World Cup prediction market’s strongest whale? Trades 380 times a day, making $10.32 million in profit

Raking in $10.32 million, Polymarket’s World Cup printing-machine whale

By Mahe, Foresight News

By Foresight News

Source:

Repost: Mars Finance

On the World Cup pitch, while teams fiercely compete for the Hercules Cup, a hidden whale is quietly making a fortune in prediction markets.

On Polymarket, an account with the nickname swisstony has total historical profits of $18.62 million, with profits reaching $10.33 million in the past month alone. The account’s earliest registration time is July 2025. It hasn’t been around long, but because its earnings are astonishing, views on its homepage have risen to 922.2k.

As of July 13, the account has made a total of 139,617 predictions, with its current open position worth about $606.1k. Notably, almost all of its current holdings are concentrated in the July 14, 2026 FIFA World Cup semifinal: France vs Spain. This includes betting that France will lose the match, with roughly $160k already wagered. In addition, it has also bet heavily on specific scoreline details, mainly by choosing NO, aiming to capture 5%-10% returns.

The address’s win rate stays in the 52.9% range. It has more than 245k total trading positions, with trading volume at the multi-hundred-million-dollar level. These figures place it in the top tier within Polymarket’s overall ecosystem. Public research shows that most retail addresses lose over the long run, while a small number of high-frequency, systematized accounts achieve significant positive returns through large-scale execution. swisstony’s win rate isn’t extremely high, but combined with very high trading frequency and position management, it amplifies the advantage of positive EV (expected value).

About a year since creating the account, the address has completed 139,617 prediction operations. Converted out, it executes about 380 trades per day on average, 16 per hour, 24/7 without rest. Most likely, it is an ultra-high-frequency quantitative bot driven by APIs.

Its bio is filled with “trash panda” (raccoon). In North American culture, raccoons are masters of survival who like to rummage through trash bins. This signature precisely summarizes its core strategy: make money amid Polymarket’s massive data “garbage” and tiny price spreads, and ultimately stack up an empire worth tens of millions of dollars.

More than 17 times profited over $1 million

Looking at this address’s profits, what’s astonishing is that it has 17 instances where profits were all above $1 million. The largest single one was a win/loss bet for Germany on June 25. This whale bet NO and earned $2,221,241, with a profit of 111.67%.

The screenshot’s ROI is generally high, with a clear advantage in entry price. The position size is also large, with each trade often in the $400,000-$1M range.

This whale likes placing大量押 NO (not to win), targeting strong teams that the market is overpricing: Germany, Paraguay (appearing multiple times), England, and Japan. Its entry prices are mostly in the 35.8¢-53.7¢ range. At the time, the market implied win probabilities for these strong teams were about 46%-64%, but the actual results were that they lost or failed to win. This is a typical anti-trend strategy.

100x returns

In prediction markets, when something the market thinks is impossible eventually happens, the profit return can be extremely exaggerated. This whale is not only good at going big when the odds seem unfavorable but also has a strong ability to go small when the odds appear favorable.

Taking the pictured match as an example, the entry price is extremely low: 0.2¢–1.2¢ (market-implied probability only 0.2%-1.2%). The capital deployed is mostly only a few thousand dollars, yet the profit contribution per trade is over $100k.

These things that the market originally considered nearly impossible actually happened, and the account used extremely low costs to reap high returns.

Laying out small capital on extremely low-probability events is basically “lottery-style,” but executed systematically. Once it hits, it can contribute $100k+ profit at very low cost, which is a great supplement to overall earnings. These high-multiple trades may have low risk capital per trade, but the win rate is extremely low. Most similar bets would lose everything.

Even if most of these bets lose (because the probability really is that low), as long as it hits only a few times occasionally, it can significantly lift total profit without dragging down too much principal.

Overall, it’s highly likely that an automated system covers a large number of obscure, low-liquidity markets. In those markets, severe mispricing is easier to occur, and then it executes a two-track strategy in parallel to generate profits.

Big capital bets the anti-trend against strong teams, while small capital bets extreme obscure outcomes. Combined, they not only ensure stable large profits, but also improve overall ROI through high-multiple trades.