In this paper, we propose a novel automatic approach for personalized music sports video generation. Two research challenges, semantic sports video content selection and automatic video composition, are addressed. For the first challenge, we propose to use multi-modal (audio, video and text) feature analysis and alignment to detect the semantic of events in sports video. For the second challenge, we propose video-centric and music-centric music video composition schemes to automatically generate personalized music sports video based on user's preference. The experimental results and user evaluations are promising and show that our system's generated music sports video is comparable to manually generated ones. The proposed approach greatly facilitates the automatic music sports video generation for both professionals and amateurs.