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Relative importance of pacing strategy and mean power output in 1500-m self-paced cycling
  1. Florentina J Hettinga1,*,
  2. Jos J De Koning2,
  3. Michiel Hulleman2,
  4. Carl Foster3
  1. 1 Center of Human Movement Sciences, University Medical Center Groningen/ University of Groningen, Netherlands;
  2. 2 Research Institute MOVE, Faculty of Human Movement Sciences, VU University Amsterdam, Netherlands;
  3. 3 Department of Exercise and Sports Science, University of Wisconsin-LaCrosse, Netherlands
  1. Correspondence to: Florentina J Hettinga, Center for Human Movement Sciences, University Medical Center Groningen/ University of Groningen, Center for Human Movement Sciences (UMCG/RUG), Antonius Deusinglaan 1, Sector F; Building 3215, Rm 0330, Groningen, 9713AV, Netherlands; f.j.hettinga{at}med.umcg.nl

Abstract

Introduction: Both mean power output and the distribution of the available energy over the race, i.e. pacing strategy, are critical factors in performance. The purpose of this study was to determine the relative importance of both pacing strategy and mean power output to performance.

Methods: Six well-trained, regionally competitive cyclists performed four 1500-m ergometer time trials (~2min). For each subject, the fastest (Fast) and slowest (Slow) time trials were compared and the relative importance of differences in power output and pacing strategy were determined with an energy flow model.

Results: The difference in final time between Fast and Slow was 4.0 ± 2.5s. Fast was performed with a higher mean power output (437.8 ± 32.3 vs 411.3 ± 39.0W), a higher aerobic peak power (295.3 ± 36.8 vs 287.5 ± 34.7W) and a higher anaerobic peak power (828.8 ± 145.4 vs 649.5 ± 112.2W) combined with a relatively higher, but not statistically different anaerobic rate constant (0.051 ± 0.016 vs 0.041 ± 0.009W). The changes in mean power output (63% anaerobic, 37% aerobic) largely explained the differences in final times. Athletes chose a different pacing strategy which was close to optimal for their physiological condition in both Fast and Slow.

Conclusion: Differences in intra-individual performance were mainly caused by differences in mean power output. Athletes seemed to be able to effectively adjust their pacing profile based on their ‘status of the day’.

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