Building training for individual abilities in esports

Abstract

The aim of this research is to develop a training program tailored to individual abilities in the field of e-sports. E-sports require a diverse range of skills, and it is difficult to achieve significant results without training that aligns with an individual's capabilities. This study focuses on the FPS (First-Person Shooter) genre, evaluating the abilities and weaknesses of each player and developing a methodology to customize training programs based on this information. Specifically, the evaluation of abilities concentrates on crucial factors in FPS games such as reflexes and accuracy in hitting targets. The research aims to verify the effectiveness of the constructed training programs by implementing them based on the evaluation results. Moreover, data analysis and machine learning techniques are employed to collect performance data and training results from competitors. The goal is to discover effective training methods by leveraging these analytical approaches. Additionally, the research emphasizes the motivation and psychological aspects of competitors, aiming to develop supportive techniques that maximize the effectiveness of the training program.