Location

Jereld R. Nicholson Library: Grand Avenue

Subject Area

Mathematics

Description

For competitive cyclists, each course presents a unique set of factors and, in turn, leads to difficulty in choosing a racing strategy. Some courses confront cyclists with drastic changes in elevation while others are of a more consistent grade. Similarly, curvature varies from course to course.

Further, riders vary in their areas of strength. A rider’s power curve maps their instantaneous power output 𝑃 in W/kg over the amount of time that the rider can sustain that power level in seconds. The shape of a rider’s power curve indicates their riding style.

In this paper, we model the optimal race strategy based on a rider’s power curve through the use of The Skiba Energy Store model and applied kinematics. We then consider the race times of select riders from the 2021 Tokyo Olympics Individual Time Trials and the 2021 UCIWorld Championships Individual Time Trials. The race times of the top finishers indicate their average power output 𝑃𝐴𝑉𝐸 during the race; we then utilize the expected 𝑃 that world class cyclists can maintain for the full time of a race to calculate a standardized finishing time of top tier riders. This enables us to evaluate the accuracy of our model.

Comments

Above is a slide presentation, but our Symposium presentation will be in the form of a poster. The information is generally the same, but will be presented using a different format.

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May 20th, 9:00 AM May 20th, 3:00 PM

Optimal Race Strategies for Cyclists

Jereld R. Nicholson Library: Grand Avenue

For competitive cyclists, each course presents a unique set of factors and, in turn, leads to difficulty in choosing a racing strategy. Some courses confront cyclists with drastic changes in elevation while others are of a more consistent grade. Similarly, curvature varies from course to course.

Further, riders vary in their areas of strength. A rider’s power curve maps their instantaneous power output 𝑃 in W/kg over the amount of time that the rider can sustain that power level in seconds. The shape of a rider’s power curve indicates their riding style.

In this paper, we model the optimal race strategy based on a rider’s power curve through the use of The Skiba Energy Store model and applied kinematics. We then consider the race times of select riders from the 2021 Tokyo Olympics Individual Time Trials and the 2021 UCIWorld Championships Individual Time Trials. The race times of the top finishers indicate their average power output 𝑃𝐴𝑉𝐸 during the race; we then utilize the expected 𝑃 that world class cyclists can maintain for the full time of a race to calculate a standardized finishing time of top tier riders. This enables us to evaluate the accuracy of our model.