The evolution of the European football transfer network

In the present paper, we construct a network that represents the football transfer market in the seasons from 2009/10 to 2021/22 in the 7 top European leagues. The goal is to identify both the large-scale structure of the transfer network, network analysis and anomalous behaviors of individual clubs. We use different approaches to encode in the network the monetary value of the transfers and the temporal evolution of the network, using data collected from the website Transfermarkt. When we consider the cost of each transfer, the most central clubs in the network are the richest and most successful at the international level, which form their own community. Instead, when all transfers are considered equal, the most central clubs are the smaller ones, and the communities faithfully reconstruct the national leagues. Further, we are able to identify peculiar behaviours of individual clubs and small groups of clubs under the same ownership.

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Publication Details

Journal
Journal Of Big Data
Published
2025-11-14
DOI
https://doi.org/10.1186/s40537-025-01275-7
Primary Topic
Sports Analytics and Performance
Type
article
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article

The evolution of the European football transfer network

Livia De Giovanni, Lorenzo Federico, Pierpaolo D’Urso
Journal Of Big Data
Sports Analytics and Performance
article

The evolution of the European football transfer network

Livia De Giovanni, Lorenzo Federico, Pierpaolo D’Urso
article en

Abstract

In the present paper, we construct a network that represents the football transfer market in the seasons from 2009/10 to 2021/22 in the 7 top European leagues. The goal is to identify both the large-scale structure of the transfer network, network analysis and anomalous behaviors of individual clubs. We use different approaches to encode in the network the monetary value of the transfers and the temporal evolution of the network, using data collected from the website Transfermarkt. When we consider the cost of each transfer, the most central clubs in the network are the richest and most successful at the international level, which form their own community. Instead, when all transfers are considered equal, the most central clubs are the smaller ones, and the communities faithfully reconstruct the national leagues. Further, we are able to identify peculiar behaviours of individual clubs and small groups of clubs under the same ownership.

Journal Of Big DataVol. 12(1)
Libera Università Internazionale degli Studi Sociali Guido Carli (IT), Sapienza University of Rome (IT)
Openalex Percentile: Top 58%
Sports Analytics and Performance
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