Research Papers

Peng, Wen-Chih; Wang, Kuang-Da; Xie, Bo-Zhou; Chen, Yu-An; Tsai, Cheng-Shiuan; Doong, Shao-Jyun; Hung, Jun-Chen

In recent years, advancements in artificial intelligence (AI) and data collection technologies have rev-olutionized sports analytics, enabling deeper insights into athletic performance that were previously unattainable. Badminton, a fast-paced and strategy-intensive sport, involves rapid decision-making and complex rally dynamics, making it a challenging yet ideal candidate for exploring the integration of AI in sports analysis. Badminton analysis typically focuses on shuttlecock landing trajectories, player movement patterns, shot type selection, and strategic planning. Accurate analysis is crucial for understanding player decision-making and providing actionable insights, both for in-game tactics and pre-match training. Effective sports analytics can help athletes address weaknesses, exploit strengths, and optimize on-court performance through targeted preparation.