Modelling and predicting adversarial behaviour using large amounts of spatiotemporal data

This research represents pioneering work to exploit new and rich data from tracking system to model player behaviour in sports. Novel methods for understanding and predicting player behaviour were proposed. The key contribution is the development of an algorithm that capture the “style” of players from trajectory data. Experimental results show improved prediction performance in various sports including tennis, basketball and soccer