Football is the most famous sports in the world, and English Premier League is the number one league in the world for three consecutive years (Fédération internationale de football association, FIFA). It is always interesting to apply technical analysis to understand what makes the best football player and football team. In this article, we try to answer the question "what kind of tactical play is the most advanced" through statistical analysis on the game data of English Premier League in the 21-22 season. To be more specific, firstly, we applied descriptive statistics to analyze the technical and tactical play of each team, and then screen out the technical and tactical indicators that significantly affect the outcome of the game through one-way analysis of variance (ANOVA) and discriminate analysis, and the preliminary target conclusions were obtained. BP neural network was then carried out to predict the rankings of the Premier League teams by using the indicators selected by ANOVA and discriminant analysis, as input value. BP neural network prediction model is then established to predict the ranking of each team in the 22-23 season. A general conclusion and make suggestions on the planning of the technical and tactical playing methods of our country's youth soccer sports.
| Published in | International Journal of Education, Culture and Society (Volume 9, Issue 2) |
| DOI | 10.11648/j.ijecs.20240902.12 |
| Page(s) | 60-67 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
English Premier League, One-way ANOVA, Discriminant Analysis, BP Neural Network
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APA Style
Li, Z. (2024). Neural Network Based Technical Analysis of Football Games. International Journal of Education, Culture and Society, 9(2), 60-67. https://doi.org/10.11648/j.ijecs.20240902.12
ACS Style
Li, Z. Neural Network Based Technical Analysis of Football Games. Int. J. Educ. Cult. Soc. 2024, 9(2), 60-67. doi: 10.11648/j.ijecs.20240902.12
AMA Style
Li Z. Neural Network Based Technical Analysis of Football Games. Int J Educ Cult Soc. 2024;9(2):60-67. doi: 10.11648/j.ijecs.20240902.12
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Download@article{10.11648/j.ijecs.20240902.12,
author = {Zhaojun Li},
title = {Neural Network Based Technical Analysis of Football Games},
journal = {International Journal of Education, Culture and Society},
volume = {9},
number = {2},
pages = {60-67},
doi = {10.11648/j.ijecs.20240902.12},
url = {https://doi.org/10.11648/j.ijecs.20240902.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijecs.20240902.12},
abstract = {Football is the most famous sports in the world, and English Premier League is the number one league in the world for three consecutive years (Fédération internationale de football association, FIFA). It is always interesting to apply technical analysis to understand what makes the best football player and football team. In this article, we try to answer the question "what kind of tactical play is the most advanced" through statistical analysis on the game data of English Premier League in the 21-22 season. To be more specific, firstly, we applied descriptive statistics to analyze the technical and tactical play of each team, and then screen out the technical and tactical indicators that significantly affect the outcome of the game through one-way analysis of variance (ANOVA) and discriminate analysis, and the preliminary target conclusions were obtained. BP neural network was then carried out to predict the rankings of the Premier League teams by using the indicators selected by ANOVA and discriminant analysis, as input value. BP neural network prediction model is then established to predict the ranking of each team in the 22-23 season. A general conclusion and make suggestions on the planning of the technical and tactical playing methods of our country's youth soccer sports.
},
year = {2024}
}
TY - JOUR T1 - Neural Network Based Technical Analysis of Football Games AU - Zhaojun Li Y1 - 2024/03/25 PY - 2024 N1 - https://doi.org/10.11648/j.ijecs.20240902.12 DO - 10.11648/j.ijecs.20240902.12 T2 - International Journal of Education, Culture and Society JF - International Journal of Education, Culture and Society JO - International Journal of Education, Culture and Society SP - 60 EP - 67 PB - Science Publishing Group SN - 2575-3363 UR - https://doi.org/10.11648/j.ijecs.20240902.12 AB - Football is the most famous sports in the world, and English Premier League is the number one league in the world for three consecutive years (Fédération internationale de football association, FIFA). It is always interesting to apply technical analysis to understand what makes the best football player and football team. In this article, we try to answer the question "what kind of tactical play is the most advanced" through statistical analysis on the game data of English Premier League in the 21-22 season. To be more specific, firstly, we applied descriptive statistics to analyze the technical and tactical play of each team, and then screen out the technical and tactical indicators that significantly affect the outcome of the game through one-way analysis of variance (ANOVA) and discriminate analysis, and the preliminary target conclusions were obtained. BP neural network was then carried out to predict the rankings of the Premier League teams by using the indicators selected by ANOVA and discriminant analysis, as input value. BP neural network prediction model is then established to predict the ranking of each team in the 22-23 season. A general conclusion and make suggestions on the planning of the technical and tactical playing methods of our country's youth soccer sports. VL - 9 IS - 2 ER -
School of Data Sciences, Zhejiang University of Finance and Economics, Hangzhou, China
