How Concentrated Is Prediction-Market Profit?
One question, one answer per study. This page tracks whether profit is clustered among a small cohort of accounts — not what percent of individual users make money.
What this page is NOT
Headline stat by study
Rows stay pending until primary URLs and verbatim quotes are available.
What each study measures — and what it does not
Why concentration is not the same as user-level profitability
Concentration metrics describe the shape of the profit distribution: whether a small cohort of accounts captures a disproportionate share of realized gains. That is structurally different from asking what percentage of users or wallets are profitable. One trader can run many wallets, one desk can control many accounts, and one account can represent tooling or capital that ordinary users do not have.
Skill-based concentration therefore says more about clustering, market-making, speed, and repeated participation than it says about the average trader's win rate. A market can have some profitable retail users and still have a fat-tailed distribution where the largest profits sit in a tiny top cohort. This page keeps those axes separate so concentration evidence does not get flattened into a claim about winners, losers, or the wisdom of crowds.
What this means for retail traders
- Treat concentration as a distribution-shape signal: a small cohort can capture outsized profit without answering how many ordinary users win or lose.
- Separate wallet/account counts from human users; one trader can operate many wallets, and one desk can create many account-level traces.
- Assume the top tail often has infrastructure advantages — speed, capital, market-making tooling, or primary-source workflows — rather than just better guesses.
- Use concentration evidence as context for risk expectations, not as a trading recommendation or policy conclusion.
FAQ
Is this page saying most prediction-market users lose money?
What does the LBS/Yale study measure here?
Does a concentrated profit distribution mean markets are rigged?
Why not combine this with the percentage-of-users-who-profit page?
Are the 1,950 accounts named?
Can retail traders use this as advice?
Understand the edge
Can retail traders win?
The retail-survivability question adjacent to concentration evidence.
Why bots lose money on execution
Execution, slippage, and live-market mechanics that can shape edge quality.
Is this real arbitrage?
How to separate durable edge from false-arbitrage or friction-driven signals.
Platform architecture map
How exchanges, wrappers, routers, perps rails, and intelligence layers fit together.
Polymarket troubleshooting hub
Practical platform-mechanics context for user-facing problems.