Volleyball Prediction

Volleyball prediction research focuses on leveraging machine learning to forecast rally outcomes, player actions (e.g., hit type, set location), and even game strategies. Current efforts utilize graph neural networks (GNNs) to analyze enriched datasets that incorporate detailed player positions and actions, often represented using novel descriptive languages. These advancements aim to provide coaches and players with actionable insights for improved training and game-day decision-making, bridging the gap between sports analytics and computer science. The development of comprehensive volleyball datasets is crucial for training and evaluating these predictive models.