.9% of athletes' times to within 10 s. A routinely collected field test can therefore estimate 2,000-m performance without additional maximal trials or laboratory testing, offering coaches and national selectors a practical, low-cost tool for talent screening and performance monitoring in female rowers.