Top traders on Polymarket are earning tens of millions of dollars. What strategies are they using?
- Core Takeaway: There is no single profitable strategy for the Polymarket prediction market. The success patterns of top wallets fall into at least three distinct categories that are almost completely uncorrelated. Position count and profit-per-trade are two independent variables that define the fundamental differences between traders.
- Key Elements:
- The scale of political markets far exceeds other categories: The total profit of the top 10 political wallets reached $94 million, significantly outpacing sports ($60 million) and crypto ($25 million). The top political trader earned $22 million, while the sports champion only made $11.3 million.
- High-Conviction Heavy Positions vs. High-Frequency Trading: Political whales like "Theo4" earned $22 million with only 18 positions, averaging over $1 million in profit per position. In contrast, sports traders like "swisstony" accumulated $7.8 million through more than 150,000 positions, averaging just $45 per position.
- Three Independent Strategies: First, political experts (like Theo4) rely on a few high-conviction, heavy positions. Second, systematic sports traders (like swisstony) use automated models for thin-margin, high-frequency profits. Third, cross-category generalists (like MonsieurDimanche) diversify profits across 9 different markets.
- Specialization and Diversification Coexist: 100% of Theo4's profits come from political markets, while MonsieurDimanche's profits are spread across multiple categories with none exceeding 31%. Both models can lead to the top.
- The "Middle Ground" is Penalized: Successful traders on the leaderboard are all deeply specialized in a single track. Traders caught in the middle in terms of breadth and volume find it difficult to replicate their success.
Original Title: The Best Traders on Polymarket
Original Author: Kiyotaka
Original Translation Compiled by: SpecialistXBT, BlockBeats
Editor's Note: In the crypto market, profit is the report card. This article delves into the on-chain data of Polymarket's top wallets, exploring whether the biggest winners on the prediction market rely on information asymmetry, models, conviction, or pure trading discipline. The conclusion is that there is no single universal strategy for consistent big profits; the top three profitable known accounts employ three almost entirely different methods of making money.
Studying the wallets that have made millions on the world's largest prediction market reveals that there isn't one unified approach, but at least three, with almost nothing in common.
If you frequently browse prediction market circles on Twitter, you'll quickly see the same anonymous IDs topping various "biggest winners" list threads. Theo4 cleaned up in the 2024 election markets. Swisstony quietly generated consistent profits through NBA betting lines. MonsieurDimanche seems to appear in the comments section of almost every market. Over time, you start to wonder: Are these people the same type? Do they do the same things? Is there an identifiable profile for someone who is "good at Polymarket"?
Intuitively, the answer is yes. Just like you might think there's a common profile for someone "good at poker": patience, mathematical ability...
But after examining the on-chain data of all top 20 wallets on the platform, the real answer is: there's no such unified profile. There are at least three types, possibly 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 breaking down exactly what the data reveals.
The data below is from Polymarket, up to May 5th. The top 10 wallets in political markets alone contributed $94 million in profits; the top 10 in sports contributed $60 million; the third largest category, Crypto, contributed $25 million. This figure is even less than the total of the top three political wallets.
Political Markets Operate on a Different Level
Comparing the top wallets across categories using the same dollar scale. Political markets lead significantly, both in peak profit for a single wallet and in the total profit of the top 10 wallets.
The top wallet in politics has already 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 crack the top 10 in politics.
This gap isn't an illusion caused by a power-law distribution. The 10th place wallet in politics has around $5 million in profits, surpassing the top wallet in every other category except sports. Political markets aren't just "the same distribution but steeper"; they operate on a completely different tier.
Plotting the total profits of the top 20 wallets for each category on a logarithmic scale shows that, besides the top three categories (Politics, Sports, Crypto), only the top wallet in Science and "Other" surpasses $1 million.
The most straightforward explanation is that political markets are fewer in number, have larger individual bet sizes, and longer settlement cycles. A correct prediction on a presidential election or a controversial policy outcome can be amplified into seven or even eight-figure returns. Sports markets typically settle within hours, have thinner spreads, and yield smaller single-position profits. Market structure dictates which strategy prevails.
High-Conviction Heavy Betting vs. High-Frequency Multi-Market Trading
Plotting the number of positions against realized profits clearly divides the leaderboard into two groups. They share the same vertical axis but have almost nothing else in common.
A comparison of position counts and trading P&L for the top 10 wallets in politics, sports, and crypto shows: political whales cluster at the low end of position counts; sports whales dominate the high-frequency trading end.
On the left side of the chart, between roughly 1 and 100 positions, we find almost exclusively political whales. The top wallet, 0x5668…5839, earned $22 million using only 18 positions. Another wallet, 0xd235…0f29, earned $11.3 million with just 2 positions.
On the right side of the chart, between 1,000 and 150,000 positions, is the domain of sports traders. The second-ranked sports wallet, 0x204f…5e14, earned $7.5 million across 151,888 positions. This looks more like the footprint of an automated system than an "investor with an opinion".
One wallet made $22 million from 18 positions. Another made $7.5 million from 151,888 positions. They are on the same leaderboard but are not playing the same game.
These are two completely different types of work. The first requires extremely strong judgment conviction and the willingness to make heavy bets on rare, high-stakes events. The second demands engineering discipline: a model with thin per-trade margins deployed across enough markets for the law of large numbers to take effect. Crypto sits in the middle, containing both styles, but on a smaller absolute scale.
Market Selection: Concentration and Diversification Coexist
Introducing 8 named wallets—those identifiable by name from public Polymarket information—provides a clearer view of the strategy distribution.
Sorting these 8 wallets by "maximum category profit as a percentage of total profit," Theo4 is entirely concentrated in politics; MonsieurDimanche spans 9 categories.
Theo4's $22 million profit comes 100% from politics. 97% of swisstony's $7.8 million profit comes from sports. 87% of the profits for the top sports trader, kch123, also come from sports. These are specialist traders who don't easily cross over.
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 area yet still sits at the top of the leaderboard.
Conventional wisdom suggests that specialization leads to deeper advantages and thus higher returns. This holds true at the very top, but only just. Theo4 has the most concentrated profit categories among named wallets and is ranked first in total profit. MonsieurDimanche is the most diversified and ranks second.
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.
Theo4 averages $1 million in profit per position. Swisstony averages $45 in profit per position. They are essentially single-category traders, nearly indistinguishable on the axis of "concentration." But on the axis of "selectivity," they differ by approximately 22,000 times.
This is the most critical analytical takeaway: position count and profit per trade are two independent variables. conflating them obscures what the leaderboard truly reveals. Which market categories a wallet covers indicates where a trader places bets; how much profit a trader generates per unit position indicates how they make money. The two are unrelated.
Three Distinct Strategies Behind Eight-Figure Returns
The data reveals not one strategy, but three.
The first is the Political Specialist. In slow-settling, high-odds, consequential political markets, use a few high-conviction, high-amount positions to reap massive rewards. Few trades, large positions, deep research. Theo4 is the classic example. The barrier to this approach is primarily psychological: most traders cannot size positions up enough for the strategy to yield significant returns. It is also not a path that scales in the traditional sense.
The second is the Sports Market Systematizer. Use automated models to price sports markets. Even if the model is only slightly better than the consensus price, profit accumulates across thousands or even hundreds of thousands of contracts. Per-trade margin is thin, but the overall strategy can be sustained over time. Swisstony is the classic example. The barriers here are engineering capability and operational discipline, not just market insight.
The third is the Cross-Category Generalist. Form well-calibrated judgments across many different topics and extract profits from markets that specialist traders might overlook. MonsieurDimanche is the classic example. The barrier here is breadth of knowledge, which is arguably harder to acquire than building a single-category model.
These skills are not interchangeable. A political specialist won't become a sports systematizer just by trading more frequently because their advantage doesn't lie there. A sports systematizer won't become a political specialist just by increasing single position size because their per-trade margins are too thin to withstand highly concentrated positions. The prediction market rewards three distinct capabilities. Being good at one says very little about being good at another.
In a sense, this is reassuring. There is no single answer to "How do you make money on Polymarket?" There are at least three. Which one is hardest for a particular 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 flattened by the leaderboard.
What the leaderboard truly punishes seems to be the middle ground: traders who have enough breadth that it dilutes their specialization, and enough trading volume that it dilutes their conviction. This is likely where most people reside. The wallets at the top have all chosen a single lane and have enough discipline to stay there.
