On May 5, 2026, Seattle's weather will create a single, measurable outcome: the city's highest temperature that day. This prediction market event partitions that single outcome into three distinct probability markets, each representing a different temperature band. The three markets ask whether the high will be 62–63°F, 60–61°F, or 59°F or below. Rather than forcing traders into a binary yes-or-no choice, this multi-outcome structure allows for more granular probability assessment across the plausible range. As you review the prices below, keep several principles in mind. First, prediction market prices represent probabilities expressed as percentages—a market trading at 30¢ suggests roughly a 30% chance of that outcome occurring, while 70¢ indicates approximately 70% likelihood. Together, the three prices should approximate 100¢, though small deviations are normal due to bid-ask spreads and market microstructure. Second, watch how prices move relative to each other. If one temperature band trades at a significant premium to the others, it reflects collective market consensus on the most likely range. Third, consider the source of price changes: market movements often precede traditional meteorological forecast updates as professional traders and weather enthusiasts incorporate new information into their positions. Liquidity matters too—higher trading volume typically indicates tighter spreads and more reliable price signals. Finally, remember that prediction markets aggregate the knowledge of many motivated participants with real financial stakes, a mechanism that research shows often produces surprisingly accurate forecasts. Whether you're a weather enthusiast, a probability researcher, or simply curious about how markets operationalize uncertainty, this bundle demonstrates how granular outcome markets enable participants to express nuanced views on a single underlying event.