Milan's weather on April 27 is the subject of this collection of five prediction markets, each exploring a different outcome within the range of expected maximum temperatures for the day. By grouping these markets together, you gain a complete view of where traders expect the thermometer to land across a range spanning 16°C to 21°C. Rather than making a single yes-or-no prediction, these five related questions collectively reveal the market's temperature distribution—which outcomes traders see as likely, which as unlikely, and where uncertainty lives. The beauty of examining grouped markets this way is that price movements across them tell an interconnected story. If traders collectively raise prices on warmer outcomes and lower them on cooler ones, you're seeing a shift in the market's central expectation. Similarly, tight price clustering around certain thresholds signals where the market consensus is strongest, while wide spreads across adjacent markets indicate greater uncertainty. By reading how these prices move in relation to one another—rather than examining any single market in isolation—you can infer both the collective expectation and the range of outcomes traders still consider plausible. Prediction markets excel at this kind of aggregation because they pool real-time forecasting from diverse participants with strong incentives to be accurate. As April 27 approaches and new weather forecasts, seasonal patterns, and atmospheric data emerge, these prices adjust dynamically to reflect the market's evolving assessment, making them a transparent and constantly-updating window into trader expectations.