Analyzing MOBA Game Data Using Feature Selection and Classification

This work presents a research designed to predict the winner outcomes in video games and analyzing the game events' effect on victory.The approach uses various methods from data mining, preprocessing of the acquired data, feature selection, and classification implementations.Different classification algorithms in Weka (Waikato Environment for Knowledge Analysis) are applied on both the original and the reduced new dataset.A comparative performance analysis on accuracy and running time are presented both for the two dataset and for the used classification algorithms.The study offers insights into the role of game event data in outcome prediction and contributes to the broader understanding of data-driven decision-making in video game analytics.