Predictive Modeling of Lower-Level English Club Soccer Using Crowd-Sourced Player Valuations

In this research, we examine the capabilities of different mathematical models to accurately predict various levels of the English football pyramid. Existing work has largely focused on top-level play in European leagues; however, our work analyzes teams throughout the entire English Football League system. We modeled team performance using weighted Colley and Massey ranking methods which incorporate player valuations from the widely-used website Transfermarkt to predict game outcomes. Our initial analysis found that lower leagues are more difficult to forecast in general. Yet, after removing dominant outlier teams from the analysis, we found that top leagues were just as difficult to predict as lower leagues. We also extended our findings using data from multiple German and Scottish leagues. Finally, we discuss reasons to doubt attributing Transfermarkt's predictive value to wisdom of the crowd.

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Published
2025-04-04
DOI
https://doi.org/10.5149/ms.1327
Primary Topic
Sports Analytics and Performance
Type
article
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article

Predictive Modeling of Lower-Level English Club Soccer Using Crowd-Sourced Player Valuations

J. Conway Brown, Samuel Thomas, Amanda Harsy, Yutong Bu et al.
Sports Analytics and Performance
article

Predictive Modeling of Lower-Level English Club Soccer Using Crowd-Sourced Player Valuations

J. Conway Brown, Samuel Thomas, Amanda Harsy, Yutong Bu, Zachary Cheesman, Benjamin Orman, Iris Horng, Adam Schultze
article en

Abstract

In this research, we examine the capabilities of different mathematical models to accurately predict various levels of the English football pyramid. Existing work has largely focused on top-level play in European leagues; however, our work analyzes teams throughout the entire English Football League system. We modeled team performance using weighted Colley and Massey ranking methods which incorporate player valuations from the widely-used website Transfermarkt to predict game outcomes. Our initial analysis found that lower leagues are more difficult to forecast in general. Yet, after removing dominant outlier teams from the analysis, we found that top leagues were just as difficult to predict as lower leagues. We also extended our findings using data from multiple German and Scottish leagues. Finally, we discuss reasons to doubt attributing Transfermarkt's predictive value to wisdom of the crowd.

Vol. 7(1)
Lewis University (US), Bowdoin College (US), Emory University (US), Grinnell College (US), John Brown University (US), Ursinus College (US), California University of Pennsylvania (US)
Openalex Percentile: Top 83%
Sports Analytics and Performance
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Predictive Modeling of Lower-Level English Club Soccer Using Crowd-Sourced Player Valuations — J. Conway Brown, Samuel Thomas, et al. · (2025) | TGRS Research Map | TGRS