Motivation and emotional dynamics in esports: a facial expression analysis during competitive performance under time constraints

Abstract

The study's main objective is to explore the psychological dynamic of competitive performance in esports, focusing on how emotion and motivation interact under constant conditions over time. Using real-time facial expression analysis through OpenFace and self-reported motivational scores, the research investigates changes in valence arousal end dominance, the VAD model, during different phases in FIFA. Results from a one way ANOVA measure indicated a significant interaction between time and emotional States, suggesting that the emotional responses fluctuate dynamically across gameplay. Arousal increased during competition, and a moderate positive correlation with motivation was observed. This finding contributes to a deeper understanding of the underlying emotions that shape motivational states and performance in Esports, offering both theoretical and practical insights into performance enhancement in a virtual sports environment.