Highest temperature in San Antonio on Jul 5, 2026?

Prediction market odds reflect real-money trader conviction and aggregate information, often diverging from traditional weather forecasts or seasonal climate models. While meteorologists typically issue forecasts only days or weeks in advance, this market allows traders to price in longer-term climate patterns, historical July heat trends for San Antonio, and emerging atmospheric signals. The odds can serve as a cross-check against published analyst views: if the market is pricing a much higher or lower probability than seasonal norms suggest, it may signal traders are incorporating information or uncertainty that conventional forecasts haven't yet emphasized.

On Kalshi, this market is priced through a continuous order book where traders buy and sell shares corresponding to different temperature ranges or outcomes. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Each share represents a claim on a specific outcome—for example, whether the high will exceed a certain threshold. The price of each outcome reflects the collective willingness of buyers and sellers to trade at that level, with tighter spreads indicating higher confidence and liquidity. As new information emerges or traders reassess their views, prices adjust in real time to clear the market.

This market resolves around Jul 6, 2026, after July 5, 2026 has concluded. The outcome is determined by the verified highest temperature recorded in San Antonio on that date, confirmed once credible public reporting becomes available. Traders holding shares in the correct outcome receive their payout, while incorrect positions expire worthless. The resolution hinges on an objective, observable measurement rather than subjective judgment, making it a straightforward event to settle once the day's weather data is finalized.

Several factors could shift odds significantly. Long-range climate forecasts or seasonal outlooks released closer to July 2026 may suggest an unusually hot or mild summer pattern. Historical heat waves or cold snaps in prior years could prompt traders to reprice tail-risk scenarios. Real-time weather models issued in late June will carry substantial weight as the date approaches. Additionally, any major atmospheric events—such as El Niño or La Niña transitions, or unusual jet-stream positioning—could alter expectations. As the event date nears, daily forecasts will become increasingly precise, likely tightening the market and concentrating trading volume.