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Pace and critical gradient for hill runners: an analysis of race records

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journal contribution
posted on 2014-12-12, 13:39 authored by Anthony Kay
Route choice through mountainous terrain requires a knowledge of how pace (the reciprocal of speed) varies with gradient of ascent or descent. To model this variation for runners, we analyse record times for 91 uphill and 15 downhill races or race stages. The pace is modelled as a nonlinear function of gradient and a linear function of race duration, using ordinary least squares to obtain a best fit. For the gradient-dependence, six functional forms are compared, of which a quartic is found to fit the data best; however, at steep gradients the quartic model is unrealistic and it may be argued that a linear model is more appropriate. Critical gradients, at which a runner's vertical speed (uphill or downhill) is maximised, may be calculated from a nonlinear model, although it appears that there is no uphill critical gradient within the range of our dataset. © 2012 American Statistical Association.

History

School

  • Science

Department

  • Mathematical Sciences

Published in

Journal of Quantitative Analysis in Sports

Volume

8

Issue

4

Citation

KAY, A., 2012. Pace and critical gradient for hill runners: an analysis of race records. Journal of Quantitative Analysis in Sports, 8 (4).

Publisher

De Gruyter / © American Statistical Association

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2012

Notes

This article was published in the serial, Journal of Quantitative Analysis in Sports [De Gruyter / © American Statistical Association]. It is also available at: http://dx.doi.org/10.1515/1559-0410.1456

eISSN

1559-0410

Language

  • en