To　further　improve　the　stickiness　of　puzzle　game　players,　we　developed　a　prediction　model　based　on　the　BP　neural　network.　Firstly,　we　preprocessed　the　existing　data　to　remove　some　useless　information.　Then,　we　introduced　the　WOA　algorithm　to　optimize　the　BP　neural　network　model　and　improve　its　prediction　accuracy.　To　predict　the　distribution　percentage　of　attempts　to　guess　a　given　word　in　the　future,　we　improved　the　BP　neural　network　using　the　multi-input　multi-output　CIWOA　algorithm　(Cubic　map　improvement　whale　optimization　algorithm).　The　experimental　results　showed　that　the　WOA-BP　prediction　model　predicted　player　data　for　March　1,　2023,　to　be　between　20,000　and　25,000,　while　the　actual　data　was　19,655.　Our　prediction　model　had　a　small　margin　of　error,　indicating　good　prediction　accuracy.　Based　on　this　model,　we　provided　reasonable　adjustment　suggestions　for　the　game　company＇s　later　operations.　©　2023　The　Authors.