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Predicting Trail-Running Performance With Laboratory Exercise Tests and Field-Based Results.

Volker Scheer, Tanja I Janssen, Solveig Vieluf

International Journal of Sports Physiology and Performance

|June 29, 2018

Summary

This summary is machine-generated.

Laboratory exercise tests accurately predict trail running performance. Combining individual anaerobic threshold and running economy with previous race times offers 99% predictive power for trail runners.

Keywords:

endurance running performance lactate threshold maximal oxygen uptake

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Area of Science:

Sports Science
Exercise Physiology
Trail Running Performance Analysis

Background:

Trail running performance prediction is complex.
Standard laboratory tests are evaluated for their efficacy in predicting trail running outcomes.
Understanding physiological markers can enhance training and race strategies.

Purpose of the Study:

To assess the predictive power of three standard laboratory exercise tests for trail running performance.
To correlate laboratory measurements with actual trail race times.
To identify key physiological variables that best predict trail running success.

Main Methods:

Nine competitive male trail runners underwent step, ramp, and trail tests.
Measurements included maximal oxygen uptake (VO2max), vVO2max, ventilatory (VT) and lactate thresholds (LT), mechanical power, and running economy (RE).
Data were correlated with 31-km trail race times using multiple-regression analysis.

Main Results:

Step and ramp tests significantly predicted performance.
Step-test variables (speed at individual anaerobic threshold and RE) showed the highest prediction (R2 = .651).
Incorporating previous year's race time with step-test data achieved 99% predictive power (R2 = .988).

Conclusions:

Graded exercise tests, including VO2max, individual anaerobic threshold, and RE, accurately predict trail running performance.
Combining submaximal intensities (individual anaerobic threshold, RE) with prior race performance significantly enhances predictive accuracy.
This model offers a highly reliable method for forecasting trail running outcomes.