Education, Science, Technology, Innovation and Life
Open Access
Sign In

Research on the Exploration of the Big Data Technology Application in Athletic Training

Download as PDF

DOI: 10.23977/jhms.2023.040105 | Downloads: 9 | Views: 338

Author(s)

Mu Xu 1

Affiliation(s)

1 Shanghai University of Sport, Shanghai, China

Corresponding Author

Mu Xu

ABSTRACT

With the passage of time and the gradual refinement of big data technology, the ubiquitous utilization of big data has permeated industries such as finance, education, and industry alike. The exponential pace of the development of big data technology has consequently exerted an unprecedented impact on the realm of athletic training, thus making the marriage of big data technology and athletic training an inexorable trend. This study, employing research methodologies encompassing literature review, logical analysis, as well as on-site observation, aims to ponder the implications of the application of big data technology in athletic training, commencing from the distinctive characteristics of the era of big data. The investigation unfolds by delving into the assimilation of big data technology in athlete talent selection, the athlete training process, in addition to the realm of athletic competitions.

KEYWORDS

Big data technology, athletic training, applied inquiry, athlete selection, athletic competition

CITE THIS PAPER

Mu Xu, Research on the Exploration of the Big Data Technology Application in Athletic Training. Journal of Human Movement Science (2023) Vol. 4: 22-27. DOI: http://dx.doi.org/10.23977/jhms.2023.040105.

REFERENCES

[1] Yang Lin, Cui Xinghe, Hui Xiao, et al. (2022) The Incorporation of Big Data Technology in Sports. China Bandy Association, Macao Fitness Association, Guangdong Fitness Association. Proceedings of the 7th China Fitness Training Science Conference. [Publisher unknown], 2022: 5. DOI: 10.26914/c.cnkihy.2022.054835.
[2] Dai Changzheng, Bao Jing. (2017) Digital Governance——A Perspective from Social Form Evolvement. Chinese Public Administration, No. 387 (09): 21-27.
[3] Zhou Wenbiao. (2021) Research on the Development Strategy of Sports Training in Colleges and Universities in China. Contemporary Sports Technology, 11 (29): 54-57. DOI: 10.16655/j.cnki.2095-2813.2103-1579-4938.
[4] Tian Maijiu. (2017) Sports Training, Higher Education Press.
[5] Yu Zhusheng, Shen Xunzhang, Zhu Xuelei. (2006) Scientific Talent Selection for Athletes. Shanghai: Shanghai University of Traditional Chinese Medicine Press.
[6] Ma Guoquan, Yang Jianwen, Zhang Huxiang, et al. (2015) Applications and Thoughts of Big Data in Sport Science. Journal of Hebei Sport University, 29 (02): 11-16.
[7] Hong Wei, Li Qinglin, Ma Yongshuai, et al. (2016) Application of Psychological Indicators in Basketball Talent Selection. Contemporary Sports Technology, 6 (18): 17-18. DOI: 10.16655/j.cnki.2095-2813.2016.18.017.
[8] Yang Bin. (2018) Construction of campus football athletes selection mode in big data environment. Automation & Instrumentation, No. 225 (07): 39-41. DOI: 10.14016/j.cnki.1001-9227.2018.07.039.
[9] Wang Qi, Yan Xiaoyan. (2016) Opportunities and Challenges for China's Sports Development in the Era of Big Data. Sports and Science, 37 (01): 75-80+86. DOI: 10.13598/j.issn1004-4590.2016.01.012.
[10] Qin Yuke, Sun Hao. (2023) Scientific Research on Sports Training under the Big Data Era. Science & Technology of Stationery & Sporting Goods, No. 517 (12): 129-131.
[11] Liu Hengyuan, Liu Zhiyun, Ha Jianwei, et al. (2020) Characteristics, Influential Factors and Monitoring Strategies of Rugby Injuries. Journal of Wuhan Institute of Physical Education, 54 (05): 75-81. DOI: 10.15930/j. cnki. wtxb. 2020.05.011.
[12] Di Xiaorui, Liu Shengjie. (2020) Research on School Track and Field Development in the Era of Big Data. Track and Field, 2020 (04): 38-40+35.
[13] Liu Qi, He Xinsen. (2015) The Development Strategies of Competitive Sports System in the Age of Big Data. Journal of Capital University of Physical Education and Sports, 27 (02): 156-159. DOI: 10.14036/j.cnki.cn11-4513.2015.02.013.

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.