Community detection in attributed networks for global transfer market

Clemente, Gian Paolo; Cornaro, Alessandra

doi:10.1007/s10479-021-04439-9

Cited by 3 publications

(5 citation statements)

References 34 publications

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“…More recently, Clemente y Cornaro [ 13 ] have applied network analysis to study number of transfers and the related costs for football players in the world market. They use all transfers between football clubs regarding the season 2020–2021, taking into account both winter and summer sessions, 44,481 transfers in total.…”

Section: Literature Review: Determinants Of Transfers and The Importa...mentioning

confidence: 99%

“…In relation to those studies [13,[18][19][20][21] it is identified that the number of points is a variable commonly used as an independent or control variable. Liu et al [19] use Kendall's Tau coefficient to analyze the relationship between club functionalities versus network properties in international and domestic transfer networks, node properties in transfer network and loan network, and node properties in money leagues and farm leagues.…”

Section: Plos Onementioning

confidence: 99%

“…This situation represents an opportunity to analyse the factors that influence transfers. Furthermore, scientific studies have evolved towards the consideration of new statistical tools in the study of determinants in this topic, such as network analysis [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

“…The main knowledge gap covered by this work is to study the dimensions responsible for the value of transfers from an approach of intense dynamics between clubs using network analysis. This work adds to the high-potential area of social network analysis in sports organizations [ 1 , 9 , 13 , 17 ]. In this way, empirical analysis shows relevant findings.…”

Section: Introductionmentioning

confidence: 99%

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Exploring soccer transfers in Spanish League–The hidden role of strategic differences among teams

Reis Mourao,

Salgado-Barandela

2024

PLoS ONE

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Transfers in the football world have become a hot topic in academic studies in recent years. Spanish league (La Liga) is one of the men’s professional football leagues that have driven some of the most notorious transfers. In this way, we test determinants for the transfer relationships of football players in the Spanish League in the most expensive seasons with records (2018/2019 and 2019/2020 seasons). Furthermore, we identify determinants for the values of the observed transfers. The empirical analysis shows relevant findings. We recognize two implications. First, Spanish soccer transfers are not random and this evidence reflects the environment of imperfect competition characterizing La Liga. Second, the nonrandomness of the transfer process can be associated with an increasing inequality among teams and with a threat to the competitive balance in professional sports.

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Section: Literature Review: Determinants Of Transfers and The Importa...mentioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Exploring soccer transfers in Spanish League–The hidden role of strategic differences among teams

Reis Mourao,

Salgado-Barandela

2024

PLoS ONE

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show abstract

“…They explored the network properties and found the transfer network had a power-law degree distribution but not a small-world characteristic. Clemente and Cornaro grouped different football clubs at country level by using the transfer network [62]. They discovered that leagues with comparable economic values belonged to the same cluster.…”

Section: Network-based Ranking Of Clubsmentioning

confidence: 99%

A survey on football network analysis

Li,

Xu,

Zhou

2023

EPL

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Being the world's most popular sport, football research has traditionally concentrated on empirical summaries or statistics, with only limited data available in the past. In recent years, social network analysis has been applied to a variety of fields, which also brings new perspectives to the study of football spots. In this paper, we survey the literature related to football networks and discuss the use of network measures to analyze the performance of footballers and teams in different types of football networks. We aim to find out how to construct appropriate football networks based on different perspectives on football research. Various studies on football network analysis, including team performance, player interactions, and club behavior, are reviewed. The findings provide insights into team performance, player roles, and social dynamics within football teams and clubs.

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