Houston's high temperature on May 5 is the subject of eight distinct prediction markets, each isolating a specific two-degree range. Rather than a single yes-or-no market, this disaggregated structure allows observers to see the probability distribution across temperature outcomes with precision. Temperature is uniquely verifiable—meteorologists publish forecasts, weather stations publish actual measurements, and outcomes are objectively determined. These markets function as a mechanism for information aggregation. If you believe Houston's high will be between 64 and 65 degrees Fahrenheit, the current market price reflects what informed participants collectively expect for that outcome. When you observe all eight segments together, their relative prices tell a story about the consensus modal outcome and the degree of uncertainty surrounding it. A segment with a high price relative to its neighbors suggests participants view that temperature range as more probable; a low price indicates skepticism. As May 5 approaches and meteorological models evolve, these prices will shift—sometimes gradually as forecasts refine, sometimes sharply when models diverge significantly. This repricing mechanism is how prediction markets aggregate information in real time. The relative clustering or spread of prices across the eight segments also signals confidence: if most probability is concentrated in one or two neighboring ranges, the market expresses high confidence in a narrow outcome; if probability is distributed more evenly, uncertainty is higher. For anyone interested in weather forecasting methods, prediction market mechanics, or simply tracking Houston's meteorological expectations, these eight markets provide a granular window into what informed observers currently expect the day's high temperature to be.