<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The transfer market of European football can be classified as a system. In this system, the effectiveness of participant teams can depend on the activity in players’ transfers. This article assesses the utility of network analysis in analysing connections between the mentioned concepts. The hypothesis is that there is causality between a club’s activity in the transfer market and its profit from transfers. This research is based on empirical transfer data of major soccer teams, which have had a significant role in the last 12 years in Europe. It is assumed that the most active clubs in the transfer system have more financial power in the transfer market, while teams which are not active in transfers have less profit from transfers. In the network analysis, the teams can be defined as a set of nodes and connected by edges (interactions). The thickness of the edges and the size of the nodes depend on the volume of transfers among clubs. The number of interactions and the amount of the transfer price can measure this volume also. Considering the results of network indices, the relationships between the two phenomena were reviewed. In order to explore these relationships, the correlations among all of the relevant variables in the transfer market were also measured.</p></abstract>

The transfer market of European football can be classified as a system. In this system, the effectiveness of participant teams can depend on the activity in players’ transfers. This article assesses the utility of network analysis in analysing connections between the mentioned concepts. The hypothesis is that there is causality between a club’s activity in the transfer market and its profit from transfers. This research is based on empirical transfer data of major soccer teams, which have had a significant role in the last 12 years in Europe. It is assumed that the most active clubs in the transfer system have more financial power in the transfer market, while teams which are not active in transfers have less profit from transfers. In the network analysis, the teams can be defined as a set of nodes and connected by edges (interactions). The thickness of the edges and the size of the nodes depend on the volume of transfers among clubs. The number of interactions and the amount of the transfer price can measure this volume also. Considering the results of network indices, the relationships between the two phenomena were reviewed. In order to explore these relationships, the correlations among all of the relevant variables in the transfer market were also measured.

Correlation between profitability and transfer activity in European football

Croatian Review of Economic, Business and Social Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Correlation between profitability and transfer activity in European football"}

The transfer market of European football can be classified as a system. In this system, the effectiveness of participant teams can depend on the activity in...

Correlation between profitability and transfer activity in European football

Published Online: Dec 14, 2018

Page range: 15 - 22

Received: May 11, 2018

Accepted: Nov 12, 2018

DOI: https://doi.org/10.2478/crebss-2018-0009

Keywords
correlation, sports economics, transfer network, transfer’s profitability of sports firms

© 2018 Diána Ivett Fürész, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Correlation between profitability and transfer activity in European football

Published Online: Dec 14, 2018

Page range: 15 - 22

Received: May 11, 2018

Accepted: Nov 12, 2018

DOI: https://doi.org/10.2478/crebss-2018-0009

Keywordscorrelation, sports economics, transfer network, transfer’s profitability of sports firms

© 2018 Diána Ivett Fürész, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
correlation, sports economics, transfer network, transfer’s profitability of sports firms