ArticleJournal of applied statistics2023
Observed heterogeneity in players' football performance analysis using PLS-PM.
Article in Journal of applied statistics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Nowadays, data science is applied in several areas of daily life. There have been many applications to sports. In this context, the attention will be focused on football (i.e. 'soccer' for Americans): the making of strategic choices, whether by the scouting department of the football club, or the technical staff, up to the management, is crucial. It has been measured and monitored football players' performance in the season 2018/2019, for the top five European Leagues, using data provided by Electronic Arts (EA) experts and available on the Kaggle data science platform. For this purpose, with the help of football experts, a third-order partial least-squares path model (PLS-PM) approach was adopted to the
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