Written by: Ma He, Foresight News
On the World Cup field, while teams fiercely compete for the championship trophy, a hidden whale has been quietly making a fortune on the prediction market.
An account on Polymarket with the nickname swisstony has a total historical profit of $18.62 million, with nearly $10.33 million earned in the last month alone. The account was first registered around July 2025, a relatively short time ago, but due to its astonishing profits, its profile page views have surged to 922,200.

As of July 13, the account has made a total of 139,617 predictions, with its current portfolio valued at approximately $606,100. Notably, its current holdings are almost entirely concentrated on the FIFA World Cup semi-final match between France and Spain on July 14, 2026. This includes a bet of around $160,000 on France losing the match. Additionally, it has placed numerous bets, primarily "NO" positions, on specific score details, aiming for 5%-10% returns.

The account's win rate is maintained around 52.9%, with total trading positions exceeding 245,000 and trading volume reaching hundreds of millions of dollars. These figures place it in the top tier within the overall Polymarket ecosystem. Public research indicates that most retail addresses incur long-term losses, while a few high-frequency, systematic accounts achieve significant positive returns through scaled execution. swisstony's data win rate is not extremely high, but combined with extremely high trading frequency and position management, it amplifies its positive EV (Expected Value) edge.
Since creating the account about a year ago, this address has completed 139,617 prediction operations. On average, this translates to about 380 trades per day, 16 per hour, operating 24/7 without rest. It is highly likely an API-driven, ultra-high-frequency quantitative trading bot.
Its profile description reads "trash panda." In North American culture, raccoons are survival experts known for rummaging through trash bins. This signature perfectly summarizes its core strategy: making money from the vast data garbage and tiny price discrepancies on Polymarket, ultimately building a multi-million dollar empire.
Over 17 Profits Exceeding $1 Million
Looking through the account's profit history, its astonishing aspect is that it has recorded over 17 instances where profits exceeded $1 million. The largest single profit came from a bet on Germany's match on June 25. The whale bet "NO," earning $2,221,241 with a return of 111.67%.

The ROI shown in the screenshot is generally very high, with clear advantages in entry prices. The investment scale is substantial, with single bets often in the $400,000 to $1 million range.
This whale favors placing large "NO" bets (against winning) on strong teams perceived as overvalued by the market: Germany, Paraguay (multiple appearances), England, and Japan. Entry prices mostly ranged from 35.8¢ to 53.7¢, implying market-implied win probabilities for these strong teams between 46% and 64% at the time, but the actual result was that they lost or did not win. This is a classic anti-favorite strategy.
100x Returns
On prediction markets, when events deemed impossible by the market actually occur, the profit returns can be extremely exaggerated. This whale excels not only at winning big with big bets but also demonstrates high skill in winning big with small bets.
Taking the matches in the image as examples, the entry prices were extremely low: 0.2¢ to 1.2¢ (market-implied probability only 0.2% to 1.2%). The invested capital per bet was mostly only a few thousand dollars, yet each contributed profits exceeding $100,000.

These events, originally considered nearly impossible by the market, actually happened. The account captured high returns with minimal cost.
Deploying small capital on extremely low-probability events is akin to a systematic "lottery ticket" approach. When it hits, it can contribute profits of $100,000+ with very low cost, serving as an excellent supplement to overall profitability. Although the risk capital per trade in such high-multiple trades is low, the win rate is extremely low. Most similar bets would lose all capital.
Even though most such bets will lose (because the probabilities are indeed very low), as long as a few hit occasionally, they can significantly boost total profit without costing too much principal.
Overall, it's highly likely that the account's automated system covers a large number of niche, low-liquidity markets where severe mispricing is more likely to occur. It then executes a dual-track strategy for profitability.
Large capital bets against popular strong teams, and small capital bets on extreme underdogs. The combination of both ensures stable, substantial profits while also enhancing overall returns through high-multiple trades.





