1. A method comprising: receiving, by a processor, a report indicating a user-reported numeric probability of a successful outcome; estimating, by the processor, a behavior and information model based on the report, the behavior and information model including a behavior model component having a bias parameter indicating user bias in providing the user-reported numeric probability and a consistency parameter indicating user consistency in providing the user-reported numeric probability, the behavior and information model including an information model component having a first user-believed probability of a successful outcome and a second user-believed probability of a successful outcome, where estimating the behavior and information model based on the report comprises employing a maximum likelihood technique that determines the bias parameter, the consistency parameter, the first user-believed probability of winning, and the second user believed probability of winning that maximize a likelihood; and, using, by the processor, the behavior and information model to yield a model-determined numeric probability of a successful outcome that more accurately reflects a probability of a successful outcome than the user-reported numeric probability of a successful outcome does, wherein the likelihood is the model-determined numeric probability of a successful outcome for an ultimate winning outcome, the bias parameter is determined based on an expected utility calculation, and the consistency parameter is determined using a probabilistic choice approach, wherein the expected utility calculation involves a Brier scoring rule in which the user-reported numeric probability is subjected to a mathematical calculation, and wherein the probabilistic choice approach models a bounded user rationality.