Prediction markets have emerged as powerful instruments for understanding how large groups of people collectively forecast specific outcomes. This page displays prediction markets focused on Seattle's high temperature on May 17—a natural phenomenon that traders are actively pricing based on their expectations. Rather than forcing participants into a single yes-or-no choice, these markets partition the temperature spectrum into three distinct ranges: at or below 45°F, between 46-47°F, and between 50-51°F. This structure enables traders to express more nuanced forecasts than binary markets alone would permit. The prices you see in these markets translate directly into probability estimates. A market price of 0.65 indicates that market participants, in aggregate, assess a 65% probability of that outcome occurring. Throughout the day leading up to May 17, these prices will fluctuate as new information emerges—updated weather forecasts, atmospheric patterns, and other relevant signals—and as traders continuously reassess their expectations. The relationships between the three markets reveal where collective uncertainty concentrates. If prices for two adjacent ranges are far apart, it suggests genuine disagreement about where the temperature will fall. Conversely, tight clustering around one range indicates confidence in a particular outcome. Because these are mutually exclusive outcomes, their probabilities should sum to approximately 100%, though in practice they may vary slightly due to market friction and uncertainty at range boundaries. These continuous, transparent price signals represent the market's best real-time estimate of what will happen, aggregating information from diverse participants without requiring any single central forecaster.