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Performance Prediction and Athlete Categorization using the Anaerobic Power Reserve Framework in Rowing
Ludwig Rappelt1,2, Lars Donath1, Tim Wiedenmann1
1Department of Intervention Research in Exercise Training, German Sport University Cologne, Cologne, GERMANY.
Medicine and Science in Sports and Exercise
|December 5, 2025
Summary
The anaerobic power reserve (APR) framework effectively predicts rowing performance and identifies distinct sprint and endurance athlete profiles. This physiological diversity highlights the need for tailored training strategies in elite rowing.
Area of Science:
- Sports Science
- Exercise Physiology
- Rowing Performance Analysis
Background:
- The Olympic rowing distance is changing to 1500m for the 2028 Games.
- The anaerobic power reserve (APR) framework has been proposed to assess anaerobic capacity and differentiate athlete physiological profiles.
- Understanding these profiles is crucial for optimizing training and performance in elite rowers.
Purpose of the Study:
- To investigate the predictive capabilities of the APR framework for simulated 2000-m rowing performance (P2k).
- To identify distinct physiological profiles of rowers using APR-related metrics.
- To explore the relationship between aerobic and anaerobic contributions to rowing performance.
Main Methods:
- Thirty-one female and 63 male elite rowers underwent testing for maximal oxygen uptake (V̇O2max), maximal lactate accumulation rate (cLamax), peak power output (PPO), and power outputs at various blood lactate concentrations (MAP, P2, P4).
- Backward stepwise regression models were developed to predict P2k, with performance validated using k-fold cross-validation.
- K-means clustering based on the power reserve ratio (PRR) was employed to categorize athletes into subgroups.
Main Results:
- Regression models demonstrated excellent predictive accuracy for P2k in both females (R²=0.90) and males (R²=0.93), with key predictors including P4, PPO, V̇O2max (females), and MAP (males).
- Commonality analyses indicated substantial shared variance (~90%) among the predictor variables.
- K-means clustering successfully differentiated rowers into sprint-type and endurance-type profiles based on their PRR values.
Conclusions:
- The study confirms the significant interplay between aerobic and anaerobic systems in determining rowing performance.
- Distinct physiological profiles (sprint vs. endurance) exist among rowers, even those with similar overall performance levels.
- Longitudinal monitoring of the PRR is recommended for talent identification and the development of individualized training programs.
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