On May 17, Denver's weather will be the focal point of these prediction markets, which offer a detailed crowd forecast for the day's high temperature. Rather than a single outcome prediction, this event is segmented across multiple temperature brackets—from whether the high will reach 90°F or above, down through various ranges spanning 78–85°F. This layered structure mirrors how meteorologists analyze temperature forecasts: by breaking outcomes into specific ranges, it enables more granular probability assessment. When reading the prices below, you're observing real-time crowd estimates for the likelihood of each temperature range occurring. A high price on the 90°F market reflects optimism about an exceptionally warm day, while prices on the 78–79°F bracket capture the market's assessment of cooler scenarios. The relationship between these prices reveals the consensus forecast—whether the crowd expects a scorching, above-average May day or a more moderate outcome. By examining these related markets together, you can see both the central forecast (where most probability density concentrates) and the distribution's tails (how much probability the market assigns to extreme outcomes). This structured approach is particularly useful for understanding what conditions the market anticipates across the full range of plausible scenarios. The markets' real-time updates reflect evolving information: fresh weather model runs, updated meteorological forecasts, or shifts in collective assessment. The prices represent the aggregated judgment of the prediction market community about Denver's May 17 weather.