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The Value of Meteorological Data in Optimizing the Pattern of Physical Load—A Forecast Model of Rowing Pacing Strategy

Author

Listed:
  • Tian Yan

    (Division of Sports Science and Physical Education, North China University of Science and Technology, Tangshan 063210, China)

  • Xiaodong Zhu

    (Division of Sports Science and Physical Education, Tsinghua University, Beijing 100084, China)

  • Xuesong Ding

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Liming Chen

    (Division of Sports Science and Physical Education, Tangshan Polytechnic College, Tangshan 063299, China)

Abstract

Mastering the information of arena environment is the premise for athletes to optimize their patterns of physical load. Therefore, improving the forecast accuracy of the arena conditions is an urgent task in competitive sports. This paper excavates the meteorological features that have great influence on outdoor events such as rowing and their influence on the pacing strategy. We selected the meteorological data of Tokyo from 1979 to 2020 to forecast the meteorology during the Tokyo 2021 Olympic Games, analyzed the athletes’ pacing choice under different temperatures, humidity and sports levels, and then recommend the best pacing strategy for rowing teams of China. The model proposed in this paper complements the absence of meteorological features in the arena environment assessment and provides an algorithm basis for improving the forecast performance of pacing strategies in outdoor sports.

Suggested Citation

  • Tian Yan & Xiaodong Zhu & Xuesong Ding & Liming Chen, 2021. "The Value of Meteorological Data in Optimizing the Pattern of Physical Load—A Forecast Model of Rowing Pacing Strategy," IJERPH, MDPI, vol. 19(1), pages 1-17, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:320-:d:713462
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    References listed on IDEAS

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    4. Marcos Chena & José Alfonso Morcillo & María Luisa Rodríguez-Hernández & Juan Carlos Zapardiel & Adam Owen & Demetrio Lozano, 2021. "The Effect of Weekly Training Load across a Competitive Microcycle on Contextual Variables in Professional Soccer," IJERPH, MDPI, vol. 18(10), pages 1-10, May.
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