The paper is concerned with a novel adaptive game server protocol optimization to combat network latencies in the case of heterogeneous network environment. In this way, game playing becomes feasible for clients accessing the game via different networks, which can pave the way to securing a higher income for the game industry and service providers. The sever based game protocol is viewed as a number of arrival processes from the clients (which are characterized by different delays) and periodical updates sent by the server to the clients. Game quality is quantified by two measures: (i) the tail probability of the maximal idle time; and (ii) the probability of missing an update period. Our objective is to chose server update time subject to minimizing the probability of the maximal idle time exceeding a certain threshold (which threshold is associated with the "psycho-physically approved quality of the game"). In order to calculate the optimal server update time and the underlying tail distribution, statistical tools from large deviation theory are used. Furthermore, an adaptive on-line algorithm has been developed which can adjust the server update time by estimating the corresponding delay probability density functions based on past observations. Due to the new method, game quality can be significantly improved despite the wide range of client latencies which typically characterize the heterogeneous network environment. In this way, more players can be served which can further increase the business potential of network games. The performance of the new method has been evaluated by using measurements and extensive simulations.