In basketball games, wild-open means that there is an offensive player not well defensed by his/her opponents. The occurrence of wild-open usually implies the existence of a successful offense tactic. In this paper, a Wild-Open Warning (WOW) system is designed to assist basketball coaches/players in revealing possible tactics of their opponents through watching the broadcast game videos. The system automatically extracts the semantic objects such as the court and the players in the video and calibrates players’ positions to match the real-world court coordinates. A robust and efficient algorithm for court detection and camera calibration is proposed for analyzing basketball videos. Wild-open event is detected when the position of an offensive player satisfies three predefined criteria. In the mean time, the system will mark the wild-open players to warn the viewers that they should keep high attention to certain players.