Lowest temperature in San Antonio on Jun 19, 2026?

Prediction market odds often diverge from traditional weather forecasts because they incorporate real-money incentives and crowd intelligence. While meteorologists rely on atmospheric models and historical data, traders in this market synthesize those same inputs alongside their own expectations and risk appetite. Over time, markets tend to aggregate dispersed information efficiently, sometimes outperforming single-model forecasts. However, analyst predictions remain valuable benchmarks; comparing the two can reveal where traders see upside or downside risk relative to official guidance for the San Antonio low on that date.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares representing different temperature outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each outcome has a price between 0 and 100 cents, reflecting the implied probability that the lowest temperature will fall within that range. As demand shifts—driven by new weather data, seasonal patterns, or changing trader conviction—prices adjust in real time. The spread between bid and ask prices tightens as liquidity increases, making it cheaper to enter or exit positions.

This market resolves around Jun 20, 2026, after June 19, 2026 has passed and the actual lowest temperature in San Antonio can be verified. The outcome is confirmed once credible public reporting—typically from the National Weather Service or equivalent meteorological authority—documents the day's minimum temperature. Traders holding shares in the correct outcome receive their payout based on the final verified reading. Resolution is automatic once the data is published and the platform processes the settlement.

Major weather pattern shifts, seasonal forecasts, and long-range climate outlooks can significantly influence trading activity in this market. Tropical systems, cold fronts, or heat domes affecting Texas will prompt traders to reassess probabilities and adjust positions. Updated meteorological models released by the National Weather Service or other forecasters often trigger price swings as new data becomes available. Additionally, historical temperature records for mid-June in San Antonio and broader climate trends may inform trader expectations. As the event date approaches, intraday forecasts will become increasingly precise, potentially causing sharp repricing in the final days.