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ORIGINAL RESEARCH article

Front. Physiol.
Sec. Exercise Physiology
Volume 16 - 2025 | doi: 10.3389/fphys.2025.1429510
This article is part of the Research Topic Assessment and Monitoring of Human Movement View all 35 articles

The Impact of Pre-Competition State on Athletic Performance among Track and Field Athletes Using Machine Learning

Provisionally accepted
Yuting ZHANG Yuting ZHANG 1Qi Yu Qi Yu 1*Pengyu Fu Pengyu Fu 1*Dongfeng Nie Dongfeng Nie 1*Qingmei NIU Qingmei NIU 1*Xiaoqin Zhang Xiaoqin Zhang 2*Xiangya Dou Xiangya Dou 1*
  • 1 Northwestern Polytechnical University, Xi'an, China
  • 2 Shaanxi University of Technology, Hanzhong, Shaanxi, China

The final, formatted version of the article will be published soon.

    Objective:Athletes' performance in competition is affected by their pre-competition status.A comprehensive assessment of college track and field athletes' pre-competition status using machine learning algorithms to explore its relationship with competition performance.Methods:Multi-indicators and multi-methods to detect exercise load, fatigue index and pre-match status of athletes with different sports performance.Results:(1)During two weeks prior to the competition,Fat Mass in The Left Upper Limb was significantly higher in the BP group than BnP group(P<0.05); the Absolute Value of Blood Basophils and the Triglyceride were significantly higher in the BnP group than BP group(P<0.05); the positive detection rate of Urinary Leukocytes was higher in the BnP group than BP group, and the positive detection rate of Urinary Occult Blood and VitaminC were higher in the BP group than BnP group.(2)During one weeks prior to the competition, the Blood Lactate Dehydrogenase in the BP group was significantly higher than BnP group(P<0.05);the detection rate of positive Urinary OccultBlood in the BnP group was higher than BP group (P<0.05).(3)There were no significant differences in the daily dietary intake,energy consumption values, physical activity, sleep efficiency,real-time heart rate, real-time respiratory rate, and real-time heart rate variability between the intensive and reduced periods.(4)The Rosenberg Self-Esteem Scale was significantly higher in the BnP group than BP group (P<0.05).Conclusions: Pre-Competition blood and urine indexes, psychology, and body composition may have an impact on the changes of athlete performance.It can be used as a training monitoring indicator that focuses on tracking before the race.Machine algorithms are informative in assessing pre-match status indicators and predicting race performance, and similar problems can be assessed with the help of machine learning.

    Keywords: Track and field athletes1, Pre-competition status2, Competition performance3, machine learning, training monitoring

    Received: 08 May 2024; Accepted: 08 Jan 2025.

    Copyright: © 2025 ZHANG, Yu, Fu, Nie, NIU, Zhang and Dou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Qi Yu, Northwestern Polytechnical University, Xi'an, China
    Pengyu Fu, Northwestern Polytechnical University, Xi'an, China
    Dongfeng Nie, Northwestern Polytechnical University, Xi'an, China
    Qingmei NIU, Northwestern Polytechnical University, Xi'an, China
    Xiaoqin Zhang, Shaanxi University of Technology, Hanzhong, Shaanxi, China
    Xiangya Dou, Northwestern Polytechnical University, Xi'an, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.