In　this　article,　through　adaptive　critic,　a　dual　event-triggered　(DET)　constrained　control　scheme　is　established　for　discrete-time　nonlinear　zero-sum　games.　The　neural　networks　are　trained　from　the　dual　heuristic　dynamic　programming　technique　to　obtain　the　approximate　optimal　policy　pair.　Two　corresponding　independent　triggering　conditions　are　constructed　for　the　control　input　and　the　disturbance　to　improve　the　utilization　efficiency　and　ensure　the　independence　between　them.　In　addition,　in　order　to　overcome　the　challenge　caused　by　the　actuator　saturation,　we　constrain　the　control　input　to　a　bounded　range.　Meanwhile,　the　asymptotically　stability　is　proved　for　the　DET　control　system.　Finally,　experimental　simulations　are　conducted　to　verify　the　effectiveness　of　the　proposed　algorithm.