2020 Volume 32 Issue 1 Pages 580-589
Japan Sports Agency aims at supporting distinguished performance of national members of Japan from a scientific aspect in the prioritized policy concerning improvement in international athletic ability. Focusing on the field sports, we have been developing a system for visualizing athletes’ plays using the GNSS sensor. In particular, we have been performing a research on matchup analysis of pass plays with a focus on American football. The aim of the research was to decide whether a pass is completed or incompleted by deep learning, using trajectory images of matchup of QB, WR, and DB. However, since only the track information of the finished plays was used, it failed to obtain information perceived during the play, for example, prediction of the completed pass probability during the play, or information that enables directing timely choice or modification of action from the side line during the game based on the prediction values. In this research, we attempt to predict completion probability during plays by using track information that takes into account the time term. In experiments, we made analysis of quick passes, short passes, and long passes to demonstrate its usefulness.
