In this work we analyse the global soccer player transfer market providing a network approach that takes into account both the number of transfers and the related costs for football players in the world market. We propose a community detection methodology that considers different features of the network. We cluster countries according to similarities in their roles in the transfer market and to the presence of indirect connections due to common neighbours. Numerical results show a strict relation between the composition of clusters and the economic value of the football leagues of different countries. Indeed, we observe that, on average, leagues with a similar economic value belongs to the same cluster. The analysis has been also extended providing a comparison based on the world trade network. We observe that prominent European players in the economic trades are also relevant in the soccer transfer network.

Clemente, G., Cornaro, A. (2023). Community detection in attributed networks for global transfer market. ANNALS OF OPERATIONS RESEARCH, 325(1), 57-83 [10.1007/s10479-021-04439-9].

Community detection in attributed networks for global transfer market

Cornaro, A
2023

Abstract

In this work we analyse the global soccer player transfer market providing a network approach that takes into account both the number of transfers and the related costs for football players in the world market. We propose a community detection methodology that considers different features of the network. We cluster countries according to similarities in their roles in the transfer market and to the presence of indirect connections due to common neighbours. Numerical results show a strict relation between the composition of clusters and the economic value of the football leagues of different countries. Indeed, we observe that, on average, leagues with a similar economic value belongs to the same cluster. The analysis has been also extended providing a comparison based on the world trade network. We observe that prominent European players in the economic trades are also relevant in the soccer transfer network.
Articolo in rivista - Articolo scientifico
Attributed networks; Community detection; Data science; Economic trade;
English
14-gen-2022
2023
325
1
57
83
none
Clemente, G., Cornaro, A. (2023). Community detection in attributed networks for global transfer market. ANNALS OF OPERATIONS RESEARCH, 325(1), 57-83 [10.1007/s10479-021-04439-9].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/345198
Citazioni
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 3
Social impact