Top Earners Made Millions: What Strategies Do Polymarket’s Top Traders Use?
- Core Insight: There is no single profitable strategy on Polymarket’s prediction markets. The success patterns of top wallets can be divided into at least three distinct types, which are largely unrelated to one another. Position count and per-trade profit are two independent variables that define the fundamental differences among traders.
- Key Elements:
- Political markets far outweigh other categories in scale: The top 10 wallets in political markets generated a total profit of $94 million, vastly exceeding sports ($60 million) and crypto ($25 million). The top political earner made $22 million, while the sports category champion only earned $11.3 million.
- High-conviction heavy positions vs. high-frequency trading: Political whale “Theo4” earned $22 million with just 18 positions, averaging over $1 million per position. In contrast, sports trader “swisstony” accumulated $7.8 million through more than 150,000 positions, averaging just $45 per trade.
- Three distinct strategies: First, political experts (e.g., Theo4), relying on a few high-conviction heavy bets; second, systematic sports traders (e.g., swisstony), using automated models for thin-margin, high-frequency trades; third, cross-category generalists (e.g., MonsieurDimanche), profiting across nine different markets.
- Specialization and diversification both work: 100% of Theo4’s profits came from political markets, while MonsieurDimanche’s profits were spread across multiple categories, with no single category exceeding 31%. Both models can lead to the top.
- The "middle ground" is penalized: Successful traders on the leaderboard all specialize in a single track. Traders stuck in the middle in terms of breadth and trading volume struggle to replicate their success.
Original title: The Best Traders on Polymarket
Original author: Kiyotaka
Original compilation: SpecialistXBT, BlockBeats
Editor's note: In the crypto market, profit is the report card. This article explores whether the biggest winners in the prediction market rely on information asymmetry, models, conviction, or pure trading discipline, based on on-chain data from Polymarket's top wallets. The conclusion is that there is no one-size-fits-all strategy for consistently making big profits. The top three profitable well-known accounts use three almost entirely different methods of making money.
After studying the wallets that have made millions of dollars on the world's largest prediction market, it becomes clear that there isn't one unified approach, but at least three, and they have almost nothing in common.
If you frequently scroll through prediction market circles on Twitter, you'll quickly see the same set of anonymous IDs in various "biggest winners" list posts. Theo4 made a fortune in the 2024 election market. Swisstony quietly generates consistent profits from NBA betting markets. MonsieurDimanche seems to appear in the comments section of almost every market. Over time, you start to wonder: Are these people the same type? Are they doing the same thing? Is there a recognizable profile for someone who is "good at Polymarket"?
Intuitively, the answer is yes. Just like you'd think there's a common profile for people "good at poker": patience, mathematical ability...
But after looking at the on-chain data for all the Top 20 wallets on the platform, the real answer is: there is no such unified profile. There are at least three types, maybe more. Apart from all appearing on the leaderboard, they have almost nothing in common. This answer is more interesting than expected, so it's worth carefully unpacking what the data actually shows.
The data below comes from Polymarket, as of May 5th. Just the top 10 wallets in political markets account for $94 million in profit; the top 10 in sports contribute another $60 million; the third largest category, Crypto, contributes $25 million. This figure is less than the total profit of the top three wallets in politics alone.
Political Markets Are on a Different Scale
Comparing top wallets across categories on the same dollar scale. Political markets lead significantly, both in peak profit for a single wallet and total profit for the Top 10 wallets.
The top wallet in politics has earned $22 million. The top in sports is $11.3 million. The top in Crypto is $4.7 million. Unfortunately, this figure wouldn't even make the top 10 in politics.
This gap isn't an illusion created by power-law distribution. The 10th place wallet in politics has about $5 million in profit, surpassing the top wallet in every other category except sports. Political markets aren't "the same distribution but steeper"; they operate on a completely different level.
Plotting the total profit of the Top 20 wallets in each category on a logarithmic scale reveals that only the top wallets in Science and "Other" exceed $1 million, besides the three major categories of Politics, Sports, and Crypto.
The most straightforward explanation is that political markets are fewer in number, have larger bet sizes per position, and have longer settlement cycles. A correct prediction on a presidential election or a controversial policy outcome can be amplified into seven or eight-figure gains. Sports markets typically settle within hours, have thinner spreads, and yield smaller profits per trade. Market structure dictates which strategies can succeed.
High-Conviction Large Bets vs. High-Frequency Multi-Market Trading
When you plot the number of positions against realized profit, the leaderboard clearly splits into two groups. They share the same vertical axis but have almost nothing else in common.
A scatter plot of position count vs. trading P&L for the Top 10 wallets in Politics, Sports, and Crypto shows: political whales cluster at the low end of position count; sports whales dominate the high-frequency trading end.
On the left side of the chart, between roughly 1 and 100 positions, you find almost entirely political whales. The top wallet, 0x5668…5839, made $22 million with just 18 positions. Another wallet, 0xd235…0f29, made $11.3 million with only 2 positions.
On the right side of the chart, between 1000 and 150,000 positions, is the domain of sports traders. The second-place sports wallet, 0x204f…5e14, made $7.5 million across 151,888 positions. This looks more like the footprint of an automated system than an "investor with a view."
One wallet made $22 million with 18 positions. Another wallet made $7.5 million with 151,888 positions. They are on the same leaderboard, but they are not in the same business.
These are two completely different jobs. The first requires strong judgmental conviction and a willingness to place large bets on rare, high-stakes events. The second requires engineering discipline: a model with a thin profit margin per trade, deployed across enough markets for the law of large numbers to take effect. Crypto falls in between, exhibiting both styles, just on a smaller absolute scale.
Market Selection: Concentration and Diversification Coexist
Introducing 8 named wallets—accounts identifiable by name from Polymarket's public records—provides a clearer view of strategy distribution.
Sorting these 8 wallets by "percentage of total profit from the largest category," Theo4 is 100% concentrated in politics; MonsieurDimanche spans 9 categories.
100% of Theo4's $22 million profit comes from politics. 97% of swisstony's $7.8 million profit comes from sports. 87% of kch123's profit (the #1 sports trader) also comes from sports. These are specialist traders who don't easily cross boundaries.
On the other end, MonsieurDimanche spreads his $15 million profit across 9 categories, with no single category contributing more than 31%. He doesn't specialize in any one category yet still stands at the top of the leaderboard.
Conventional wisdom suggests that specialization leads to deeper advantages and therefore higher returns. This assessment holds true at the very top, but barely. Theo4, the most concentrated named wallet in terms of profit category, is also #1 in total profit. MonsieurDimanche, the most diversified, is #2.
Position Count vs. Profit Per Trade
The most useful chart in the entire dataset divides each wallet's profit by its number of positions, measuring the average dollar earned per bet.
On a log chart of profit per position, Theo4 and swisstony are both almost 100% concentrated in a single category, but they differ in selectivity by a factor of about 22,000x.
Theo4 earns an average of $1 million per position. Swisstony earns an average of $45 per position. Both are essentially single-category traders, nearly indistinguishable on the "concentration" axis. But on the "selectivity" axis, they differ by about 22,000x.
This is the most important analytical insight: position count and profit per trade are two independent variables. Conflating them obscures what the leaderboard truly reveals. Which market categories a wallet covers shows where the trader bets; how much profit is generated per unit of position count shows how the trader makes money. The two are not correlated.
Three Strategies Behind Eight-Figure Gains
The data reveals not one strategy, but three.
The first is the Political Specialist. In political markets with slow settlement, wide odds, and high stakes, they use a few high-conviction, high-value positions to capture massive gains. Few trades, large positions, deep research. Theo4 is the archetype. The main barrier to this approach is psychological: most traders cannot scale their positions enough for the strategy to yield significant returns. It's also not a traditionally scalable path.
The second is the Systematic Sports Trader. They use automated models to price sports markets. Even being just slightly better than the consensus price allows them to accumulate profits across thousands or even hundreds of thousands of contracts. Per-trade profits are thin, but the overall model is sustainable. Swisstony is the archetype. The barrier here is engineering skill and operational discipline, not mere market insight.
The third is the Cross-Category Generalist. They form well-calibrated judgments across many subjects and extract profits from markets that specialist traders ignore. MonsieurDimanche is the archetype. The barrier is breadth of knowledge, which is arguably harder to acquire than building a single-category model.
These skill sets are not interchangeable. A political specialist won't become a systematic sports trader by trading more frequently because their advantage doesn't lie there. A systematic sports trader won't become a political specialist by increasing position size because their per-trade margins are too thin to withstand highly concentrated positions. Prediction markets reward three distinct capabilities. Being good at one says almost nothing about being good at another.
In a way, this is reassuring. There is no single answer to "How to make money on Polymarket?" There are at least three answers. Which one is hardest for a given person depends on their personality, engineering skills, and how many high-quality opinions they can form on how many topics. And these differences are not erased by the leaderboard.
What the leaderboard truly punishes seems to be the middle ground: traders with enough breadth to dilute their specialization and enough volume to dilute their conviction. In other words, where most people likely are. The wallets at the top all chose a specific track to go deep on and had the discipline to stay on it.
