Proceedings of the 2024 5th International Conference on Big Data and Social Sciences (ICBDSS 2024)

English Premier League Data Analysis: Insights and Recommendations

Authors
Xinyao Li1, *
1Beijing Normal University (BNU) and Hong Kong Baptist University (HKBU), United International College (UIC), Zhuhai, Guangdong, 519087, China
*Corresponding author. Email: 1469460334@qq.com
Corresponding Author
Xinyao Li
Available Online 13 November 2024.
DOI
10.2991/978-94-6463-562-1_5How to use a DOI?
Keywords
Expected Goals; Expected Goals Against; Pressing Intensity; Opponent Pressing Intensity; Team Performance; English Premier League; Tactical Strategy; Manchester City; Liverpool; Football Analytics
Abstract

This research explores the tactical and statistical patterns of team performance in the English Premier League (EPL). The study focuses on key metrics such as Expected Goals (xG), Expected Goals Against (xGA), and pressing intensities (PPDA and OPPDA) to understand their impact on team success. Analyzing data from Manchester City (MCI) and Liverpool (LIV) for the 2020-2021 and 2021-2022 seasons, the study identifies critical factors that differentiate top-performing teams. The results underscore the role of strategic adjustments in enhancing both offensive and defensive capabilities in the EPL.

Copyright
© 2024 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 2024 5th International Conference on Big Data and Social Sciences (ICBDSS 2024)
Series
Advances in Computer Science Research
Publication Date
13 November 2024
ISBN
978-94-6463-562-1
ISSN
2352-538X
DOI
10.2991/978-94-6463-562-1_5How to use a DOI?
Copyright
© 2024 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

TY  - CONF
AU  - Xinyao Li
PY  - 2024
DA  - 2024/11/13
TI  - English Premier League Data Analysis: Insights and Recommendations
BT  - Proceedings of the 2024 5th International Conference on Big Data and Social Sciences (ICBDSS 2024)
PB  - Atlantis Press
SP  - 37
EP  - 48
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-562-1_5
DO  - 10.2991/978-94-6463-562-1_5
ID  - Li2024
ER  -