We examine high-stakes strategic choice using more than 40 years of data from the American TV game show “The Price Is Right”. In every episode, contestants play the “Showcase Showdown”, a sequential game of perfect information for which the optimal strategy can be found through backward induction. We find that contestants systematically deviate from the subgame perfect Nash equilibrium. These departures from optimality are well described by an agent quantal response model with limited foresight, where a sizable proportion of the contestants myopically consider the next stage of the game only. In line with learning, the quality of contestants' choices improves over the course of our sample period.