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A new method for comparing rankings through complex networks: Model and analysis of competitiveness of major European soccer leagues

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A new method for comparing rankings through complex networks: Model and analysis of competitiveness of major European soccer leagues

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dc.contributor.author Criado Herrero, Regino es_ES
dc.contributor.author García González, Esther es_ES
dc.contributor.author Pedroche Sánchez, Francisco es_ES
dc.contributor.author Romance, Miguel es_ES
dc.date.accessioned 2014-04-16T12:20:21Z
dc.date.issued 2013-10-31
dc.identifier.issn 1054-1500
dc.identifier.uri http://hdl.handle.net/10251/37048
dc.description.abstract In this paper, we show a new technique to analyze families of rankings. In particular, we focus on sports rankings and, more precisely, on soccer leagues. We consider that two teams compete when they change their relative positions in consecutive rankings. This allows to define a graph by linking teams that compete. We show how to use some structural properties of this competitivity graph to measure to what extend the teams in a league compete. These structural properties are the mean degree, the mean strength, and the clustering coefficient. We give a generalization of the Kendall's correlation coefficient to more than two rankings. We also show how to make a dynamic analysis of a league and how to compare different leagues. We apply this technique to analyze the four major European soccer leagues: Bundesliga, Italian Lega, Spanish Liga, and Premier League. We compare our results with the classical analysis of sport ranking based on measures of competitive balance. es_ES
dc.description.sponsorship This paper was partially supported by Spanish MICINN Funds and FEDER Funds MTM2009-13848, MTM2010-16153 and MTM2010-18674, and Junta de Andalucia Funds FQM-264. en_EN
dc.language Inglés es_ES
dc.publisher American Institute of Physics (AIP) es_ES
dc.relation.ispartof Chaos es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title A new method for comparing rankings through complex networks: Model and analysis of competitiveness of major European soccer leagues es_ES
dc.type Artículo es_ES
dc.embargo.lift 10000-01-01
dc.embargo.terms forever es_ES
dc.identifier.doi 10.1063/1.4826446
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//MTM2009-13848/ES/Analisis Estructural, Optimizacion Y Dinamica En Sistemas Reales Con Estructuras Tipo Red/ / es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Junta de Andalucía//FQM-264/ES/Estructuras De Jordan/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//MTM2010-16153/ES/SISTEMAS DE JORDAN Y ALGEBRAS DE LIE/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.description.bibliographicCitation Criado Herrero, R.; García González, E.; Pedroche Sánchez, F.; Romance, M. (2013). A new method for comparing rankings through complex networks: Model and analysis of competitiveness of major European soccer leagues. Chaos. 23(4):1-10. https://doi.org/10.1063/1.4826446 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1063/1.4826446 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 10 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 23 es_ES
dc.description.issue 4 es_ES
dc.relation.senia 255956
dc.contributor.funder Junta de Andalucía es_ES
dc.description.references Dobson, S., & Goddard, J. (2009). The Economics of Football. doi:10.1017/cbo9780511973864 es_ES
dc.description.references Kendall, M. G., & Smith, B. B. (1939). The Problem of $m$ Rankings. The Annals of Mathematical Statistics, 10(3), 275-287. doi:10.1214/aoms/1177732186 es_ES
dc.description.references KENDALL, M. G. (1938). A NEW MEASURE OF RANK CORRELATION. Biometrika, 30(1-2), 81-93. doi:10.1093/biomet/30.1-2.81 es_ES
dc.description.references Fagin, R., Kumar, R., Mahdian, M., Sivakumar, D., & Vee, E. (2006). Comparing Partial Rankings. SIAM Journal on Discrete Mathematics, 20(3), 628-648. doi:10.1137/05063088x es_ES
dc.description.references Legendre, P. (2005). Species associations: the Kendall coefficient of concordance revisited. Journal of Agricultural, Biological, and Environmental Statistics, 10(2), 226-245. doi:10.1198/108571105x46642 es_ES
dc.description.references Emond, E. J., & Mason, D. W. (2002). A new rank correlation coefficient with application to the consensus ranking problem. Journal of Multi-Criteria Decision Analysis, 11(1), 17-28. doi:10.1002/mcda.313 es_ES
dc.description.references Blumm, N., Ghoshal, G., Forró, Z., Schich, M., Bianconi, G., Bouchaud, J.-P., & Barabási, A.-L. (2012). Dynamics of Ranking Processes in Complex Systems. Physical Review Letters, 109(12). doi:10.1103/physrevlett.109.128701 es_ES
dc.description.references Radicchi, F. (2011). Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis. PLoS ONE, 6(2), e17249. doi:10.1371/journal.pone.0017249 es_ES
dc.description.references Chartier, T. P., Kreutzer, E., Langville, A. N., & Pedings, K. E. (2011). Sensitivity and Stability of Ranking Vectors. SIAM Journal on Scientific Computing, 33(3), 1077-1102. doi:10.1137/090772745 es_ES
dc.description.references Park, J., & Newman, M. E. J. (2005). A network-based ranking system for US college football. Journal of Statistical Mechanics: Theory and Experiment, 2005(10), P10014-P10014. doi:10.1088/1742-5468/2005/10/p10014 es_ES
dc.description.references Callaghan, T., Mucha, P. J., & Porter, M. A. (2007). Random Walker Ranking for NCAA Division I-A Football. The American Mathematical Monthly, 114(9), 761-777. doi:10.1080/00029890.2007.11920469 es_ES
dc.description.references Motegi, S., & Masuda, N. (2012). A network-based dynamical ranking system for competitive sports. Scientific Reports, 2(1). doi:10.1038/srep00904 es_ES
dc.description.references Pawlowski, T., Breuer, C., & Hovemann, A. (2010). Top Clubs’ Performance and the Competitive Situation in European Domestic Football Competitions. Journal of Sports Economics, 11(2), 186-202. doi:10.1177/1527002510363100 es_ES
dc.description.references A. Feddersen and W. Maennig, “ Trends in competitive balance: Is there evidence for growing imbalance in professional sport leagues?” Hamburg contemporary economic discussions No. 01/2005, University of Hamburg, 2005. es_ES
dc.description.references Pedroche Sánchez, F. (2010). Competitivity groups on social network sites. Mathematical and Computer Modelling, 52(7-8), 1052-1057. doi:10.1016/j.mcm.2010.02.031 es_ES
dc.description.references PEDROCHE, F. (2012). A MODEL TO CLASSIFY USERS OF SOCIAL NETWORKS BASED ON PAGERANK. International Journal of Bifurcation and Chaos, 22(07), 1250162. doi:10.1142/s0218127412501623 es_ES
dc.description.references Pedroche, F., Moreno, F., González, A., & Valencia, A. (2013). Leadership groups on Social Network Sites based on Personalized PageRank. Mathematical and Computer Modelling, 57(7-8), 1891-1896. doi:10.1016/j.mcm.2011.12.026 es_ES
dc.description.references García, E., Pedroche, F., & Romance, M. (2013). On the localization of the personalized PageRank of complex networks. Linear Algebra and its Applications, 439(3), 640-652. doi:10.1016/j.laa.2012.10.051 es_ES
dc.description.references BOCCALETTI, S., LATORA, V., MORENO, Y., CHAVEZ, M., & HWANG, D. (2006). Complex networks: Structure and dynamics. Physics Reports, 424(4-5), 175-308. doi:10.1016/j.physrep.2005.10.009 es_ES
dc.description.references Humphreys, B. R. (2002). Alternative Measures of Competitive Balance in Sports Leagues. Journal of Sports Economics, 3(2), 133-148. doi:10.1177/152700250200300203 es_ES
dc.description.references M. Kringstad, “ Competitive balance in complex professional sports leagues,” Doctoral thesis (The University of Leeds. Leeds University Business School, 2008). es_ES
dc.description.references Owen, P. D., Ryan, M., & Weatherston, C. R. (2007). Measuring Competitive Balance in Professional Team Sports Using the Herfindahl-Hirschman Index. Review of Industrial Organization, 31(4), 289-302. doi:10.1007/s11151-008-9157-0 es_ES


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