Evolutionary Games (EG) represent the attempt to describe the evolution of populations by Game Theory. A long list of applications of EG spans from biology to economy, where several complex systems and phenomena may be identified. For instance, the immune system, financial markets, and even crowds, or ants swarms, constitute emblematic examples of complex systems composed by a huge amount of elements, whose interactions drive the whole system towards particular states or equilibria. On the other hand, statistical physics constitutes the natural framework to study dynamics of complex systems in and out of equilibrium. Therefore, the application of statistical physics to EG seems a natural step which allows, in principle, to study several complex systems by analytical and computational approaches. During this talk two main examples will be presented: the spatial prisoner's dilemma and poker. The former has been widely investigated during last years, in particular to identify mechanisms that may lead a population to cooperate. Instead the latter, although represents an open problem in different communities (artificial intelligence, game theory, economy), has been investigated with less emphasis by statistical physicists.