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The Impact of Match Location and Players’ Physical and Technical Activities on Winning in the German Bundesliga
This study aimed to examine whether the physical and technical activities of soccer players and match locations can be associated with higher or lower odds of winning matches whose outcome can be described as “close.” The study comprised 7972 individual observations of German Bundesliga players duri...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390904/ https://www.ncbi.nlm.nih.gov/pubmed/32793071 http://dx.doi.org/10.3389/fpsyg.2020.01748 |
Sumario: | This study aimed to examine whether the physical and technical activities of soccer players and match locations can be associated with higher or lower odds of winning matches whose outcome can be described as “close.” The study comprised 7972 individual observations of German Bundesliga players during the 2014/2015 (n = 2794), 2015/2016 (n = 2494), and 2016/2017 (n = 2684) seasons. A selection of “close matches” was made, which were defined as those in which the difference in numbers of scored goals was ≤1. Players’ five pitch positions were considered: central defenders, fullbacks, central midfielders, wide midfielders, and forwards. Data on 12 physical and 10 technical activities performed by players during matches as well as on match location were retrieved from the Impire AG (Germany) match analysis system. The study results show that the odds of winning at home are different for each playing position: from 41.99% for wide midfielders to 91.34% for central midfielders. Another conclusion was that one of the key components of the predictive model for forwards is the percentage of overall distance covered at speeds >24 km/h (7.99%), which is a variable with an increasing trend. The proposed model predicts that each 1% increase in this variable will theoretically be associated with a 4.08% raise of the odds of winning in further seasons. The presented statistical model may be used by trainers to identify players’ physical and technical activities and contextual variables that may significantly affect the match outcome. In addition, it can help to determine the individual training load related to the player’s position on the pitch. |
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