03366ntm a22005417i 4500 000716581 CZ-PrVSE 20240824093620.0 m d cr n|||||||||| 240824s2024 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Hodge, James Michael ISIS:165387 dis Application of Classification Methods on Fantasy Premier League Data eng Application of Classification Methods on Fantasy Premier League Data / James Michael Hodge 2024 ?? stran : digital, PDF soubor Vedoucí práce: Zdeněk Šulc Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2024 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2024 Fantasy Premier League (FPL) allows participants to roleplay as a manager in the English Premier League (EPL) and assemble their own team of real players to compete against other managers. As the popularity of FPL continues to rise, managers are seeking new ways to gain an advantage against other competitors. The following thesis aims to utilize cluster analysis methods on real data from the 2021-2022 season to gain insights into the underlying structure of FPL Goalkeepers and Forwards, as well as to objectively determine which players should be selected. Two modes of FPL, FPL and FPL Draft, will be considered when performing the cluster analysis and discussing the players and strategies that should be considered for team selection. Specifically, agglomerative hierarchical clustering and k-means are used with variables relating to FPL performance, finding distinct clusters and tiers of players that should and should not be considered for team selection. A supplementary goal of this thesis is to compare the performance of agglomerative hierarchical clustering and k-means clustering of FPL data. This thesis provides the framework for how to use cluster analysis in the context of FPL for the additional positions of FPL Defenders and Midfielders. Způsob přístupu: Internet data analysis and modeling [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas Fantasy Premier League (FPL) English Premier League (EPL) cluster analysis agglomerative hierarchical clustering k-means Goalkeepers Forwards Šulc, Zdeněk vse20191023055 ths Cibulková, Jana ISIS:129091 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/86260/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/86260 Hlavní práce https://insis.vse.cz/zp/86260/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/86260/posudek/oponent/81702 Oponentura https://insis.vse.cz/zp/86260/podrobnosti dc:identifier NEPOSILAT VSKP vse86260 240822 86260