On May 18, Denver's weather will be subject to prediction markets that allow readers to assess the probability of different high-temperature outcomes. This event aggregates five related prediction markets, each covering a specific temperature range: 70–71°F, 74–75°F, 76–77°F, 78–79°F, and 80°F or higher. Rather than providing a single forecast, these bundled markets reveal how traders collectively weigh the likelihood of each scenario. The key to reading these markets is comparing the implied probabilities—the likelihood each range commands based on market prices. The range with the highest probability represents where the market consensus leans most strongly. Pay attention to gaps in probabilities between adjacent ranges; sharp divergences often signal where traders expect distinct boundaries in temperature outcomes. The full picture requires looking at all five markets together: tightly clustered probabilities suggest confidence in a narrow band of outcomes, while dispersed odds indicate broader uncertainty about May 18's conditions. Real-world factors—seasonal weather patterns, current atmospheric pressure, and forecaster models—influence these markets, but they ultimately reflect live trader expectations. Whether you're interested in how markets price weather uncertainty, curious about meteorological patterns, or exploring probabilistic forecasting in action, these temperature markets offer a transparent window into how distributed networks of traders assign likelihoods to specific natural events.