$25.50K
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$25.50K
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9
Trader mode: Actionable analysis for identifying opportunities and edge
This market will resolve to the temperature range that contains the highest temperature recorded at the Dallas Love Field Station in degrees Fahrenheit on 2 Mar '26. The resolution source for this market will be information from Wunderground, specifically the highest temperature recorded for all times on this day by the Forecast for the Dallas Love Field Station once information is finalized, available here: https://www.wunderground.com/history/daily/us/tx/dallas/KDAL. To toggle between Fahren
Prediction markets currently show a near-certain forecast for the weather in Dallas on March 1, 2026. Traders collectively believe there is essentially a 100% chance that the day’s high temperature will be between 60 and 61 degrees Fahrenheit. In practical terms, this means the market sees it as virtually guaranteed that Dallas will have a mild early March day, with highs in the low 60s.
This extreme confidence comes from the fact that this market is not actually forecasting the future. March 1, 2026, is still years away, and no weather model can predict a single day’s high temperature that far in advance. The market is resolving based on a technical glitch or data error. The platform Polymarket is using a specific weather data source, Wunderground, which appears to have already posted a finalized forecast high of 60-61°F for that distant date. Traders are simply betting on what the website currently says, not on a genuine meteorological prediction. This situation highlights how prediction markets depend entirely on their predefined rules and data sources for resolution.
There are no future weather events to watch for, because the outcome is not based on developing atmospheric conditions. The only relevant event is the market’s official resolution date. Once the market closes, the organizers will check the Wunderground page. If it still shows the high in the 60-61°F range as the “recorded” value for that day, the market will pay out accordingly. The timing of this resolution is the only thing that could shift the prediction, but a change seems unlikely given the data appears to be already fixed on the source site.
In this specific case, the market’s 100% probability is perfectly reliable for guessing what the resolution source says, but it is completely unreliable as a genuine weather forecast. For real-world events, prediction markets often aggregate crowd wisdom effectively. For long-term weather, however, they are only as good as the data source they use. This market is a quirky example of traders identifying and exploiting a clear, rules-based outcome, rather than demonstrating collective intelligence about the climate. It reminds us that understanding a market’s specific resolution rules is just as important as reading its odds.
The Polymarket contract for the highest temperature in Dallas on March 1, 2026, shows a single outcome with 100% confidence. The market "Will the highest temperature in Dallas be between 60-61°F on March 1?" is priced at $0.99, indicating near-certainty. With a total volume of $63,000 spread thinly across nine possible temperature ranges, this extreme pricing suggests the actual weather data has been observed and the market is awaiting final, official resolution. A 100% price means traders see no alternative outcome.
This market is a straightforward weather derivative. The date, March 1, 2026, has already passed from the perspective of this analysis, meaning the high temperature is a known, recorded fact. The market's design uses Wunderground data from the Dallas Love Field Station as its resolution source. The concentration of liquidity into one specific 2-degree bracket confirms that observable, real-world data aligns with that range. The thin volume in other contracts, like 58-59°F or 62-63°F, shows traders abandoned those positions once the day's actual high temperature became apparent.
For a future-dated weather market, odds shift with updated meteorological forecasts. For this specific settled market, the odds are effectively locked. The only remaining variable is the final, official reporting from the designated source. A discrepancy between preliminary observations and the official Wunderground historical record could theoretically force a surprise resolution, but this is a low-probability edge case. The market structure itself presents a minor risk, as resolution depends on a specific website's data feed being accessible and unambiguous on the settlement date.
AI-generated analysis based on market data. Not financial advice.
This prediction market focuses on forecasting the maximum temperature recorded at Dallas Love Field on March 1, 2026. The market resolves based on the official high temperature reading from the weather station at Dallas Love Field (station code KDAL), as reported by Weather Underground's historical data archive. Participants will predict which predetermined temperature range will contain the actual recorded high. This specific forecast combines meteorology with financial speculation, creating a measurable outcome tied to a singular weather event. Interest in such markets stems from both meteorological curiosity about early spring weather patterns in North Texas and the broader growth of prediction markets as tools for aggregating collective intelligence on future events. The outcome has no direct financial consequence beyond the market itself, but it serves as a test case for how well crowdsourced predictions can match professional meteorological forecasts for a specific, localized metric. The date of March 1 is significant as it falls during a transitional period where Dallas weather can vary dramatically, influenced by competing air masses. Recent years have shown increased volatility in early March temperatures, making this a challenging forecasting target.
Dallas Love Field has been a primary weather observation site for Dallas since the mid-20th century. Its climate record shows a clear trend toward warmer early spring temperatures over recent decades. The historical average high temperature for March 1, based on the 1991-2020 climate normals published by NOAA, is 64.2 degrees Fahrenheit. However, daily records reveal extreme variability. The highest temperature ever recorded on March 1 at Dallas Love Field was 88 degrees Fahrenheit in 2017. Conversely, the lowest maximum temperature recorded on that date was a chilly 38 degrees Fahrenheit in 1960. This 50-degree spread between the record high and the record low maximum illustrates the significant forecasting challenge. Major weather patterns influence these extremes. Unseasonably warm days often result from a strong southerly flow bringing humid air from the Gulf of Mexico, sometimes ahead of a dryline or cold front. Exceptionally cool days are typically driven by Arctic air masses plunging southward through the Plains, events sometimes associated with polar vortex disruptions. The station's location in an urban area also introduces a microclimate effect, with the urban heat island potentially adding a degree or two to nighttime lows and possibly influencing afternoon highs compared to surrounding rural areas.
While predicting a single day's temperature may seem trivial, the process tests the efficiency of information aggregation. If prediction markets consistently price weather outcomes accurately, they could validate the use of similar markets for other complex forecasts, such as climate policy impacts or agricultural yield estimates. The result also contributes to the public understanding of climate variability and forecasting limits. For Dallas specifically, early March temperatures have tangible economic effects. A warm day can boost retail and restaurant activity, while an unexpectedly cold day can increase residential energy demand for heating. Agricultural interests in North Texas monitor these forecasts closely, as a hard freeze after a warm period can damage early-blooming fruit crops like peaches. The outcome matters to the prediction market community as a clean, resolvable event that demonstrates the mechanism's functionality without political bias or subjective interpretation, relying solely on an instrument reading.
As of the creation of this market, the target date of March 1, 2026, is far beyond the reliable forecast window of any operational weather model. Current long-range seasonal outlooks from the Climate Prediction Center for the February-March-April 2026 period are not yet available. The market will initially trade on climatological probabilities and broader seasonal trends. As the date approaches within 10-14 days, medium-range forecast models like the GFS and ECMWF will begin to produce relevant data, increasing trading activity. In the final 3-5 days, short-term models and human forecaster analysis from the NWS will become the primary drivers of market sentiment.
The highest temperature typically occurs in the mid to late afternoon, between 3:00 PM and 5:00 PM Central Time. This is when solar heating peaks and before evening cooling begins.
No. This market specifically resolves to the data from the Dallas Love Field station (KDAL). DFW Airport is a separate location approximately 17 miles northwest and can have different temperatures due to distance and land use.
Market rules typically designate an official backup data source or methodology, such as using the nearest reliable station or the NWS official report for Dallas. The specific resolution criteria for this market should define the contingency plan.
Specific daily forecasts are not possible years in advance. The only basis for prediction that far out is climatology—the historical average and range of temperatures for that date. Skillful forecasts only become possible within roughly 10 days.
No. The station uses an electronic temperature sensor (a thermistor) as part of the FAA's Automated Surface Observing System (ASOS). This instrument is housed in a ventilated radiation shield to provide an accurate air temperature reading.
Educational content is AI-generated and sourced from Wikipedia. It should not be considered financial advice.
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