Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)

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Data Analysis of Middle Distance Running Strategy Based on Binary Discrete Choice Model

Authors
Tingting Zheng1, Xi Yang1, Shanwen Cao2, *
1School of Economics and Management, North China University of Technology, Beijing, China
2China Unicom Research Institute, Beijing, China
*Corresponding author. Email: 1182894876@qq.com
Corresponding Author
Shanwen Cao
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-064-0_51How to use a DOI?
Keywords
middle-distance running; pace strategy; binary discrete selection model
Abstract

Through video analysis, this paper establishes the database of the pace strategy of distance runners in the 2008–2019 World Championships and the final of the Olympic Games. Combined with the econometric binary discrete selection model, this paper analyzes the differences between the self pace strategy, team strategy, the pace strategy of award-winning athletes and non award-winning athletes, and the pace strategy of male and female athletes. The results show that: 1) In the middle distance running, high-level athletes prefer to adopt the leading running strategy, whether there is team cooperation or not. 2) In 1500 m, athletes with 4–2 tactics (the speed ratio of the last 400 m is the highest and the speed ratio of the second 400 m is the lowest) are more likely to win medals; but athletes who adopt 1–2 tactics (the speed ratio of the first 400 m is the highest and the speed ratio of the second 400 m is the lowest) are more likely to win the medals in 800 m; 3) In the 1500 m events, the overall pace of male athletes is more even than female athletes.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-064-0_51
ISSN
2589-4900
DOI
10.2991/978-94-6463-064-0_51How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Tingting Zheng
AU  - Xi Yang
AU  - Shanwen Cao
PY  - 2022
DA  - 2022/12/27
TI  - Data Analysis of Middle Distance Running Strategy Based on Binary Discrete Choice Model
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 496
EP  - 504
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_51
DO  - 10.2991/978-94-6463-064-0_51
ID  - Zheng2022
ER  -