Creators & users sell NFTs on OpenSea. They receive royalties from secondary sales (supply-side fees).

OpenSea is a non-custodial NFT marketplace protocol built on Ethereum. OpenSea was founded by Alex Atallah & Devin Finzer and launched in 2017.

OpenSea team & investors own and govern the protocol. They currently take a cut of the total transaction fees paid by buyers (revenue). OpenSea's investors include a16z, Coatue, Founders Fund, etc.

github

twitter

discord

website

NFT marketplaces

OpenSea

# OpenSea Trading volume Methodology

## 1. Overview

OpenSea trading volume measures the total USD value of NFT transactions facilitated through the OpenSea marketplace platform on a daily basis. This metric captures trading activity across both the current Seaport protocol (versions 1.1-1.6) and the legacy Wyvern protocol, identifying OpenSea-specific transactions through multiple detection methods including fee recipients, protocol ownership, and transaction tags. The calculation aggregates volume amounts from individual trades, converts them to USD using end-of-day price feeds, and presents daily totals segmented by blockchain network.

## 2. Data sources

The calculation utilizes several types of blockchain data and external feeds:

- **Seaport protocol events**: Parsed `OrderFulfilled` events from Seaport versions 1.1 through 1.6 on Ethereum, containing trade details including offer and consideration arrays, token addresses, amounts, and participant addresses
- **Seaport function calls**: Parsed `matchAdvancedOrders` and `matchOrders` function calls that provide additional context for order matching scenarios
- **WyvernExchange events**: Parsed `OrdersMatched` events from the legacy Wyvern protocol on Ethereum containing trade prices and participant information
- **WyvernExchange function calls**: Parsed `atomicMatch` function calls that provide detailed trade parameters including fee structures and token addresses
- **Ethereum transaction traces**: Raw transaction trace data used to identify OpenSea-originated transactions through specific input data patterns
- **End-of-day token price feeds**: Daily closing price data for various tokens to enable USD conversion of trading volumes
- **Token metadata**: Token contract information including decimal precision for proper amount calculations

## 3. Step-by-step calculation

### Component A: Seaport trade processing
- **Purpose**: Extract and process trading data from the current Seaport protocol across all versions
- **Logic**: Parse `OrderFulfilled` events from Seaport versions 1.1-1.6, unnesting the `offer` and `consideration` arrays to analyze each component of complex multi-token transactions. Classify tokens by type where 0 and 1 represent ETH and ERC20 tokens respectively, while 2 and 3 represent ERC-721 and ERC-1155 NFT tokens. Determine trading volume by identifying which array elements represent actual payment versus fees or royalties based on token types and recipient addresses. For matched orders (bulk transactions), apply different logic than individual orders to correctly attribute volume amounts. Handle edge cases like NFT-to-NFT swaps by comparing offer and consideration amounts.
- **Key fields**: Extract `block_timestamp` for timing, `transaction_hash` for grouping, `offer.amount` and `consideration.amount` for volume calculation, `offer.token` and `consideration.token` for token identification, and `recipient` addresses for fee classification

### Component B: Wyvern trade processing  
- **Purpose**: Process trading data from the legacy Wyvern protocol used before Seaport migration
- **Logic**: Join `OrdersMatched` events with corresponding `atomicMatch` function calls using transaction hash, price, maker, and taker address matching. Extract the trade price from the event as the volume amount, assuming each trade represents one NFT transaction. Identify buyer and seller roles based on the presence of buy hash versus sell hash in the order data. Calculate fee amounts using fee tier parameters from function calls and estimate protocol fees at 2.5% to separate OpenSea fees from creator royalties. Only include successfully executed transactions where status is true.
- **Key fields**: Use `price` from events as `volume_amount`, extract fee recipient addresses from `addrs` array positions, and determine `nft_seller_address` and `nft_buyer_address` based on maker/taker roles

### Component C: OpenSea transaction identification
- **Purpose**: Apply multiple methods to comprehensively identify transactions that should be attributed to OpenSea
- **Logic**: Implement four distinct identification approaches: (1) Protocol fee method - identify Seaport transactions where fees are sent to known OpenSea fee addresses including OpenSea Wallet and fee collection contracts, (2) Protocol ownership method - identify Seaport transactions where the zone field matches OpenSea's valid zone addresses indicating protocol control, (3) Website tag method - identify transactions containing the hexadecimal tag '360c6ebe' in transaction input data indicating OpenSea website origination (applied only after February 18, 2023), (4) Legacy fee method - identify Wyvern transactions where fee recipients match OpenSea's known fee addresses. Combine results using union operations to capture transactions identified by any method.
- **Key fields**: Check `recipient` and `consideration.recipient` addresses against OpenSea fee addresses, validate `zone` field against valid zones, and scan transaction `input` data for OpenSea tags

### Component D: Volume consolidation and deduplication
- **Purpose**: Combine trading volume from all protocols and identification methods while removing duplicates
- **Logic**: Union all trading volume records from Seaport and Wyvern processing that match any of the OpenSea identification criteria. Apply distinct operations to remove duplicate transactions that might be identified by multiple methods. Maintain consistent field structure across protocols by standardizing field names and business categorization. Filter out any records with null or zero volume amounts that don't represent actual trading activity.
- **Key fields**: Preserve `volume_amount`, `token_address`, `block_timestamp`, `transaction_hash`, and business classification fields consistently across all sources

### Component E: Daily aggregation
- **Purpose**: Aggregate individual transaction volumes into daily totals by relevant dimensions
- **Logic**: Group all identified trading volume records by truncated daily timestamp using `timestamp_trunc(block_timestamp, day)` to establish consistent daily boundaries. Sum volume amounts within each group defined by day, chain identifier, market sector, business segment, product identifier, and token address. This creates daily volume totals segmented by business dimensions while maintaining token-level granularity for accurate price conversion.
- **Key fields**: Group by `timestamp`, `chain_id`, `market_sector_id`, `business_segment_id`, `product_id`, and `token_address` while summing `volume_amount`

### Final aggregation
- **Combining components**: Sum all daily volume amounts across tokens and business segments to create total daily trading volume for OpenSea
- **Currency conversion**: Apply end-of-day token price feeds to convert native token amounts to USD values, using proper decimal correction based on token metadata to ensure accurate conversions regardless of token precision
- **Time aggregation**: Daily boundaries are established using timestamp truncation to day level, ensuring consistent daily reporting periods
- **Final calculation**: The final trading volume represents the sum of all USD-converted volume amounts for transactions identified as OpenSea marketplace activity on each day, with zero-filling applied for days with no activity to maintain consistent time series data

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Total value of spot trades executed on the exchange.

OpenSea

Trading volume

Trading volume

Competitive landscape

Chain breakdown