Calls for moving from a deterministic to a probabilistic view of weather forecasting have become increasingly urgent over recent decades, yet the primary national forecasting competition and many in-class forecasting games are wholly deterministic in nature. To counter these conflicting trends, a long-running forecasting game at Rutgers University has recently been modified to become fully probabilistic. Students forecast high and low temperature ranges (or credible intervals) and probabilities of precipitation for two locations, one fixed at the Rutgers cooperative observing station, the other chosen for each forecast window to maximize difficulty. Precipitation errors are tabulated with a Brier score, while the temperature interval score can be decomposed into a sharpness component dependent on the width of the range and a reliability component dependent on the degree to which the verification falls within the range. The resulting forecasting game is essentially a hybrid of contests that have been reported elsewhere.

The inclusion of a probabilistic forecasting game allows for the creation of a substantial database of forecasts that can be analyzed using standard probabilistic approaches, such as reliability diagrams, relative operating characteristic curves, and histograms. Discussions of probabilistic forecast quality can be quite abstract for undergraduate students, but the use of a forecast database that students themselves help construct motivates these discussions and helps students make connections between their forecast process, their standing in class rankings, and the verification diagrams they see. Student feedback on the probabilistic game is also discussed.