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Determining optimal cadence for an individual road cyclist from field data

Reed, Robert, Scarf, Philip, Jobson, Simon Adrian and Passfield, Louis 2016. Determining optimal cadence for an individual road cyclist from field data. European Journal of Sport Science 16 (8) , pp. 903-911. 10.1080/17461391.2016.1146336

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The cadence that maximises power output developed at the crank by an individual cyclist is conventionally determined using a laboratory test. The purpose of this study was two-fold: (i) to show that such a cadence, which we call the optimal cadence, can be determined using power output, heart-rate, and cadence measured in the field and (ii) to describe methodology to do so. For an individual cyclist's sessions, power output is related to cadence and the elicited heart-rate using a non-linear regression model. Optimal cadences are found for two riders (83 and 70 revolutions per minute, respectively); these cadences are similar to the riders’ preferred cadences (82–92 rpm and 65–75 rpm). Power output reduces by approximately 6% for cadences 20 rpm above or below optimum. Our methodology can be used by a rider to determine an optimal cadence without laboratory testing intervention: the rider will need to collect power output, heart-rate, and cadence measurements from training and racing sessions over an extended period (>6 months); ride at a range of cadences within those sessions; and calculate his/her optimal cadence using the methodology described or a software tool that implements it.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Additional Information: This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, reproduction in any medium, provided the original work is properly cited.
Publisher: Taylor & Francis: SSH Journals
ISSN: 1746-1391
Funders: EPSRC
Date of First Compliant Deposit: 7 December 2020
Date of Acceptance: 31 December 2015
Last Modified: 09 Dec 2020 14:45

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