Skip to Main Content
Pro Clubs & Colleges

Data-Driven Ghosting Using Deep Imitation Learning

By: Stats Perform

Hoang Le, Peter Carr, Yisong Yue and Patrick Lucey’s 2017 entry titled “Data-Driven Ghosting Using Deep Imitation Learning” utilised player and ball tracking to analyse player decision making, specifically in defensive situations.

Our work showcased an automatic “data-driven ghosting” method using advanced machine learning methodologies called “deep imitation learning”, applied to a season’s worth of tracking data from a recent professional league in soccer. Our ghosting method, which avoids substantial manual human annotation, results in a data-driven system that allowed us to answer the question “how should this player or team have played in a given game situation compare to the league average?”

Complete the form and download the full report.