Lowest temperature in San Antonio on Jun 30, 2026?

Prediction market odds often diverge from traditional weather analyst forecasts because they incorporate real-time trader behavior, financial incentives, and crowd wisdom rather than relying solely on meteorological models. While meteorologists publish seasonal outlooks and long-range forecasts, this market aggregates the beliefs of participants who have money at stake, potentially surfacing consensus or contrarian views that institutional forecasters may not emphasize. Over time, prediction markets have shown competitive accuracy against expert predictions, especially when traders have access to the same underlying data. Comparing the two approaches can reveal where expert opinion and market sentiment align or diverge.

On Kalshi, this market is priced through an order-book mechanism where traders buy and sell shares corresponding to 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 for a particular outcome increases, its price rises; conversely, selling pressure lowers it. Traders profit by buying low and selling high, or by correctly predicting which outcome will occur. The platform's matching engine ensures transparent price discovery and continuous liquidity throughout the trading period.

This market resolves around Jul 1, 2026, once June 30, 2026 has passed and the lowest temperature for that day in San Antonio is verifiable from credible public sources. The outcome is determined by comparing the recorded low against the temperature thresholds defined in each outcome option. Once the data is confirmed and published by authoritative weather reporting, the winning outcome is declared and traders' positions settle accordingly. All shares in the correct outcome are redeemed at full value, while incorrect positions expire worthless.

Several factors can shift odds in this market: updated seasonal climate forecasts, changes in long-range weather models, historical temperature anomalies for late June in Texas, and shifts in broader climate patterns such as La Niña or El Niño. Major weather events or heat waves in the region during spring and early summer may influence trader expectations. As June 2026 approaches, short-range forecasts become more reliable, typically triggering sharper price moves. Media coverage of extreme weather or climate reports can also sway sentiment. Traders monitor the National Weather Service, climate indices, and historical temperature records to inform their positions.