Liquidity providers deposit funds into Velodrome and stake their LP tokens to receive VELO tokens in proportion to their share of the votes (token incentives).

Velodrome is a non-custodial exchange protocol built on Optimism. Velodrome was founded by veDAO members and launched in 2022.

VELO tokenholders own and govern the protocol. They vote which pools they wish to earn trading fees from (revenue), while the pools' unstaked liquidity providers earn the remainder of the trading fees (supply-side fees).

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Exchanges (DEX)

Velodrome

# Velodrome Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) measures the number of unique users who conducted at least one trade on the Velodrome DEX within a rolling 7-day period. This metric provides insights into user engagement and platform adoption across Velodrome's different products (V1, V2, and Slipstream V3). The calculation uses HyperLogLog sketches to efficiently compute unique user counts across overlapping time windows and provides breakdowns by chain, user type, and product version.

## 2. Data sources

- **Velodrome V1 swap events**: Parsed `Pair_Swap` events from Velodrome V1 pair contracts on Optimism, containing trade execution details including token amounts and user addresses
- **Velodrome V2 swap events**: Parsed `Pool_Swap` events from Velodrome V2 pool contracts on Optimism, capturing automated market maker trading activity  
- **Velodrome V3 swap events**: Parsed `CLPool_Swap` events from Velodrome V3 concentrated liquidity pool contracts on Optimism, launched June 18, 2024
- **Optimism transaction records**: Transaction data providing user addresses (`from_address`) that initiated the trading transactions
- **Trading pair denylist**: Hardcoded list of trading pair contract addresses excluded due to limited price feed support for low-liquidity tokens

## 3. Step-by-step calculation

### Component A: Trade event extraction
- **Purpose**: Extract and standardize trading events across all Velodrome versions
- **Logic**: Query `Swap` events from Velodrome V1 `Pair` contracts, V2 `Pool` contracts, and V3 `CLPool` contracts on Optimism. Join swap events with Optimism transaction records to obtain the originating user address (`from_address`). For V1/V2, calculate token amount changes by subtracting out-amounts from in-amounts. For V3, use the direct amount fields from concentrated liquidity swaps. Filter events to include V1/V2 from June 2022 onwards and V3 from June 18, 2024 onwards.
- **Key fields**: `block_timestamp` for timing, `transaction_hash` for joining, `user_address` from transaction records, `account_address` for pool identification, product classification (`V1`, `V2`, `Slipstream`)

### Component B: Trading pair filtering  
- **Purpose**: Remove trades from problematic trading pairs with unreliable price data
- **Logic**: Apply a hardcoded denylist that excludes specific trading pair contract addresses known to have limited price feed support for low-liquidity tokens. This ensures data quality by removing trades that cannot be properly valued.
- **Key fields**: `account_address` for trading pair identification, `chain` for network specification

### Component C: Daily active user aggregation
- **Purpose**: Identify unique users who traded each day
- **Logic**: Group filtered trading events by day using timestamp truncation to daily boundaries. Extract distinct user addresses per day and classify all users as `Trader` type since the metric focuses on trading activity. Organize data by chain, product version, and business classification.
- **Key fields**: `timestamp` truncated to daily grain, `user_address` for unique identification, `chain`, `product_id`, `user_type`

### Component D: HyperLogLog initialization
- **Purpose**: Convert daily user lists into efficient sketches for unique counting
- **Logic**: Transform daily active user lists into HyperLogLog sketches with 15-bit precision. This probabilistic data structure enables efficient memory usage and fast merging operations when calculating unique users across multiple days.
- **Key fields**: HLL sketches containing user identifiers, maintaining dimensional attributes for later aggregation

### Component E: Rolling window creation
- **Purpose**: Generate 7-day rolling windows for WAU calculation
- **Logic**: Create a continuous datespine covering all days from the earliest trade date to yesterday. For each day in the datespine, generate a 7-day lookback window including the current day plus the previous 6 days. This ensures complete time series coverage without gaps from days with no trading activity.
- **Key fields**: `timestamp` for the target day, `joinday` for each day in the 7-day window

### Component F: Weekly aggregation with HLL merging
- **Purpose**: Calculate unique weekly active users using probabilistic sketches
- **Logic**: For each target day, join the 7-day window with daily HLL sketches to collect all sketches within the rolling window. Merge the HLL sketches across the 7-day period to compute the unique count of users who were active on any day within that week. This approach handles overlapping user activity efficiently.
- **Key fields**: Merged HLL sketches, extracted unique user counts, dimensional attributes

### Final aggregation
- **Combining components**: Generate four separate dimensional views of WAU data - project-level (overall Velodrome), chain-level (Optimism), user-type-level (Traders), and product-level (V1, V2, Slipstream). Union all dimensional breakdowns into a single comprehensive dataset.
- **Currency conversion**: Not applicable for user count metrics
- **Time aggregation**: Daily timestamps represent the end date of each 7-day rolling window, with each day showing unique users active in the preceding week
- **Final calculation**: Extract the final unique user count from merged HLL sketches using the extract function, apply metric finalization with zero-filling for missing periods, and organize by timestamp and dimensional attributes

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

Unique revenue-generating users over a rolling 7-day window.

VelodromeVELO

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown