Uma análise das seleções da copa utilizando uma rede de transferências de jogadores entre países
Resumo
O futebol é hoje o esporte mais popular do mundo. O crescimento no número de transações de compra e venda, marketing, patrocínios, venda de ingressos, contratos de TV, entre outras formas de monetização do futebol faz com que o fluxo de valores seja cada vez maior. Grande parte dos trabalhos relacionados a esse esporte são associados a análises sociológicas. Neste trabalho, é proposto um estudo focado nas transações feitas entre as seleções classificadas para a Copa do Mundo 2018 utilizando técnicas de redes complexas para uma análise da transferência de jogadores entre esses países.
Referências
fifa-11. [link]. Accessed: 2017-12-04.
Richest clubs. [link]. Accessed: 2018-01-13.
The Guardian. [link] Why Chinese clubs are breaking transfer records – and why players are wise to go. Accessed: 2017-11-20.
Transfermarkt. transfermarkt.com/statistik/transferrekorde. Accessed: 2017-11-17.
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., and Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10):P10008.
Clauset, A., Newman, M. E. J., and Moore, C. (2004). Finding community structure in very large networks. Phys. Rev. E, 70:066111.
Deloitte (June 2016). Annual review of football finance.
Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks, page 215.
Frick, B. The football players’ labor market: Empirical evidence from the major european leagues. Scottish Journal of Political Economy, 54(3):422–446.
Liebig, J., Rhein, A. V., Kastner, C., Apel, S., Dorre, J., and Lengauer, C. (2012). Large-scale variability-aware type checking and dataflow analysis.
Liu XF, Liu Y-L, L. X.-H. W. Q.-X. W. T.-X. (2016). The anatomy of the global football player transfer network: Club functionalities versus network properties. PLoS ONE, 11(6).
Maguire, J. (1994). Preliminary observations on globalisation and the migration of sport labour. The Sociological Review, 42(3):452–480.
Maguire, J. and Pearton, R. (2000). The impact of elite labour migration on the identification, selection and development of european soccer players. Journal of Sports Sciences, 18(9):759–769. PMID: 11043901.
Newman, M. E. J. (2006). Finding community structure in networks using the eigenvectors of matrices. Phys. Rev. E, 74:036104.
Newman, M. E. J. and Girvan, M. (2004). Finding and evaluating community structure in networks. Phys. Rev. E, 69:026113.
Page, L., Brin, S., Motwani, R., and Winograd, T. (1999). The pagerank citation ranking: Bringing order to the web. Technical Report 1999-66, Stanford InfoLab. Previous number = SIDL-WP-1999-0120.
Palacios-Huerta, I. (2004). Structural changes during a century of the world’s most popular sport. Statistical Methods and Applications, 13(2):241–258.
Poli, R. (2010). Understanding globalization through football: The new international division of labour, migratory channels and transnational trade circuits. International Review for the Sociology of Sport, 45(4):491–506.
Roderick, M. (2013). Domestic moves: An exploration of intra-national labour mobility in the working lives of professional footballers. International Review for the Sociology of Sport, 48(4):387–404.
Richest clubs. [link]. Accessed: 2018-01-13.
The Guardian. [link] Why Chinese clubs are breaking transfer records – and why players are wise to go. Accessed: 2017-11-20.
Transfermarkt. transfermarkt.com/statistik/transferrekorde. Accessed: 2017-11-17.
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., and Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10):P10008.
Clauset, A., Newman, M. E. J., and Moore, C. (2004). Finding community structure in very large networks. Phys. Rev. E, 70:066111.
Deloitte (June 2016). Annual review of football finance.
Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks, page 215.
Frick, B. The football players’ labor market: Empirical evidence from the major european leagues. Scottish Journal of Political Economy, 54(3):422–446.
Liebig, J., Rhein, A. V., Kastner, C., Apel, S., Dorre, J., and Lengauer, C. (2012). Large-scale variability-aware type checking and dataflow analysis.
Liu XF, Liu Y-L, L. X.-H. W. Q.-X. W. T.-X. (2016). The anatomy of the global football player transfer network: Club functionalities versus network properties. PLoS ONE, 11(6).
Maguire, J. (1994). Preliminary observations on globalisation and the migration of sport labour. The Sociological Review, 42(3):452–480.
Maguire, J. and Pearton, R. (2000). The impact of elite labour migration on the identification, selection and development of european soccer players. Journal of Sports Sciences, 18(9):759–769. PMID: 11043901.
Newman, M. E. J. (2006). Finding community structure in networks using the eigenvectors of matrices. Phys. Rev. E, 74:036104.
Newman, M. E. J. and Girvan, M. (2004). Finding and evaluating community structure in networks. Phys. Rev. E, 69:026113.
Page, L., Brin, S., Motwani, R., and Winograd, T. (1999). The pagerank citation ranking: Bringing order to the web. Technical Report 1999-66, Stanford InfoLab. Previous number = SIDL-WP-1999-0120.
Palacios-Huerta, I. (2004). Structural changes during a century of the world’s most popular sport. Statistical Methods and Applications, 13(2):241–258.
Poli, R. (2010). Understanding globalization through football: The new international division of labour, migratory channels and transnational trade circuits. International Review for the Sociology of Sport, 45(4):491–506.
Roderick, M. (2013). Domestic moves: An exploration of intra-national labour mobility in the working lives of professional footballers. International Review for the Sociology of Sport, 48(4):387–404.
Publicado
26/07/2018
Como Citar
FÉLIX, Lucas G. S.; BARBOSA, Carlos M.; CARVALHO, Iago A.; VIEIRA, Vinícius da F.; XAVIER, Carolina Ribeiro.
Uma análise das seleções da copa utilizando uma rede de transferências de jogadores entre países. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 7. , 2018, Natal.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 157-168.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2018.3588.
