Lowest temperature in San Antonio on May 30, 2026?

Prediction market odds on Kalshi reflect aggregated trader expectations and often diverge from traditional meteorological forecasts issued by the National Weather Service or private weather analysts. Markets incorporate real-time data, historical patterns, and trader conviction, sometimes pricing in tail risks that analysts downweight. Comparing Kalshi implied probabilities to published seasonal forecasts or long-range weather models can reveal where the market is pricing confidence differently than institutional forecasters, offering traders an alternative perspective on San Antonio's May 30 low temperature.

On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Kalshi, the Lowest temperature in San Antonio on May 30 is priced as a set of binary or range-based contracts, each representing a specific temperature threshold or band. Traders buy and sell shares reflecting their belief in whether the actual low will fall within or outside those ranges. Prices move between 0 and 100 cents per share based on supply, demand, and incoming weather data. As May 30 approaches and forecasts sharpen, Kalshi prices typically converge toward the most likely outcome, with volume and volatility reflecting trader confidence in the final temperature reading.

The market resolves on May 31, 2026, after the close of May 30 in San Antonio. Resolution is determined by the official lowest temperature recorded for that date, sourced from designated weather stations or meteorological authorities serving the San Antonio area. Once the actual minimum temperature is confirmed and published, the market settles to the corresponding outcome contract. Traders holding shares in the correct temperature range or threshold receive their payout, while incorrect positions expire worthless.

Key drivers include updated long-range weather forecasts, seasonal climate patterns, and real-time atmospheric data as May 30 approaches. Cold fronts, high-pressure systems, or tropical influences could shift market expectations significantly. Historical May temperatures in San Antonio, El Niño or La Niña conditions, and any unusual weather anomalies reported in the region will influence trader positioning. As the event date nears, short-range forecasts become more precise, typically narrowing the range of plausible outcomes and tightening market odds around the most probable low temperature.