  The increasing use of artificial intelligence (AI) technology in turn-based
sports, such as badminton, has sparked significant interest in evaluating
strategies through the analysis of match video data. Predicting future shots
based on past ones plays a vital role in coaching and strategic planning. In
this study, we present a Multi-Layer Multi-Input Transformer Network (MuLMINet)
that leverages professional badminton player match data to accurately predict
future shot types and area coordinates. Our approach resulted in achieving the
runner-up (2nd place) in the IJCAI CoachAI Badminton Challenge 2023, Track 2.
To facilitate further research, we have made our code publicly accessible
online, contributing to the broader research community's knowledge and
advancements in the field of AI-assisted sports analysis.
