EWA Lite is a one-parameter theory of learning in normal-form games. It approximates the free parameters in an earlier model (EWA) with functions of experience. The theory is tested on seven different games and compared to other learning and equilibrium theories. Either EWA Lite or parameterized EWA predict best, but one kind of reinforcement learning predicts well in games with mixed-strategy equilibrium. Belief learning models fit worst. The economic value of theories is measured by howmuch more subjects would have earned if they followed theory recommendations. EWA Lite and EWA add the most economic value in every game but one.