Polymarket's 'Weatherman': Predict Temperature, Win Million-Dollar Payout

Original Title: "Polymarket Welcomes Two 'Sons of the Weather'"

Original Author: Mach, Foresight News

If someone told you that there were some clever traders making money by predicting the weather and temperature, would you believe it?

The trader in the image above, named neobrother, has been aggressively betting on the weather in various cities on Polymarket, currently accumulating over $20,000 in profits. He is not a reckless gambler but rather a highly data-driven, vertically specialized expert in leveraging odds. neobrother's trading record is almost exclusively focused on weather forecasting (Weather Markets), particularly the daily high temperatures of major global cities (Buenos Aires, Miami, Ankara, Chicago, New York).

He doesn't bet on the 'big picture' but only on 'precision,' much like a gridded arbitrageur in the meteorological field.

Take the Buenos Aires temperature prediction, for example. Instead of betting on just one temperature, he employed a 'Temperature Laddering' strategy, simultaneously buying Yes positions for 29°C, 30°C, 31°C, 32°C, 33°C, and even 34°C+. This approach is similar to 'wide straddle arbitrage' or 'grid trading' in options. By placing dense low-price orders (0.2¢ - 15¢) in a high-probability temperature range, if the temperature falls within that range, the super high returns from one or two positions (such as the 811.78% return from 31°C) can cover all losses from other ladders and result in substantial profits.

Furthermore, he excels at capturing some extremely low probability money-making opportunities. The unit price of most prediction markets he bought into was very low. For instance, on the 32°C position in Buenos Aires, his average buying price was only 0.7¢. This purchase price implies he secured nearly 142x potential odds. The screenshot shows that this position has now risen to 5¢ (a 733% increase).

He can use minimal costs to speculate on the price's drastic fluctuations caused by weather forecast deviations. This style demands a deep understanding of weather models (such as ECMWF or GFS) and the ability to decisively lurk when the market price lags behind in reacting.

This trader's 2373 predictions indicate extremely frequent and highly automated/systematized trading. He is most likely a quantitative or semi-quantitative trader who monitors weather forecast changes in real-time and places orders through scripts. He does not squeeze a large sum of money into a single position but continuously seeks hundreds of times returns through small costs, swiftly withdraws profits, or compounds for the next round.

He may have access to a more accurate and real-time weather prediction source than most Polymarket retail traders (possibly through access to a meteorological API). While politics and sports have too much noise, weather is pure physics and mathematics. As long as the model is accurate enough, this is his continuous ATM.

If this trader is a "weather geek" who accurately calculates the weather in a lab, then Hans323 is the "Black Swan Hunter" and "Top Odds Master" on Polymarket. In London weather prediction, he dared to place a single bet of $92,000 with only an 8% win rate, crazily making a profit of $1.11 million.

Hans323's operations have moved beyond simple prediction. He is utilizing **extremely asymmetric risk-reward** to conduct large-scale capital harvesting.

Looking at his winning record, buy prices are usually between 2¢ - 8¢. In the prediction market, this represents the market's belief that the event's probability is only 2% - 8%. While an average player may only invest $10 in a 2¢ position, Hans323 is willing to put in $92,632 at 8¢ (London temperature bet).

This strategy is similar to hedge fund manager Nassim Taleb's "leveraged investment." He doesn’t care if 90% of the predictions fail because hitting a return of 1,100% or even 5,300% once is enough to cover the costs of thousands of trial and errors.

Unlike neobrother's "full coverage ladder," Hans323 prefers to invest a large amount of capital at specific narrow points with statistical bias, requiring strong confidence and underlying model support.

In addition, looking at all his past transaction history, this trader may be a versatile player with a powerful data scraping team or intelligence source in a vertical domain. For example, in politics: betting on Trump issuing fewer than 10 executive orders in June (7¢ entry), in sports: decisively buying when Scottie Scheffler had very low odds to win the PGA Championship (2¢), and even successfully predicting the Time Magazine Person of the Year in the cultural field (6¢), this player has achieved impressive results.

When it comes to making money, when ordinary users track the transactions of Polymarket whales, they should not only look at their win rate but also track their fund skewness and pay attention to their own risk control. Because the same large loss can be worlds apart in terms of tolerance for different individuals.

Original Article Link