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Uncovering determinants of victory and defeat in Men's UEFA champions league: An analytical exploration using logistic regression
Karuppasamy Govindasamy, Debajit Karmakar, Sohom Saha, Masilamani Elayaraja, Anindita Das, Arnav Sharma, Poli Borah, Lakshyajit Gogoi, Hemantajit Gogoi
Status minimal Language English Country Czech Republic
This study aimed to explore the factors influencing outcomes in men's UEFA Championship matches. The sample comprised 201 UEFA Championship games, and the primary objective was to identify key components significantly associated with success in the UEFA Champions League through logistic regression analysis. The game outcome was treated as the dependent variable in a Binary Logistic Regression (Forward: LR Method). Logistic regression, a statistical technique assessing the relationship between variables, employed predictor variables as covariates, with calculations of β, standard error β, and Wald’s χ2. Model evaluation involved the likelihood ratio test, Cox & Snell (R2), and Nagelkerke (R2) tests, while the fit of the models to the data was assessed using the Hosmer & Lemeshow test. The analysis revealed six variables linked to winning matches. The study highlights a significant correlation between crucial variables and success in UEFA Champions League matches. Players and coaches can gain valuable insights into essential elements contributing to victory in this prestigious championship.
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Literatura
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- $a This study aimed to explore the factors influencing outcomes in men's UEFA Championship matches. The sample comprised 201 UEFA Championship games, and the primary objective was to identify key components significantly associated with success in the UEFA Champions League through logistic regression analysis. The game outcome was treated as the dependent variable in a Binary Logistic Regression (Forward: LR Method). Logistic regression, a statistical technique assessing the relationship between variables, employed predictor variables as covariates, with calculations of β, standard error β, and Wald’s χ2. Model evaluation involved the likelihood ratio test, Cox & Snell (R2), and Nagelkerke (R2) tests, while the fit of the models to the data was assessed using the Hosmer & Lemeshow test. The analysis revealed six variables linked to winning matches. The study highlights a significant correlation between crucial variables and success in UEFA Champions League matches. Players and coaches can gain valuable insights into essential elements contributing to victory in this prestigious championship.
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