What is Wash Trading?
Wash trading is fake trading: a trader buys and sells the same token with themselves, or with a ring of wallets they control, until the volume number looks big while no ownership changes hands. That fake volume can make a token look more liquid and more popular than it is, pushing you to overpay or buy into something you later can't sell.
- Volume anomalies
- Risk tiers
- Editorial impact
Overview
We watch every token's price and volume for the patterns fake trading leaves behind. We score what we find from 0 (clean) to 100 and map that score to a plain label.
This is our own automated read of the evidence, not financial advice. It doesn't say whether a token is safe to buy.
How we detect it
We run four independent checks. Each looks for a different fingerprint of fake volume, and a token can trip one without tripping the others.
- Volume against size: we compare a day's trading volume to the token's total market value. A healthy token turns over a small share of its value each day. Volume near or above the full market value rarely comes from real buyers, and above three times that value, it almost certainly comes from wash trading.
- Price that won't move: real buying and selling pushes a price around. We look for hours where volume jumps but the price barely moves. Heavy volume with almost no price movement is a classic sign that one side is trading with itself. We measure "barely moves" against each token's own normal swing, so we don't flag a steady large-cap token for trading calmly.
- Sudden spikes: we compare today's volume against the token's average over the past month. A burst several times the usual level, with no matching price move, looks staged. A price move that lines up with the volume softens the read, since real news creates real spikes too.
- Standing apart from peers: we line a token up against others in the same category, then flag volume that runs far hotter than its peers with nothing else to explain it. We need at least three peers before we run the comparison.
We blend the four checks into one score, weighting whichever have enough data behind them and setting aside the rest. Tokens younger than 30 days get a gentler score, since new tokens trade unevenly on their own, without any wash trading involved. Alongside the score, we show a confidence note of low, medium, or high, telling you how much data we had to work with. We recompute every token once a day.
Risk tiers
The score maps to one of five labels, each summing up how much suspicious trading we found:
- Minimal indicators
- 0–20. Little or no sign of wash trading.
- Some indicators
- 21–45. A few patterns worth noting.
- Many indicators
- 46–70. Several patterns line up. Treat the volume with caution.
- Severe indicators
- 71–100. Strong signs that much of the volume is fake.
- No recent trades
- The token has barely traded for two weeks, so there's nothing meaningful to measure.
How this shapes our coverage
The score and label follow a token everywhere we show it.
- On the token's own page: a Wash Trading Detector panel shows the score, the confidence note, each of the four checks as its own meter, and a 30-day trend, so you can tell a one-off spike from a token that stays flagged week after week.
- On the tokens list and a game's related-tokens table: the label appears as a compact badge next to the token's price and Token Health score.
- In the analysis text on a token's page: the paragraph names the specific driver once a score runs high enough to point at one, such as volume that dwarfs the market cap.
Caveats
We treat this score as evidence, not a verdict. A flagged reading calls for a closer look, not a sell order, and a clean reading isn't a promise that a token is safe.
- Minimal doesn't mean safe: it means our checks found nothing to flag. Other risks sit outside what this tool looks at.
- Small tokens sit outside the volume-vs-size check: we skip tokens under $100k in market cap there. At that size, the ratio swings widely on its own, wash trading or not.
- The score is our own estimate: it comes from public price and volume data, and we can be wrong.
