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Methodological approaches to determine the “U”-pacing strategy in cycling time trial

Author

Listed:
  • Rafael Azevedo
  • Ramon Cruz
  • Marcos Silva-Cavalcante
  • Renata Silva
  • Carlos Correia-Oliveira
  • Patrícia Couto
  • Adriano Lima-Silva
  • Romulo Bertuzzi

Abstract

The present study proposed two models (visual and mathematical) to determine the three phases of “U”-pacing profile during a cycling time trial. The reliability of visual model was tested and models were compared. Fifteen cyclists performed a maximal incremental test and two 4-km TT. For the visual model, four experienced evaluators analysed twice the pacing, seven days apart. The mathematical model consisted on the mean of power output during phase 2 (1- until 3 km) plus two standard deviations, to distinguish phase 2 change points between phases 1 (CP1) and 3 (CP2). The CP1 occurred at 419 ± 186 and 415 ± 178 m for visual and mathematical model and CP2 occurred at 3646 ± 228 and 3809 ± 213 m, respectively. There was no difference between models for both CP (p <0.05). The within-evaluator visual model reliability for CP1 was ICC >0.87 and CP2 was ICC >0.96 (p <0.05), and between-evaluator reliability was ICC > 0.89 (p <0.05). Bland–Altman plots showed agreement between models, most the difference was <5%. The visual and mathematical models are reliable and produce similar values for determining main phases of the “U”-pacing profile during a cycling TT.

Suggested Citation

  • Rafael Azevedo & Ramon Cruz & Marcos Silva-Cavalcante & Renata Silva & Carlos Correia-Oliveira & Patrícia Couto & Adriano Lima-Silva & Romulo Bertuzzi, 2017. "Methodological approaches to determine the “U”-pacing strategy in cycling time trial," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 17(5), pages 752-762, September.
  • Handle: RePEc:taf:rpanxx:v:17:y:2017:i:5:p:752-762
    DOI: 10.1080/24748668.2017.1399322
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    References listed on IDEAS

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    1. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
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