Lowest temperature in Oklahoma City on Jun 17, 2026?

Prediction market odds on this market represent real-money forecasts from traders, while traditional analyst forecasts come from meteorologists and climate models. Markets often incorporate broader data sources and incentivize accuracy through financial stakes, whereas analyst predictions rely on established weather science and historical patterns. Both approaches have merit: markets can be faster to react to emerging signals, while analysts bring domain expertise and peer review. Comparing the two reveals whether traders are pricing in risks that official forecasts may underweight or overlook. Over time, tracking both provides insight into how different forecasting methods handle seasonal temperature prediction.

On Kalshi, this market is priced through a continuous order-book mechanism where traders submit bids and asks for different temperature outcome ranges. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The platform matches buyers and sellers in real time, and the midpoint of the spread reflects the current consensus forecast. Each outcome bucket—such as "below 65°F" or "65–75°F"—has its own price, and all prices across outcomes sum to 100 cents, ensuring internal consistency. As new information arrives or trading volume shifts, prices adjust automatically. This transparent, auction-style pricing allows you to see exactly what the market believes about the lowest temperature on that date.

This market resolves around Jun 18, 2026, after June 17, 2026 has passed. The outcome is determined by the verified lowest temperature recorded in Oklahoma City on that date. Once the event is confirmed through credible public reporting—typically from the National Weather Service or equivalent official weather data—the market settles to the outcome range that matches the actual low. Traders holding shares in the correct outcome range receive their payout. The resolution process is automatic once the data is finalized, ensuring all participants see the same result.

Several factors can shift odds in this market. Seasonal weather pattern updates, such as shifts in the jet stream or development of high-pressure systems, often trigger price moves. Long-range forecasts from the National Weather Service or other meteorological agencies can influence trader sentiment weeks in advance. El Niño or La Niña conditions may affect regional temperature trends. As June 17 approaches, short-range forecasts become more reliable and typically cause sharper repricing. Unusual climate events or anomalies in spring temperatures leading up to the date can also reshape expectations. Trading volume often increases closer to the resolution date as forecasts narrow and uncertainty decreases.