# name
Multivariate Exploratory Comparative Analysis of LaLiga Teams: Principal Component Analysis

# metadata.dc.description.abstract[].value
The use of principal component analysis (PCA) provides information about the main characteristics of teams, based on a set of indicators, instead of displaying individualized information for each of these indicators. In this work we have considered reducing an extensive data matrix to improve interpretation, using PCA. Subsequently, with new components and with multiple linear regression, we have carried out a comparative analysis between the best and bottom teams of LaLiga. The sample consisted of the matches corresponding to the 2015/16, 2016/17 and 2017/18 seasons. The results showed that the best teams were characterized and differentiated from bottom teams in the realization of a greater number of successful passes and in the execution of a greater number of dynamic offensive transitions. The bottom teams were characterized by executing more defensive than offensive actions, showing fewer number of goals and a greater ball possession time in the final third of the field. Goals, ball possession time in the final third of the field, number of effective shots and crosses are the main discriminating performance factors of football. This information allows us to increase knowledge about the key performance indicators (KPI) in football.

# metadata.dc.relation.ispartof[].value
International Journal of Environmental Research and Public Health, 2021, vol. 18, num. 6, p. 3176

# metadata.dc.rights[].value
cc-by (c) Casal, Claudio A. et al., 2021

# metadata.dc.source[].value
Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)

# metadata.dc.title[].value
Multivariate Exploratory Comparative Analysis of LaLiga Teams: Principal Component Analysis