Incentive models are becoming increasingly popular in Mobile Peer to Peer Networks (M-P2P) as these models entice node participation in return for a virtual currency to combat free riding and to effectively manage constraint resources in the network. Many routing protocols proposed are based on best effort data traffic policy, such as the shortest route selection (hop minimization). Using virtual currency to find a cost effective optimal route from the source to the destination, while considering Quality of Service (QoS) aspects such as bandwidth and service capacity constraints for data delivery, remains a challenging task due to the presence of multiple paths and service providers. Modeling the network as a directed weighted graph and using the cost acquired from the price function as an incentive to pay the intermediate nodes in M-P2P networks to forward data, we develop a Game theoretic approach based on stochastic games to find an optimal route considering QoS aspect. The performance of our routing protocol is evaluated and compared with some existing routing protocols and the result shows that our protocol proves to be efficient compared to shortest-path DSR and multiple paths SMR in terms of average response time, energy and bandwidth utilization in the network.