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 starts from on-chain data of Polymarket’s top wallets to explore: are the big winners in prediction markets relying on information asymmetry, models, beliefs, or simply trading discipline? The conclusion is that a universal strategy for stable big profits does not exist; the top three profitable accounts each employ nearly unrelated methods of making money.

After studying the wallets that have earned millions of dollars on the world’s largest prediction markets, it becomes clear that there is no single approach, but at least three, and they have almost no common points.

If you often scroll through prediction market-related tweets, you’ll quickly see the same anonymous IDs on various “biggest winners” leaderboard posts. Theo4 has made a fortune in the 2024 election market. swisstony quietly continues to profit in NBA markets. MonsieurDimanche almost always appears in the comment sections of various markets. Over time, you might start to wonder: are these people the same type? Are they doing the same thing? Is there a certain recognizable profile for “people skilled at Polymarket”?

The intuitive answer is: yes. Just like you might think “skilled poker players” share certain traits: patience, mathematical ability…

But after examining the on-chain data of all Top 20 wallets on the platform, the real answer is: no such unified profile exists. There are at least three types, possibly more. Besides all appearing on the leaderboard, they have almost no commonalities. This answer is more interesting than expected, so it’s worth carefully analyzing what the data actually reveals.

The data below is from Polymarket, as of May 5. The top 10 wallets in political markets alone contributed $94 million in profit; the top 10 in sports markets contributed $60 million; the third-largest category, Crypto, contributed $25 million. This number is even less than the combined total of the top three wallets in political markets.

Political Markets Are a Different Level

Comparing the top wallets across categories on the same dollar scale, political markets clearly lead in both peak single-wallet gains and total profits of the top 10 wallets.

The top wallet in politics has earned $22 million. The top in sports earned $11.3 million. The top in Crypto earned $4.7 million. Unfortunately, this figure doesn’t even make it into the top 10 in politics.

This gap is not just an illusion caused by a power-law distribution. The 10th-ranked wallet in politics has about $5 million in profit, surpassing the top in all other categories except sports. Political markets are not “a slightly steeper distribution of the same kind,” but operate on a completely different level.

If you plot the top 20 wallets in each category on a logarithmic scale by total profit, only the top wallets in Science and “Other” categories exceed $1 million, aside from politics, sports, and Crypto.

The most straightforward explanation is: political markets have fewer events, larger individual bets, and longer settlement cycles. Correctly predicting the outcome of a presidential election or controversial policy can be magnified into seven- or eight-figure gains. Sports markets usually settle within hours, with thinner spreads and smaller individual profits. Market structure determines which strategies can succeed.

High-confidence heavy bets vs. high-frequency multi-market trading

If we look at position sizes alongside realized profits, the leaderboard clearly splits into two groups. They share a common vertical axis but have almost no other similarities.

A comparison chart of the top 10 wallets in political, sports, and Crypto markets shows: whales in politics cluster at low position counts; whales in sports dominate high-frequency trading.

On the left side of the chart, between about 1 and 100 positions, political whales are nearly filling the space. Wallet 0x5668…5839 earned $22 million with only 18 positions. Another wallet, 0xd235…0f29, made $11.3 million with just 2 positions.

On the right side, between 1,000 and 150,000 positions, are sports traders. Wallet 0x204f…5e14, with 151,888 positions, earned $7.5 million. This looks more like an automated system than an “opinionated investor.”

One wallet made $22 million with 18 positions. Another made $7.5 million with 151,888 positions. They are on the same leaderboard but are doing entirely different kinds of business.

These are two completely different approaches. The first requires extremely strong judgment and willingness to heavily bet on rare high-risk events. The second requires engineering discipline: a model with very thin profit per trade, deployed across enough markets to leverage the law of large numbers. Crypto sits between the two, with both styles present, just on a smaller scale.

Market choices: concentration and diversification coexist

Introducing 8 named wallets—accounts identifiable by name from Polymarket’s public data—makes the strategy distribution more visible.

Sorting these 8 wallets by “proportion of profit from the largest category,” Theo4 is entirely concentrated in politics; MonsieurDimanche spans 9 categories.

Theo4’s $22 million profit is 100% from politics. swisstony’s $7.8 million is 97% from sports. The top sports wallet, kch123, earns 87% from sports. These are all expert traders unlikely to cross over easily.

On the other end, MonsieurDimanche’s $15 million profit is spread across 9 categories, with no single category contributing more than 31%. He doesn’t focus on any one category but still ranks high on the leaderboard.

Traditional wisdom suggests specialization yields deeper advantages and higher returns. This holds true at the top, but only barely. Theo4, the most profit-concentrated named wallet, is also the top in total profit. MonsieurDimanche, the most diversified, ranks second.

Position sizes vs. profit per trade

The most useful chart in the entire dataset is the one showing each wallet’s profit divided by its position count, measuring how much profit on average each bet yields in dollars.

On a log scale of profit per position, Theo4 and swisstony are nearly 100% concentrated in a single category, but their selectivity differs by about 22,000 times.

Theo4 earns about $1 million per position on average. swisstony earns about $45 per position. Both are essentially single-category traders, nearly indistinguishable on the “concentration” axis. But on the “selectivity” axis, they differ by roughly 22,000 times.

This is the most important conclusion: position count and profit per trade are two independent variables. conflating them obscures what the leaderboard truly reveals. Which markets a trader bets on indicates where they place their bets; how much profit per unit of position indicates how they make money. The two are unrelated.

Three strategies behind eight-figure profits

The data does not show one strategy, but three.

The first is political expertise. In slow-settlement, high-odds, high-impact political markets, using a few high-confidence, high-stakes positions to reap huge rewards. Few trades, large positions, deep research. Theo4 is a typical example. The main barrier is psychological: most traders cannot scale their positions enough for the strategy to truly pay off. It’s not a scalable approach in the traditional sense.

The second is systematic trading in sports markets. Using automated models to price sports markets, even slightly better than consensus prices, can generate cumulative gains over thousands or hundreds of thousands of contracts. Profits per trade are thin, but the overall can be sustainable long-term. swisstony exemplifies this. The barrier here is engineering ability and operational discipline, not market insight.

The third is cross-category generalists. Able to form well-calibrated judgments across many topics and extract profits in markets overlooked by expert traders. MonsieurDimanche is a typical representative. The barrier is breadth of knowledge—more difficult to acquire than building a single-category model.

These skills are not interchangeable. Political experts won’t become systematic sports traders just by trading more often, because their advantage isn’t there. Sports systematic traders won’t become political experts by increasing their single-trade size, because their profit per trade is too thin to support highly concentrated positions. Prediction markets reward three separate skills. Excelling at one does not imply proficiency in the others.

In a sense, this is reassuring. “How to make money on Polymarket?” There is no single answer. At least three. Which is hardest depends on one’s personality, engineering ability, and how many high-quality opinions they can form. These differences are not smoothed out by the leaderboard.

What the leaderboard truly penalizes seems to be the middle ground: traders with enough breadth to dilute specialization but enough trading volume to dilute conviction. That’s where most people probably are. Top wallets have chosen a track to specialize deeply and have enough discipline to stay on that track.

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