Analyzing Winning-Related Features to Understand Team Characteristics
Analyzing Winning-Related Features to Understand Team Characteristics
Hideyuki Yoza,Yoshiro Yamamoto
2023 · DOI: 10.1109/ICTKE58576.2023.10401813
International Conference on ICT and Knowledge Engineering · 1 Citations
Abstract
In this study, the data published by Fédération Internationale de Football Association officials have been classified according to the difficulty of obtaining the variables. Classification was based on the availability of video, the Global positioning system and experts. Herein the variable importance of random forests, an ensemble learning process, was used. Visualizations were created to analyze the features. This study examines the features of winning and losing in soccer competitions through visualization utilizing a web application with R-Shiny. The visualized information allowed discussion of the matches.
