TOTAL VOLUME:
$134b
24H VOL:
$103,397,351
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,410,176,180
399,592
Markets across
30,097
events
MATCHED EVENTS:
2,622
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
$
The maximum daytime temperature in San Antonio on June 1, 2026, will be recorded by the National Weather Service.
On Kalshi, the Highest temperature in San Antonio on Jun 1 is priced as binary or range-based contracts tied to specific temperature thresholds. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. Traders buy or sell shares at prices between 0 and 100 cents, where the price reflects the implied probability of that outcome occurring. Each contract settles based on the actual recorded high temperature on June 1, 2026. Kalshi's order book displays bid-ask spreads, allowing traders to enter positions at competitive prices. Volume and liquidity on the contract determine how easily traders can scale positions in or out.
The market resolves on Jun 2, 2026, after the close of trading and official temperature data is recorded. Resolution is determined by the highest temperature recorded in San Antonio on June 1, 2026, as reported by the designated weather authority. The specific temperature threshold or range you selected in your contract determines whether your position settles to 100 cents (correct outcome) or 0 cents (incorrect outcome). Once the official high temperature is confirmed and published, Kalshi automatically settles all contracts tied to that event.
Several factors can shift odds for San Antonio's June 1 high temperature. Seasonal climate patterns, El Niño or La Niña conditions, and long-range weather models updated by meteorologists will influence trader expectations. As June 1 approaches, short-range forecasts from the National Weather Service become more precise, typically driving sharper price moves. Heat waves or cold fronts affecting the South-Central U.S. in late May can signal whether June 1 will be anomalously hot or cool. Real-time atmospheric data, upper-air patterns, and soil moisture conditions all feed into trader decisions, causing odds to drift as new information emerges.