Identification and Empirical Analysis of Key Influencing Factors on the Outcomes of Professional Football Matches
Research Article
Open Access
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Identification and Empirical Analysis of Key Influencing Factors on the Outcomes of Professional Football Matches

Jiayang Dong 1*
1 Anhui Normal University
*Corresponding author: Dongjiayang2026@163.com
Published on 2 October 2025
Volume Cover
TNS Vol.132
ISSN (Print): 2753-8826
ISSN (Online): 2753-8818
ISBN (Print): 978-1-80590-305-5
ISBN (Online): 978-1-80590-306-2
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Abstract

In the context of strengthening youth football training nationwide, promoting open and transparent selection of national football players, fostering a healthy football competition environment, advancing the modernization of coach education, improving the construction of the national football team, and comprehensively improving the level of national football, the factors influencing the outcome of football matches have been studied. This study provides scientific data analysis for team training, prompting coaches and players to further improve their personal and team tactical strategies, increase the team's winning rate, and analyze the factors that affect the outcome of football matches. Using key match data from the English Premier League in the DCD app multiple linear regression analysis was performed via SPSS to identify the 12 most critical factors affecting match results. Based on this, practical suggestions were proposed for teams to improve their winning probability from micro to macro levels, including players themselves, coaches, and the General Administration of Sport of China.

Keywords:

Football match, influencing factors, the DCD, multiple linear regression model

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Dong,J. (2025). Identification and Empirical Analysis of Key Influencing Factors on the Outcomes of Professional Football Matches. Theoretical and Natural Science,132,65-74.

References

[1]. Matthew Cole; Jennie L Carter; Frances Brooks; Charlie J Roberts(2025).Caregivers nutrition knowledge and perspectives on the enablers and barriers to nutrition provision for male academy football players.Journal of the International Society of Sports Nutrition, 22.

[2]. Gygax, Pascal M; Wagner-Egger, Pascal; Parris, Ben; Seiler, Roland; Hauert, Claude-Alain(2008).A psycholinguistic investigation of football players' mental representations of game situations: Does expertise count?  European Journal of Psychology Open, 67.

[3]. Liu Yang.A cognitive study on the home and away effects of Chinese men's professional football league players [D]. Shanxi University, 2024.

[4]. Han Zhe.Research on home advantage in the second leg of the UEFA Champions League and Europa League [D]. Southwest University of Finance and Economics, 2023.

[5]. Yin Xiaochuan.Research on the influencing factors of home advantage in China's Jia A Football League [C]. Chinese Psychological Association Selected Abstracts from the 8th National Conference on Psychology Beijing Institute of Physical Education; , 1997: 233.

[6]. Jinmo Lee; Eunil Park; Angel P. del Pobil(2025)We know who wins: graph-oriented approaches of passing networks for predictive football match outcomes.Journal of Big Data, 12.

[7]. Ma Xiaoni.Analysis of Influencing Factors on the Results of Chinese Super League Matches in the 2009-2018 Season [D]. Capital Institute of Physical Education, 2020.

[8]. Saragih Joe Pratama; Widodo Achmad; Bawono Mokhamad Nur; Firmansyah Awang(2025).Analysis of The Playing Technique Skills of The English Manchester City Football Club in Winning The UEFA Champions League Title for The 2022–2023 Season.Proceedings of the International Seminar of Sport and Exercise Science, 14-19.

[9]. Fernando Leiva Bertrán(2025), Ranking in Incomplete Tournaments: The Generalized Win Percentage Method, Efficiency, and NCAA Football.Journal of Sports EconomicsVolume 26, 3-34.

[10]. Hill S. E.(2022).In-game win probability models for Canadian football.Journal of Business Analytics, 5, 164-178

[11]. Gamble Declan; McCarren Andrew; Bradley Jonathan; Moyna Niall(2020), Novel component variables can be used to distinguish between winning and losing across match periodsin elite Gaelic football.International Journal of Performance Analysis in Sport, 20, 264-279.

[12]. Lionel Frost; Luc Borrowman; Vinod Mishra; Abdel K. Halabi(2019).Stadium construction and the distribution of winning percentages in the English and Scottish football leagues, 1888-89 to 1938-9.Historical Perspectives on Sports Economics: Lessons from the Field, 37-51.

[13]. Gamble; Bradley; McCarren; Moyna(2019).Team performance indicators which differentiate between winning and losing in elite Gaelic football.International Journal of Performance Analysis in Sport, 19, 478-490.

[14]. Silvestri R.; D'isanto T.; Izzo R.; Di Domenico F.(2019).The winning shares in the major football leagues.Journal of Human Sport and Exercise, 14, S631-S637.

[15]. Cheng Kang.Research on the Model Construction of Winning Factors in the Chinese Football Super League [D]. Shaanxi Normal University, 2021.

[16]. Li Chunhua.Analysis of Winning Factors in the 2019 Chinese Football Association Super League [J]. Sports Excellence, 2022, 41 (7): 93-95

[17]. Hu Guangming.Technical continuity and relative advantages of teams that have won consecutive championships in the five major European football leagues [D]. Fujian Normal University, 2021.

[18]. Par Prateek; Kumar Gupt Ankit; Singh Samarth; Khare Neelu; Bhattachrya Sweta(2017).Football league win prediction based on online and league table data.IOP Conference Series: Materials Science and Engineering, 263.

[19]. Sigrid Olthof; Jesse Davis(2025).Perspectives on data analytics for gaining a competitive advantage in football: computational approaches to tactics.Science and Medicine in Football.

[20]. Xu Lulu.Quantitative Study on Factors Influencing the Performance of Chinese Super League Teams [D]. Shanghai Normal University, 2020.

[21]. Tahir Sheikh Badar Ud Din(2025).A Comparative and Statistical Analysis of xG to Predict Football Shot Outcomes in Event Data.Statistics for Innovation I: SIS 2025, Short Papers, Plenary, Specialized, and Solicited Sessions, 408-414.

[22]. Mohamed Elsharkawi; Raja Hashim Ali; Talha Ali Khan(2025).Crafting a Player Impact Metric through analysis of football match event data.Journal of Computational Mathematics and Data Science, 15.

[23]. Victor Chang; Sreeram Sajeev; Qianwen Ariel Xu; Mengmeng Tan; Hai Wang(2024).Football Analytics: Assessing the Correlation between Workload, Injury and Performance of Football Players in the English Premier League.Applied Sciences, 14.

[24]. Brager Allison J; Mistovich R Justin(2017).Game Times and Higher Winning Percentages of West Coast Teams of the National Football League Correspond With Reduced Prevalence of Regular Season Injury.Journal of Strength and Conditioning Research, 31, 462-467.

[25]. Brigitte, Nana; André, Kaboré; Gnynayen Xavier, Ziba(2024).Emotional Analysis of First Division Football Referees in Burkina Faso during Matches.Journal of Psychology & Behavior Research, 6.

References

[1]. Matthew Cole; Jennie L Carter; Frances Brooks; Charlie J Roberts(2025).Caregivers nutrition knowledge and perspectives on the enablers and barriers to nutrition provision for male academy football players.Journal of the International Society of Sports Nutrition, 22.

[2]. Gygax, Pascal M; Wagner-Egger, Pascal; Parris, Ben; Seiler, Roland; Hauert, Claude-Alain(2008).A psycholinguistic investigation of football players' mental representations of game situations: Does expertise count?  European Journal of Psychology Open, 67.

[3]. Liu Yang.A cognitive study on the home and away effects of Chinese men's professional football league players [D]. Shanxi University, 2024.

[4]. Han Zhe.Research on home advantage in the second leg of the UEFA Champions League and Europa League [D]. Southwest University of Finance and Economics, 2023.

[5]. Yin Xiaochuan.Research on the influencing factors of home advantage in China's Jia A Football League [C]. Chinese Psychological Association Selected Abstracts from the 8th National Conference on Psychology Beijing Institute of Physical Education; , 1997: 233.

[6]. Jinmo Lee; Eunil Park; Angel P. del Pobil(2025)We know who wins: graph-oriented approaches of passing networks for predictive football match outcomes.Journal of Big Data, 12.

[7]. Ma Xiaoni.Analysis of Influencing Factors on the Results of Chinese Super League Matches in the 2009-2018 Season [D]. Capital Institute of Physical Education, 2020.

[8]. Saragih Joe Pratama; Widodo Achmad; Bawono Mokhamad Nur; Firmansyah Awang(2025).Analysis of The Playing Technique Skills of The English Manchester City Football Club in Winning The UEFA Champions League Title for The 2022–2023 Season.Proceedings of the International Seminar of Sport and Exercise Science, 14-19.

[9]. Fernando Leiva Bertrán(2025), Ranking in Incomplete Tournaments: The Generalized Win Percentage Method, Efficiency, and NCAA Football.Journal of Sports EconomicsVolume 26, 3-34.

[10]. Hill S. E.(2022).In-game win probability models for Canadian football.Journal of Business Analytics, 5, 164-178

[11]. Gamble Declan; McCarren Andrew; Bradley Jonathan; Moyna Niall(2020), Novel component variables can be used to distinguish between winning and losing across match periodsin elite Gaelic football.International Journal of Performance Analysis in Sport, 20, 264-279.

[12]. Lionel Frost; Luc Borrowman; Vinod Mishra; Abdel K. Halabi(2019).Stadium construction and the distribution of winning percentages in the English and Scottish football leagues, 1888-89 to 1938-9.Historical Perspectives on Sports Economics: Lessons from the Field, 37-51.

[13]. Gamble; Bradley; McCarren; Moyna(2019).Team performance indicators which differentiate between winning and losing in elite Gaelic football.International Journal of Performance Analysis in Sport, 19, 478-490.

[14]. Silvestri R.; D'isanto T.; Izzo R.; Di Domenico F.(2019).The winning shares in the major football leagues.Journal of Human Sport and Exercise, 14, S631-S637.

[15]. Cheng Kang.Research on the Model Construction of Winning Factors in the Chinese Football Super League [D]. Shaanxi Normal University, 2021.

[16]. Li Chunhua.Analysis of Winning Factors in the 2019 Chinese Football Association Super League [J]. Sports Excellence, 2022, 41 (7): 93-95

[17]. Hu Guangming.Technical continuity and relative advantages of teams that have won consecutive championships in the five major European football leagues [D]. Fujian Normal University, 2021.

[18]. Par Prateek; Kumar Gupt Ankit; Singh Samarth; Khare Neelu; Bhattachrya Sweta(2017).Football league win prediction based on online and league table data.IOP Conference Series: Materials Science and Engineering, 263.

[19]. Sigrid Olthof; Jesse Davis(2025).Perspectives on data analytics for gaining a competitive advantage in football: computational approaches to tactics.Science and Medicine in Football.

[20]. Xu Lulu.Quantitative Study on Factors Influencing the Performance of Chinese Super League Teams [D]. Shanghai Normal University, 2020.

[21]. Tahir Sheikh Badar Ud Din(2025).A Comparative and Statistical Analysis of xG to Predict Football Shot Outcomes in Event Data.Statistics for Innovation I: SIS 2025, Short Papers, Plenary, Specialized, and Solicited Sessions, 408-414.

[22]. Mohamed Elsharkawi; Raja Hashim Ali; Talha Ali Khan(2025).Crafting a Player Impact Metric through analysis of football match event data.Journal of Computational Mathematics and Data Science, 15.

[23]. Victor Chang; Sreeram Sajeev; Qianwen Ariel Xu; Mengmeng Tan; Hai Wang(2024).Football Analytics: Assessing the Correlation between Workload, Injury and Performance of Football Players in the English Premier League.Applied Sciences, 14.

[24]. Brager Allison J; Mistovich R Justin(2017).Game Times and Higher Winning Percentages of West Coast Teams of the National Football League Correspond With Reduced Prevalence of Regular Season Injury.Journal of Strength and Conditioning Research, 31, 462-467.

[25]. Brigitte, Nana; André, Kaboré; Gnynayen Xavier, Ziba(2024).Emotional Analysis of First Division Football Referees in Burkina Faso during Matches.Journal of Psychology & Behavior Research, 6.

Cite this article

Dong,J. (2025). Identification and Empirical Analysis of Key Influencing Factors on the Outcomes of Professional Football Matches. Theoretical and Natural Science,132,65-74.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-APMM 2025 Symposium: Simulation and Theory of Differential-Integral Equation in Applied Physics

ISBN: 978-1-80590-305-5(Print) / 978-1-80590-306-2(Online)
Editor: Marwan Omar, Shuxia Zhao
Conference website: https://www.confapmm.org/dalian.html
Conference date: 27 September 2025
Series: Theoretical and Natural Science
Volume number: Vol.132
ISSN: 2753-8818(Print) / 2753-8826(Online)

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