<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Wushu sparring is an important part of Chinese multi-sports, and the athletic performance of wushu sparring athletes has a crucial role in Chinese wushu sparring performance. In this paper, the relationship between athletes’ performance and the training load of wushu sparring athletes was investigated using gray correlation analysis, with wushu sparring athletes as the research object. According to the relevant standards to establish and determine the objective indicators to measure the performance of wushu sparring athletes, at the same time, the group of athletes with different intensity training experiments, the use of gray correlation analysis based on the data obtained from the training to calculate the gray correlation between the athlete’s performance and their training load, and as a basis for the establishment of the gray rule model through the GM (1, 1) algorithm. The relationship between training load and athlete performance was evaluated to correlate up to 0.975, and the algorithm’s model was 88% accurate in predicting athlete performance based on training intensity. The study of the relationship between training load and athletes’ performance can aid wushu sparring athletes in rationally scheduling their training intensity, which is crucial for the development of Chinese wushu sparring.</p>
</abstract>

Wushu sparring is an important part of Chinese multi-sports, and the athletic performance of wushu sparring athletes has a crucial role in Chinese wushu sparring performance. In this paper, the relationship between athletes’ performance and the training load of wushu sparring athletes was investigated using gray correlation analysis, with wushu sparring athletes as the research object. According to the relevant standards to establish and determine the objective indicators to measure the performance of wushu sparring athletes, at the same time, the group of athletes with different intensity training experiments, the use of gray correlation analysis based on the data obtained from the training to calculate the gray correlation between the athlete’s performance and their training load, and as a basis for the establishment of the gray rule model through the GM (1, 1) algorithm. The relationship between training load and athlete performance was evaluated to correlate up to 0.975, and the algorithm’s model was 88% accurate in predicting athlete performance based on training intensity. The study of the relationship between training load and athletes’ performance can aid wushu sparring athletes in rationally scheduling their training intensity, which is crucial for the development of Chinese wushu sparring.

Relationship between athlete performance and training load in martial arts sparring: based on a gray rule model

Department of Physical & Military Education

Hainan Vocational University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Wushu sparring is an important part of Chinese multi-sports, and the athletic performance of wushu sparring athletes has a crucial role in Chinese wushu...

Relationship between athlete performance and training load in martial arts sparring: based on a gray rule model

Published Online: Jul 05, 2024

Page range: -

Received: Mar 01, 2024

Accepted: May 27, 2024

DOI: https://doi.org/10.2478/amns-2024-1596

Keywords
martial arts, training load, gray rule model, correlation coefficient

© 2024 Zhongsheng Fu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Relationship between athlete performance and training load in martial arts sparring: based on a gray rule model

Published Online: Jul 05, 2024

Page range: -

Received: Mar 01, 2024

Accepted: May 27, 2024

DOI: https://doi.org/10.2478/amns-2024-1596

Keywordsmartial arts, training load, gray rule model, correlation coefficient

© 2024 Zhongsheng Fu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
martial arts, training load, gray rule model, correlation coefficient