What Polymarket’s Skilled Minority Actually Proves About Accuracy

A small minority of Polymarket accounts show evidence of persistent trading skill, but the evidence does not establish that their probability forecasts are consistently calibrated or that copying their trades will work. The working paper Prediction Market Accuracy: Crowd Wisdom or Informed Minority? identifies around 3% of accounts as persistently skilled. That is a finding about repeatable trading performance—not a 3% forecast-accuracy rate or a guarantee of future profits.

The authors argue that this minority helps make prices informative by reacting to public news, correcting inconsistent prices and trading against behavioral mistakes. The paper’s abstract supports that interpretation. It does not imply that every successful trader knows outcomes in advance, or that every Polymarket price is an accurate probability.

Choose the evidence available for a trader; see which accuracy claim it can support.

The Study Identifies Skill In A Sample, Not Every Profitable Account

The paper is by Roberto Gomez Cram, Yunhan Guo, Theis Ingerslev Jensen and Howard Kung, affiliated with London Business School and Yale. Its SSRN record lists April 20, 2026 as its date written, April 22 as its posting date, and June 25 as its latest revision. It remains listed as a working paper on Jensen’s research page, with a revise-and-resubmit status at The Review of Financial Studies, not final journal acceptance.

CNBC’s September report says the analysis covered $13.76 billion in Polymarket trades, and that the skilled 3% captured roughly 27% of dollar profits. That is substantial concentration. But 27% is not “most profits,” and the 3% figure is not the percentage of accounts that ever made money.

PlayUSA’s September 14 summary reports 1.72 million accounts across 210,322 markets over two years. It describes a statistical test that reran traders’ histories thousands of times to help separate skill from luck. These are sample counts reported in the coverage, not an October 2026 census of current users.

Reported Figure	What It Describes	What It Does Not Mean
Around 3%	Accounts identified as persistently skilled	All other accounts lost money
Roughly 27%	Dollar profits captured by that group	A forecast accuracy score
$13.76 billion	Trades covered by the reported analysis	Profits earned by traders
1.72 million	Accounts in the reported sample	Unique people or current users

The distinction is between having a profitable history and having a history that provides statistical evidence of skill. A few large wins can produce an impressive profit total without demonstrating repeatable ability. Equally, failure to identify skill does not prove that an account has none: a classification is an inference from the available record, not a complete description of its owner.

“Persistent” therefore needs a defined measurement window and test. It should not be read as “permanent.” The supplied reporting does not give a numerical probability that an identified trader will remain skilled in the future, nor a forecast-accuracy percentage for that group.

A Skilled Minority Can Improve Prices Without Making Everyone Accurate

The authors identify three mechanisms in their abstract. Each can improve prices without requiring the average participant to be an exceptional forecaster.

Reacting to public news means information need not be secret to create a trading opportunity. A trader can benefit by incorporating a public development before prices fully adjust. The relevant advantage is the interpretation or timing of the response, not necessarily exclusive access to information.

Correcting inconsistent prices means related contracts can imply conflicting valuations. Trading those discrepancies helps bring prices into alignment. Recognizing a contradiction between contracts is not the same task as estimating an event’s standalone probability with precision.

Trading against behavioral mistakes means the skilled minority takes the other side of errors made by the broader crowd. In the authors’ account, these trades help correct prices that reflect those mistakes.

The market price can consequently be informative even when many participants are not. The claim concerns how trading aggregates information: a relatively small group can influence the price that everyone sees. It is not a claim that every wallet contributing to that price is a reliable forecasting service.

Nor does the proposed mechanism establish equal accuracy across every contract. Evidence about a sample of trading activity does not certify a particular live market, a specialist’s entire record or an individual probability quote. Evaluating those requires evidence matched to the contract or trader being assessed.

Profit, Win Rate And Calibration Measure Different Things

Consider a hypothetical YES contract paying $1 if an event happens and $0 otherwise. A trader buys at 40 cents when the event’s true probability is 50%. If held to settlement, and ignoring costs, the expected profit is 10 cents per share—even though there is a 50% chance of losing the position’s purchase price.

Expected profit per YES share held to settlement, before costs, equals the event probability multiplied by the $1 payout, minus the purchase price.

This is an illustration, not a result from the paper. In an actual trade, the event’s true probability is not directly observable. A trader may believe the contract is underpriced without being able to demonstrate that belief from one outcome.

Measure	Question It Answers	What It Cannot Establish Alone
Profit	Did trades earn money at their entry and exit prices?	Calibrated probability forecasts
Win rate	How often did positions win under a stated definition?	Whether wins covered losses and costs
Calibration	Did events assigned 60% occur about 60% of the time?	Profitable trading opportunities

A winning position is not automatically evidence of a good forecast. An event considered unlikely can still happen; an event considered likely can fail to happen. Evaluating probabilities requires a collection of forecasts and outcomes, rather than treating each settled contract as a pass-or-fail prediction.

Win rate also depends on its definition. Winning at settlement and closing a position at a profit describe different records. Neither measure, without prices and sizes, tells readers whether the money earned on winners outweighed the money lost elsewhere.

Calibration instead asks whether stated probabilities match observed frequencies across an appropriate set of forecasts. The 60% example concerns a group of predictions, not a requirement that one particular event partially occur. Dollar profit concentration cannot answer that question.

For evaluating probability forecasts, Brier score and calibration are more directly relevant than dollar rankings. They address forecast quality, while profit also depends on the price at which someone could trade and the costs of doing so.

A Wallet’s Purchases Do Not Reveal Its Full Probability Forecast

Buying YES at 40 cents does not tell an observer exactly what probability the trader assigns to the event. The purchase establishes a transaction price. It does not distinguish between a trader who sees a small pricing discrepancy and one who believes the event is much more likely.

The same limitation applies when a wallet trades related contracts. A purchase might be part of a strategy to correct inconsistent prices rather than an isolated forecast of that contract’s outcome. Looking at one leg without its context can turn a pricing trade into an apparent directional prediction.

Exits add another distinction. A trader can benefit from a price change before settlement, whereas a probability forecast is evaluated against the eventual outcome at its stated horizon. A record of profitable exits is useful trading evidence, but it does not supply the missing probability estimates.

An evaluation of forecast accuracy therefore needs explicit, timestamped probabilities. A list of trades alone cannot reconstruct the trader’s complete beliefs. Assigning the purchase price as the trader’s forecast would confuse the market quote they accepted with the probability they believed justified the purchase.

Later Outcomes Are The Test Of A Transferable Record

To evaluate a particular trader, look for an analysis that identifies accounts using an earlier period and then tests them on later, unseen outcomes. This separates the record used to select the trader from the record used to evaluate persistence.

Selecting accounts after seeing their entire history can favor those that happened to perform well. A later test asks the more useful question: did the apparent advantage survive beyond the results that drew attention to it?

For forecasting, the evaluation should compare timestamped probabilities with contemporaneous market prices at the same forecast horizon. A trader’s forecast made shortly before resolution should not be treated as directly comparable to a market quote recorded much earlier. The later forecast may incorporate information that was not yet available.

The analysis should also account for related contracts resolving from the same underlying event. Multiple successful positions tied to that event do not necessarily provide independent demonstrations of accuracy. Counting contracts is not always the same as counting distinct forecasting tests.

These are criteria for evaluating a trader, not a claim that the working paper omitted such tests. The supplied summaries do not provide enough methodological detail to reproduce the paper’s classification or turn it into a wallet-screening rule.

There are two separate hurdles for a stronger forecasting claim. A trader’s probabilities must perform credibly on later outcomes, and comparison with the market must show what the trader adds. A calibrated forecaster who merely matches contemporaneous prices has not demonstrated an incremental forecasting advantage over those prices.

Copying A Skilled Trader Changes The Trade Being Evaluated

Even persuasive evidence of historical skill would not make that edge automatically transferable. For trading performance, an evaluation needs executable prices, position size and all-in costs, not just an attractive-looking entry on a wallet’s history.

A follower observing the trade later may face a different price. If the original advantage came from responding quickly to public news, a delayed copy does not reproduce that response. If it came from correcting a discrepancy between related contracts, copying only the visible purchase may omit the rest of the strategy.

The original account’s dollar profit also does not specify what another trader could earn at a different size. The supplied figures contain no universal cost-adjusted return estimate for copying the identified group. There is therefore no evidence-backed percentage to insert into a copy-trading profit projection.

Competition may change available opportunities as well. In CNBC’s report, Jensen expects stronger competition to reduce available edges, while analyst Julie Hoover sees room for specialists in niche markets. Those are forward-looking views, not measured guarantees about any account’s next trades.

The Supported Verdict Is Persistent Trading Skill, Not Guaranteed Accuracy

The study provides an evidence-backed explanation for informative Polymarket prices: a skilled minority can help correct them. The reported concentration of profits supports the importance of that minority, while the statistical classification distinguishes its record from simply having made money.

The stronger claim—persistent accuracy in a particular trader’s probability forecasts—requires different evidence. It needs explicit probabilities, later outcomes, a suitable calibration assessment and comparison with market prices at matched times. Profit totals cannot substitute for that record.

For the keyword claim about “Polymarket skilled traders persistent accuracy,” the defensible reading is therefore narrow: persistent trading skill has been identified in a small share of sampled accounts; persistent calibrated forecasting is not established by the headline profit figures. A profitable wallet is not automatically a forecasting service, and its historical edge is not automatically available to someone following it later. This is forecast analysis, not trading advice.