TOTAL VOLUME:
$134.1b
24H VOL:
$141,541,542
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,440,096,988
406,065
Markets across
30,522
events
MATCHED EVENTS:
2,692
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: May 28, 1:00 AM EST
Kalshi
On May 27, 2026, the National Weather Service will record the daytime high temperature in Washington, D.C. This event captures the full range of possible maximum temperatures that could occur that day.
Prediction market odds on Kalshi reflect real-money consensus from traders pricing in seasonal patterns, historical May temperatures in DC, and current atmospheric models. Traditional meteorological forecasts from NOAA and the National Weather Service rely on physics-based models and expert interpretation. Market odds often incorporate forward-looking sentiment and uncertainty premiums that differ from deterministic model outputs. Comparing the two reveals whether traders are pricing in more or less volatility than official forecasters expect for late May conditions in the DC region.
The market resolves on May 28, 2026, after the highest temperature reading for May 27, 2026, is officially recorded in Washington DC. Resolution hinges on the actual daily maximum temperature observed at the designated weather station. Traders holding contracts on the correct temperature range receive payouts, while incorrect predictions expire worthless. The precise measurement and timing of that official high temperature determine which outcome bracket wins and settles the market.
Major weather pattern shifts, updated seasonal forecasts, and real-time atmospheric data will drive odds movement. A strong high-pressure system developing over the East Coast could push temperatures higher, while an unexpected cold front or storm system could suppress them. Climate indices like the North Atlantic Oscillation and soil moisture anomalies influence late-May conditions. As May 27 approaches, short-range forecast models become more reliable, typically causing sharper repricing. Any significant deviation from historical May averages in the weeks leading up to the event will shift trader positioning.