Yale Study Finds 3% of Polymarket Traders Capture 27% of Bitcoin (BTC) Betting Profits

3% of Accounts Take 27% of Profits

A new academic study reports that a tiny fraction of traders on Polymarket, the largest crypto-adjacent prediction market, is capturing the bulk of the platform's profits. The working paper, produced by researchers at Yale and the London Business School, analyzed two years of trading history spanning roughly 1.72 million accounts and 210,322 markets. Its central finding: about 3% of accounts collected approximately 27% of all dollar-denominated profits on the platform. That concentration has been the defining feature of prediction-market trading since volumes surged alongside Bitcoin (BTC) event contracts and election markets, but the researchers argue the dynamic is now under pressure. Wall Street firms are directing order flow into these venues, and the resulting competition is narrowing the margin that skilled retail and proprietary traders have historically enjoyed. The paper frames Polymarket's order-book and automated market maker infrastructure as increasingly efficient, meaning the easiest mispricings are being arbitraged away. For a market that grew up on crypto-native liquidity, the arrival of institutional depth marks a structural turning point in who can consistently profit.

The methodology behind the finding is what gives it weight. The authors ran a statistical test that replays each trader's full history thousands of times, separating genuine skill from a lucky streak — a distinction most performance dashboards cannot make. Theis Jensen, a Yale economist and co-author, expects the share of consistently skilled traders to fall from roughly 3% to below 1% as institutional competition intensifies. His reasoning: when many skilled participants bid against each other, their competing orders push quoted prices closer to true probabilities. Jensen put it directly — a large pool of skilled traders competing among themselves makes prices more correct. Julie Hoover, an equity analyst at Bank of America, adds that tighter spreads make mispricing harder to find, though she sees room for smaller specialists in niche contracts. The platform's unusually wide range of markets lets specialists build deep, narrow expertise, and Jensen notes that large institutions tend to avoid low-liquidity markets, since even modest orders there erode their own edge. That leaves durable pockets where focused traders can still outperform.

Nvidia's Top 3 Buyers Hit 44%

The capital flowing into prediction markets comes from the same institutional complex whose concentration risks are showing up elsewhere in filings. Disclosure data for Nvidia shows the chipmaker's customer base narrowing sharply: in the first half of fiscal 2027 (February 2026 to January 2027), the largest customer accounted for 16% of revenue, the second 15% and the third 13% — a combined 44%. In fiscal 2026 the top two buyers represented 36%, and as recently as fiscal 2023 no single customer exceeded 10%. Including receivables, the five largest customers generated 70% of first-half fiscal 2027 revenue. Data center revenue, the segment carrying the AI chip business, expanded from $15 billion in fiscal 2023 to $193.7 billion in fiscal 2026, with consensus expecting fiscal 2027 sales to double year over year. Michael Burry, known for calling the 2008 subprime crisis, has cited the deepening customer concentration as a key risk in recent months. Nvidia CFO Colette Kress said in February that five cloud providers account for more than half of data center revenue, while rivals developing their own silicon — a path peers like AMD have long pursued — adds a second layer of exposure. Nvidia is countering by investing in neocloud firms such as CoreWeave and Nebius to broaden its buyer base. Readers tracking the market in real time can follow live spot and futures prices on Gate.

Better Prices, Narrower Edges Ahead

Read together, the study and the Nvidia disclosures describe one arc: institutional capital is maturing crypto-adjacent markets while concentrating power among a few large players. In prediction markets, that means profits skew further toward the most sophisticated firms even as everyone else benefits from more accurate prices — and a Federal Reserve working paper lends credibility to the space, finding that Kalshi's macroeconomic contracts matched or beat standard forecasting benchmarks, with its headline inflation forecast outperforming the Bloomberg consensus. In our reading, better-calibrated contract prices strengthen these venues as hedging and forecasting tools alongside crypto options, and rising institutional volume expands platform fee revenue. The edge is migrating to specialists — and the largest funds.