03472ntm a22005177i 4500 000714095 CZ-PrVSE 20240608092444.0 m d cr n|||||||||| 240608s2024 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Bonsel, Job Paul Maria ISIS:147030 dis COMPARATIVE ANALYSIS OF MULTIVARIATE STATISTICAL METHODS FOR PREDICTING FOOTBALL MATCH OUTCOMES USING REAL DATA eng Comparative Analysis of Multivariate Statistical Methods for Predicting Football Match Outcomes using Real Data / Job Paul Maria Bonsel 2024 ?? stran : digital, PDF soubor Vedoucí práce: Adam Čabla Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2024 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2024 This thesis evaluates the predictive accuracy of six multivariate statistical models for forecasting football match outcomes within the English Premier League, comparing them against betting odds. The models examined include the Bradley-Terry model with an Additive Feature Differences (AFD) extension, Multinomial Logistic Regression (MLR), Bayesian Networks (BN), Decision Trees, Poisson regression, and Weibull count models. Using data from the 2006/2007 to 2018/2019 seasons sourced from www.football-data.co.uk and www.sofifa.com, the study incorporates both traditional performance metrics and FIFA video game ratings to assess team strengths. Performance evaluation is conducted through Ranked Probability Score (RPS) and Classification Accuracy, utilizing k-fold cross-validation. Results indicate that the Bradley-Terry AFD and MLR models perform most effectively, closely rivaling the sophisticated betting models which include real-time data adjustments. The study also highlights the tendency of models to overestimate home wins and the potential of FIFA ratings as predictive tools. This research provides insights into the capabilities of statistical models in sports analytics and suggests directions for future enhancements, particularly in integrating novel data sources to improve the prediction of football match outcomes. Způsob přístupu: Internet data analysis and modeling [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas football match outcomes comparative analysis videogame data multivariate statistical methods Predictive modeling Čabla, Adam, 1985- vse2015897119 ths Helman, Karel xx0260953 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/86317/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/86317 Hlavní práce https://insis.vse.cz/zp/86317/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/86317/posudek/oponent/82060 Oponentura https://insis.vse.cz/zp/86317/podrobnosti dc:identifier NEPOSILAT VSKP vse86317 240606 86317