The short answerCryptoSlam took the NFT sector's dirtiest metric and cleaned it, publishing both raw and wash-filtered volume so users can see the size of the problem. The filtering is heuristic and will miss sophisticated cases, and it remains the most honest volume data available at any price.
Best forVolume data with wash trading stripped out
Data accuracyweight 25%
9.0avg 7.8
Analytical usefulnessweight 20%
7.5avg 7.4
Value for moneyweight 20%
9.5avg 8.1
Coverageweight 20%
8.5avg 7.8
Method transparencyweight 15%
8.5avg 7.1
this service category average across 15Score = Σ mark × weight. Recommendable to most readers, with stated caveats. Methodology.
| Criterion | Mark | What we found | Source | Checked |
|---|
| Data accuracy | 9.0 | not sourced yet | not sourced yet | — |
| Analytical usefulness | 7.5 | not sourced yet | not sourced yet | — |
| Value for money | 9.5 | not sourced yet | not sourced yet | — |
| Coverage | 8.5 | not sourced yet | not sourced yet | — |
| Method transparency | 8.5 | not sourced yet | not sourced yet | — |
What we liked, and what fell short
Liked- Documented wash-trade filtering applied across collections
- Free access to the core rankings
- Broad multi-chain coverage over many years
Fell short- Interface and analytics are basic compared with paid rivals
- Filtering is heuristic and will miss sophisticated cases
Why the marks landed where they did
NFT volume is the most systematically manipulated number in crypto. Traders sell to themselves to farm token rewards, to inflate a collection's apparent activity, or to manufacture a price history. CryptoSlam was the first platform to filter that out and publish the difference.
How the filtering works
Transactions between related wallets, circular trades and self-funded loops are identified and excluded, with the methodology documented rather than hidden. Both raw and adjusted figures are shown, so users can see exactly how much of a collection's reported volume is genuine. On some collections during incentive periods, the gap has exceeded 90%.
Limitations
Heuristics catch obvious patterns and miss sophisticated actors who fund wallets through exchanges or mix their activity. Adjusted figures should be read as a floor on genuine volume rather than an exact measurement.
Coverage and cost
Multi-chain, spanning years of history, free to read with paid API tiers for developers. The interface is basic compared with paid analytics platforms, and the data is the product.
Who should use it
Anyone citing NFT volume figures. Checking a collection's adjusted volume against its reported volume takes seconds and is the single most useful diligence step in this category.
FAQ
How does CryptoSlam detect wash trading?+
It identifies transactions between related wallets, circular trades and self-funded loops using documented heuristics, publishing both raw and adjusted figures.
Is CryptoSlam free?+
Yes for the core rankings and collection data, with paid API tiers for programmatic access.
How much NFT volume is wash trading?+
It varies enormously by collection and period. During token-incentive programmes, the majority of reported volume on some venues has been wash traded.
Can the filtering be fooled?+
Yes. Sophisticated actors who fund wallets through exchanges can evade heuristic detection, so adjusted figures are a floor rather than an exact measure.
