Lowest temperature in Houston on Jul 11, 2026?

Prediction market odds and traditional meteorological forecasts often diverge because they measure different things. Weather analysts rely on physics-based models and historical data to estimate conditions, while this market reflects what traders believe will actually occur, incorporating their confidence, risk tolerance, and access to emerging information. Markets can sometimes outperform static forecasts by rapidly incorporating new data—such as shifting atmospheric patterns or seasonal anomalies—that analysts may not yet have fully weighted. Comparing the two approaches provides a richer picture of uncertainty around Houston's July 11 low temperature.

On Kalshi, this market is priced through a continuous order book where traders submit bids and offers for shares tied to specific temperature outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Prices range from near zero to nearly 100, reflecting the implied probability that each outcome will occur. As new information emerges or trader sentiment shifts, prices adjust in real time. The spread between buy and sell prices represents the market's uncertainty; tighter spreads indicate higher confidence in a particular range, while wider spreads suggest genuine disagreement about where Houston's low will land.

This market resolves around Jul 12, 2026, once July 11, 2026 has passed and the lowest temperature for that day in Houston can be verified. The outcome is confirmed against credible public sources to ensure accuracy. Traders holding shares in the correct temperature range receive their payout, while incorrect positions expire worthless. The resolution process is designed to be transparent and final, preventing disputes and ensuring all participants understand the rules before trading begins.

Several factors could shift odds significantly before July 2026. Major climate patterns—such as El Niño or La Niña conditions, or unusual jet stream behavior—could alter seasonal temperature expectations for Houston. Real-time weather updates closer to the event date, particularly shifts in high-pressure systems or tropical activity, often trigger sharp repricing. Long-term climate data releases or revised seasonal outlooks from meteorological agencies may also influence trader positioning. Additionally, any unusual market activity or large trades can cascade into broader price movements as other participants react to new information.