Nft Analytics Guide

NFT Analytics Guide

A practical guide to analyzing NFT markets and collections using free tools and on-chain data.

Key NFT Metrics

Collection-Level Metrics

| Metric | What It Means | Good Sign | |--------|--------------|-----------| | Floor Price | Cheapest available NFT in collection | Stable or rising over weeks | | Total Volume | All-time trading volume | >1,000 ETH for established collections | | Unique Holders | Number of distinct wallets | >30% of supply held by unique wallets | | Holder/Supply Ratio | Holders ÷ Supply | >0.5 (more holders than concentrated) | | Listed % | What % of supply is for sale | 5–15% is healthy | | Sales Velocity | Number of sales per day | Consistent daily sales > sporadic | | Wash Trading % | Fake volume between same wallets | 50% of volume from Sperax context: ERC-8004 is the standard Sperax created for on-chain AI agent identity. Each agent is minted as an NFT with metadata about its capabilities, reputation score, and validation status. It's deployed on 12 chains.

NFT Valuation Framework

For PFP/Art Collections

| Factor | Weight | What to Check | |--------|--------|---------------| | Community | 30% | Discord activity, holder engagement, celebrity holders | | Floor stability | 25% | Look at 30/90 day floor chart, not just current | | Volume quality | 20% | Real volume after removing wash trades | | Utility | 15% | Token-gated access, airdrops, real-world perks | | Team | 10% | Track record, transparency, roadmap execution |

For Utility NFTs

| Factor | Weight | What to Check | |--------|--------|---------------| | Functional value | 40% | What does holding this NFT actually get you? | | Protocol adoption | 25% | Is the underlying protocol growing? | | Supply dynamics | 20% | Mint rate, burn mechanics, total cap | | Revenue generation | 15% | Does the NFT generate yield or fee share? |

Dune Analytics Queries for NFTs

Collection Volume (Last 30 Days)

SELECT
    date_trunc('day', block_time) as day,
    COUNT(*) as sales,
    SUM(amount_usd) as volume_usd
FROM nft.trades
WHERE nft_contract_address = 0x... -- collection address
  AND block_time > now() - interval '30 days'
GROUP BY 1
ORDER BY 1

Holder Distribution

SELECT
    COUNT(DISTINCT wallet) as unique_holders,
    SUM(CASE WHEN balance = 1 THEN 1 ELSE 0 END) as single_holders,
    SUM(CASE WHEN balance > 10 THEN 1 ELSE 0 END) as whales
FROM (
    SELECT to as wallet, COUNT(*) as balance
    FROM erc721_transfers
    WHERE contract_address = 0x...
    GROUP BY 1
)

Agent Tips

1. Always check for wash trading — reported volume can be 50–90% fake
2. Floor price is the most honest metric — it's the actual cost to enter
3. Low listed % is usually bullish — holders aren't trying to sell
4. Whale concentration — if top 10 wallets hold >30%, they control the floor
5. Use aggregators for best prices — don't buy on just one marketplace
6. ERC-8004 NFTs are different — they represent AI agents with reputation, not art
7. Bear market NFTs — focus on utility and revenue, not hype

Links

• OpenSea: https://opensea.io
• Blur: https://blur.io
• Reservoir: https://reservoir.tools
• NFTGo: https://nftgo.io
• Dune (NFT queries): https://dune.com
• ERC-8004 (agent NFTs): https://eips.ethereum.org/EIPS/eip-8004

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Sperax
• Source: Sperax/sperax-skills
• License: MIT

Install and usage instructions live in the source repository linked above.