Short-Term Speed Variability as an Index of Pacing Stochasticity in Athletic Running Events

Daniel Boullosa; Eliésdras Patrocínio; Andrew Renfree; Arturo Casado; Brian Hanley; Carl Foster

doi:10.3390/jfmk8020086

Short-Term Speed Variability as an Index of Pacing Stochasticity in Athletic Running Events

J Funct Morphol Kinesiol. 2023 Jun 19;8(2):86. doi: 10.3390/jfmk8020086.

Authors

Daniel Boullosa^{1

2

3}, Eliésdras Patrocínio², Andrew Renfree⁴, Arturo Casado⁵, Brian Hanley⁶, Carl Foster⁷

Affiliations

¹ Faculty of Physical Activity and Sports Sciences, Universidad de León, 24007 León, Spain.
² Graduate Program in Movement Sciences, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil.
³ College of Healthcare Sciences, James Cook University, Townsville 4811, Australia.
⁴ Institute of Sport and Exercise Science, University of Worcester, Worcester WR2 6AJ, UK.
⁵ Centre for Sport Studies, Rey Juan Carlos University, 28933 Madrid, Spain.
⁶ Carnegie School of Sport, Leeds Beckett University, Leeds LS6 3QS, UK.
⁷ Department of Exercise and Sports Science, University of Wisconsin-La Crosse, La Crosse, WI 54601, USA.

Abstract

We aimed to compare differences in performance and pacing variability indices between 5000 m heats and finals during major championships in men and women. Data with 100 m time resolution were used to compare overall pacing variability (standard deviation of 100 m section times, SD; and coefficient of variation, CV%) and short-term pacing variability (root mean square of successive differences between 100 m section times, RMSSD). The changes in performance and pacing indices differed between races and competitions. For instance, the men's final in Beijing 2008 was quicker than the heat (p < 0.01) while the CV% was reduced (p = 0.03) and RMSSD increased (p < 0.01). For women, the heats and the final exhibited a similar mean time in London 2017 (p = 0.33) but with CV% (p < 0.001) and RMSSD (p < 0.001) showing opposite trends. Individual analyses of men's and women's champions revealed highly individual variability metrics. The use of RMSSD can complement overall variability indices for better characterization of pacing stochasticity.

Keywords: aerobic endurance; aerobic performance; athletics; endurance running.

Grants and funding

DB was supported by Grant RYC2021-031098-I funded by MCIN/AEI/10.13039/501100011033, by “European Union NextGenerationEU/PRTR”, and by a productivity research grant (PQ1D) from CNPq (Brazil).