Event　analysis　in　multi-person　videos　is　a　great　challenge-able　task,　especially　in　the　sports　videos　due　to　the　intensive　and　fast　movement　of　players　with　serious　occlusions.　In　this　paper,　we　propose　a　global　motion　pattern　(GMP)　based　event　recognition　algorithm.　In　order　to　avoid　obstacles　from　complex　background　noise,　GMP　of　video　frames　in　sports　video　is　extracted　by　optical　flow.　In　particular,　both　spatial　and　temporal　features　of　GMP　are　devoted　to　event　recognition　by　sequential　CNN　and　LSTM.　Experimental　analysis　demonstrates　that　the　proposed　algorithm　is　capable　to　take　benefit　from　spatial　and　temporal　characteristics　of　GMP　for　effective　event　recognition.