Evidence from psychological studies of both novice and expert forecasters often show that people are overconfident in their ability to make accurate judgmental predictions about future events. In contrast, evidence from much cognitive engineering research appears to show that experienced performers are reasonably well adapted to their task environments and do not display many of the cognitive biases, such as overconfidence, evident in the psychological literature. We present the results of a study providing evidence for both views, and more importantly, for the conditions under which experienced forecasters will exhibit high levels of calibration (little overconfidence) versus poorer calibration and thus overconfidence. In short, good calibration resulted when forecasters were required to draw solely upon high validity base-rate information gained through many years of repetitive exposures to a prediction task, yet displayed overconfidence when they were also provided case-specific information with high salience and interest but little or no predictive validity.