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Predicting High-Power Performance in Professional Cyclists.

Dajo Sanders, Mathieu Heijboer, Ibrahim Akubat

    International Journal of Sports Physiology and Performance
    |June 2, 2016
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    The anaerobic power reserve (APR) model accurately predicts high-power cycling performance up to 300 seconds in professional cyclists. This model shows strong correlations between predicted and actual power outputs in field trials.

    Keywords:
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    Area of Science:

    • Exercise Physiology
    • Sports Science
    • Cycling Performance Analysis

    Background:

    • Accurate prediction of short-duration, high-power output is crucial for optimizing training and performance in professional cycling.
    • The anaerobic power reserve (APR) model offers a potential framework for predicting exercise intensity and duration capabilities.

    Purpose of the Study:

    • To evaluate the predictive accuracy of the anaerobic power reserve (APR) model for short-duration (5 to ~300 seconds) high-power performance in professional cyclists.
    • To assess the applicability of the APR model using a field-based approach in elite endurance athletes.

    Main Methods:

    • Collected data from 4 professional cyclists, including maximal aerobic power and sprint peak power output.
    • Established an individual power-duration relationship using an exponential constant for power decrement over time.
    • Validated the APR model by comparing predicted power output with actual power output from multiple all-out field trials of varying durations.

    Main Results:

    • The APR model demonstrated very large to nearly perfect correlations with actual power output across all cyclists (r = .88 to .97).
    • Actual power output during field trials consistently remained within an average of 6.6% (53 W) of the APR model's predictions.
    • The decrement in high-intensity exercise performance aligns with a single exponential-decay model, supporting the APR model's principles.

    Conclusions:

    • This pilot study provides case examples supporting the field-based applicability of the APR model in professional cyclists.
    • The findings suggest that the APR model can effectively predict high-power, short-duration cycling performance.
    • Further research with larger cohorts of elite cyclists is recommended to confirm these preliminary results.