Trajectory prediction with imitation learning reflecting defensive evaluation in team sports

In team sports, qualitative video analysis is mainly used for decision making of team tactics because of the complex interaction. Among the quantitative analyses, most of studies in team trajectory generation have been evaluated only on prediction errors and did not take tactical evaluations (e.g., good defense) into consideration. In this paper, we propose a trajectory prediction method incorporating the defensive evaluation (i.e., how well they protect the goal) into multi-agent imitation learning model. Although the proposed method had the similar prediction performance to the existing method, our method generated an improved trajectory in terms of defensive evaluation.