Many real life situations, like the financial market, auctions and resources competitions, can be modeled as Minority Games. In minority games, players choose to join one of the two sides, A or B. The players are rewarded if they have joined the minority side, and punished otherwise. A traditional way to play in the minority games is to use predictors to decide which side to join. A predictor predicts the winning side in the next time step given a history of winning sides in previous time steps. In this paper, we introduce Behavioral Predictors and Adaptive Strategies for the minority game, with which players perform much better than those using previous models.