Abstract
The purpose of this study is to contribute to improve badminton player’s performance for analyzing data in features playing badminton games and moreover estimating trend using it. Player’s feature quantity consists of player position on the court and strokes using motion analysis with multi view camera. Player’s feature quantity dataset in chronological order is generated by the combination of player’s feature quantity. Player’s feature quantity dataset of amateur player are compared with dataset of professional player in men's badminton singles games using mining sequential patterns. We confirmed the difference between amateur player and professional player.
