Abstract. Every fall, millions of Americans enter betting pools to pick winners of the weekly NFL football games. In the spring, NCAA tournament basketball pools are even more popular. In both cases, teams which are popularly perceived as “favorites” gain a disproportionate share of entries. In large pools there can be a significant advantage to picking upsets that differentiate your picks from the crowd. In this paper we present a model of betting pools that incorporates pool participant behavior. We use the model to derive strategies that maximize the expected return on a bet in both football and tournament style pools. These strategies significantly outperform strategies based on maximizing score or number of correct picks–often by orders of magnitude.