Purpose: With the Olympic rowing distance reduced to 1500 m for 2028, the anaerobic power reserve (APR) framework has been proposed to evaluate anaerobic performance and differentiate physiological profiles. This study investigated performance predictions and athlete profiles using the APR framework and related physical performance measures. Methods: Thirty-one female (simulated 2000-m performance (P2k) = 285.1 ± 36.0 W) and 63 male (P2k = 422.8 ± 62.2 W) (sub-)elite German rowers completed tests for maximal oxygen uptake (V̇O 2 max), maximal lactate accumulation rate (cLamax), peak power output (PPO), power at V̇O 2 max (MAP), at 2 mmol·L⁻¹ (P2) and 4 mmol·L⁻¹ blood lactate (P4), and P2k. Backward stepwise regression models were used to predict P2k and models performance was evaluated via a k-fold cross-validation approach. Commonality analyses and LGM metrics were used to assess predictor contribution, while k -means clustering based on the power reserve ratio (PRR = PPOꞏMAP -1 ) were used to identify athlete subgroups. Results: For P2k prediction, P4, PPO, and V̇O 2 max in females (average results from k-fold cross-validation: R 2 = 0.90, RMSE = 9.3 W, MAE = 6.3 W), and P4, MAP, and PPO in males (R 2 = 0.93, RMSE = 16.2 W, MAE = 12.6 W) showed excellent model fits. Commonality analyses revealed ~90% shared variance contributions among predictors. K -means clustering identified sprint-type (females: PRR ≥1.52; males: PRR ≥1.66) and endurance-type rowers (females: PRR ≤1.43; males: PRR ≤1.62) along the PRR continuum. Conclusions: Key predictors for P2k highlight the interplay between the aerobic and anaerobic systems. Moreover, the distinct sprint - and endurance-type clusters emphasize the physiological diversity among rowers, even among athletes with similar performance outcomes. Longitudinal PRR assessments may support talent identification and tailored training strategies.
Rappelt et al. (Fri,) studied this question.