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Exploring essential variables for successful and unsuccessful football teams in the "Big Five" with multivariate supervised techniques

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Exploring essential variables for successful and unsuccessful football teams in the "Big Five" with multivariate supervised techniques

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dc.contributor.author Malagón-Selma, María del Pilar es_ES
dc.contributor.author Debón, A. es_ES
dc.contributor.author Ferrer, Alberto es_ES
dc.date.accessioned 2023-03-20T19:01:15Z
dc.date.available 2023-03-20T19:01:15Z
dc.date.issued 2022-05 es_ES
dc.identifier.uri http://hdl.handle.net/10251/192527
dc.description.abstract [EN] This research proposes multivariate techniques for discovering the game actions that contribute to the final ranking of football teams. This study uses data from the "Big Five" teams that competed in the Bundesliga First Division, Premier League, LaLiga, Ligue 1, and Serie A in the 2018-2019 season. The principal component analysis is used for outlier detection and for providing an overall preliminary insight. The statistically significant game actions of the top and bottom teams were studied using three supervised multivariate techniques, namely the partial least squares discriminant analysis, random forest and logistic regression. The partial least squares discriminant analysis model best identifies the variables with the most statistically significant contribution to a team's success or failure. The results were compared with those obtained using two-sample univariate tests (such as the Student's t-test or the Mann-Whitney test), demonstrating the advantages of multivariate approaches over univariate approaches. The results indicate that the top teams have both offensive and defensive power, and emphasise the high number of attacking actions; in contrast, the bottom teams have weak defences and few offensive actions. es_ES
dc.description.sponsorship The authors want to express their gratitude to the Universitat Politecnica de Valencia for the financial support through the FPI-UPV grant (PAID-01-19). es_ES
dc.language Inglés es_ES
dc.publisher Università del Salento es_ES
dc.relation.ispartof Electronic Journal of Applied Statistical Analysis es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Multivariate methods es_ES
dc.subject Two-sample tests es_ES
dc.subject Partial least squares discriminant analysis (PLS-DA) es_ES
dc.subject Random forest (RF) es_ES
dc.subject Logistic regression (RL) es_ES
dc.subject Game actions es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Exploring essential variables for successful and unsuccessful football teams in the "Big Five" with multivariate supervised techniques es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1285/i20705948v15n1p249 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV//PAID-01-19/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.contributor.affiliation Universitat Politècnica de València. Facultad de Administración y Dirección de Empresas - Facultat d'Administració i Direcció d'Empreses es_ES
dc.description.bibliographicCitation Malagón-Selma, MDP.; Debón, A.; Ferrer, A. (2022). Exploring essential variables for successful and unsuccessful football teams in the "Big Five" with multivariate supervised techniques. Electronic Journal of Applied Statistical Analysis. 15(1):249-276. https://doi.org/10.1285/i20705948v15n1p249 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1285/i20705948v15n1p249 es_ES
dc.description.upvformatpinicio 249 es_ES
dc.description.upvformatpfin 276 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 15 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 2070-5948 es_ES
dc.relation.pasarela S\466661 es_ES
dc.contributor.funder Universitat Politècnica de València es_ES


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