| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 96° or above | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 92° to 93° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 87° or below | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 88° to 89° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 90° to 91° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 94° to 95° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which temperature range will contain the highest temperature recorded in San Antonio on March 25, 2026. It matters because traders aggregate weather forecasts and observations to form a market view of that day's peak temperature.
Late March is a transitional month in south-central Texas when temperatures can swing because of cold fronts, Gulf moisture, or early spring heat. The market is hosted on Kalshi with six discrete outcomes (temperature ranges); the close time is listed on the event page (currently TBD).
Market prices represent how traders collectively price the relative likelihood of each temperature range given available forecasts and observations; use them as a real-time, crowd-sourced forecast signal rather than a guarantee.
The exact resolving data source and station are specified in the Kalshi event rules on the event page; typically these markets rely on an official NWS/NOAA observing station for the city—check the event description to confirm the chosen station and dataset.
The six mutually exclusive outcomes correspond to the temperature ranges shown on the event page; that page also explains how boundary values are handled and the numeric cutoffs for each outcome.
The event rules define the applicable timezone and resolution timing—typically the local date in San Antonio is used and the market resolves after the official source publishes the daily maximum or at the resolution time listed on Kalshi; check the event page for the precise rule.
That measurement definition is provided in the event's resolution rules. Many weather products report a daily maximum (based on instantaneous observations or short averaging windows), so consult the event description to see which method applies here.
Short-term changes such as the approach or timing of a cold or warm front, model updates altering cloud/precipitation forecasts, shifts in wind direction or moisture advection from the Gulf, and late-night/early-morning temperature trends are all likely to cause traders to update expectations and move prices.