As an efficient technique to research complex system, networks can reveal the interactions in many systems. The interactions in many real-life networks are complex, for example, the cooperation and competition in social networks. The different strategies in game theory can be used to describe the complex interactions. A network evolution model is proposed with the consideration of both preference and coordination game. Theoretical analysis and experiment results show that the model can well describe many statistical properties in real-life complex networks, like scale-free and high clustering coefficient.