TOTAL VOLUME:
$134.1b
24H VOL:
$113,466,932
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,423,222,590
402,751
Markets across
30,217
events
MATCHED EVENTS:
2,632
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: May 29, 8:00 AM EST
Polymarket
This market tracks whether the highest temperature recorded in Lucknow will reach 38°C or below on May 29, 2026. On Polymarket, the leading outcome—temperatures of 38°C or lower—stands at 99.4%, while the outcome of exactly 39°C registers at 0.5%. Resolution will be determined by historical weather data from Weather Underground, using measurements from the Chaudhary Charan Singh International Airport Station. Watch for actual temperature readings as May 29, 2026 approaches, since the final settlement depends on the precise high temperature recorded on that specific date.
Prediction market odds on Polymarket reflect real-time trader conviction about Lucknow's maximum temperature on May 29, often incorporating weather models and historical data faster than traditional analyst forecasts. While meteorological agencies issue seasonal and medium-range predictions, prediction markets aggregate dispersed information through financial incentives, sometimes diverging from official forecasts when new data emerges. Comparing market odds to analyst consensus helps identify where traders see undervalued or overvalued temperature scenarios relative to expert opinion.
The market resolves on May 29, 2026, after the highest temperature in Lucknow on May 29 is officially recorded. Resolution depends on verified temperature data from recognized meteorological sources for that specific date and location. Once the actual maximum temperature is confirmed, the outcome is determined and traders' positions settle accordingly. Early resolution is possible if official data becomes available before the end date.
Temperature predictions for Lucknow on May 29 can shift based on updated weather forecasts, monsoon onset timing, atmospheric pressure patterns, and seasonal climate anomalies. El Niño or La Niña conditions, soil moisture levels, and urban heat island effects also influence outcomes. Major weather model updates from meteorological agencies typically trigger repricing. Historical temperature records and recent heat waves in the region provide context for traders assessing extreme temperature scenarios. Traders monitor real-time weather data and forecaster revisions continuously.