Liquidity providers deposit funds into PoolTogether and receive a return on investment in lottery winnings (supply-side fees).

PoolTogether is an asset management (no-loss lottery) protocol built on Ethereum and other adjacent blockchains. PoolTogether was founded by Leighton Cusack and launched in 2019.

POOL tokenholders own and govern the protocol. They currently do not take a cut of the total return on investment paid by liquidity providers (revenue). PoolTogether’s investors include IDEO CoLab Ventures, DTC Capital, ConsenSys Ventures, etc.

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PoolTogether

# PoolTogether Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average daily fees generated per active user in the PoolTogether protocol. This metric is calculated by dividing total daily fees by the number of daily active users, providing insight into the revenue efficiency and user engagement of the platform. The metric captures fees from prize claim payouts across PoolTogether v4 deployments on Ethereum, Polygon, Avalanche, and Optimism.

## 2. Data sources

- **PoolTogether event logs**: Parsed smart contract events from PoolTogether v4 deployments across Ethereum, Polygon, Avalanche, and Optimism networks
  - `ClaimedDraw` events containing prize claim payouts and user addresses
  - `RewardDistributor_ClaimedDraw` events (Polygon-specific) for prize distributions
  - `YieldSourcePrizePool_Deposited` events capturing deposit interactions
  - `YieldSourcePrizePool_Withdrawal` events capturing withdrawal interactions
- **Token price data**: End-of-day price feeds for USDC tokens across supported chains
- **Token metadata**: Decimal precision data for proper token amount calculations
- **Chain-specific data**: Transaction timestamps, block data, and log indices for event ordering

## 3. Step-by-step calculation

### Component A: Daily active users calculation

- **Purpose**: Count unique daily active users across all PoolTogether interactions
- **Logic**: Collect user addresses from three types of interactions across all supported chains. For prize claims, extract the `user` field from `ClaimedDraw` events, labeling these as "Withdrawer" user types. For deposits, extract the `operator` field from `YieldSourcePrizePool_Deposited` events, labeling as "Depositor" types. For withdrawals, extract the `operator` field from `YieldSourcePrizePool_Withdrawal` events, labeling as "Withdrawer" types. Truncate all event timestamps to day granularity and count distinct user addresses per day using HyperLogLog sketches for efficient aggregation across multiple interaction types and chains.
- **Key fields**: `user_address` from events, `block_timestamp` for daily grouping, `user_type` for interaction classification, `chain` for multi-chain aggregation

### Component B: Daily fees calculation

- **Purpose**: Calculate total daily fees from PoolTogether prize claim payouts
- **Logic**: Extract payout amounts from `ClaimedDraw` and `RewardDistributor_ClaimedDraw` events across all supported chains. Each chain uses a specific USDC token address for consistency. Convert the `payout` amounts to USD using end-of-day price feeds and apply proper decimal corrections based on token metadata. Aggregate these USD amounts daily by truncating event timestamps to day granularity and summing all converted payout amounts.
- **Key fields**: `payout` amount from events, `token_address` for chain-specific tokens, `block_timestamp` for daily aggregation, converted USD amounts

### Final aggregation

- **Combining components**: Join daily active user counts with daily fee totals by timestamp and chain, ensuring both metrics are calculated for the same time periods
- **Currency conversion**: All fees are converted to USD using end-of-day price feeds applied to chain-specific USDC token addresses, with proper decimal adjustments
- **Time aggregation**: Both metrics use day-level timestamp truncation to ensure consistent daily boundaries across all calculations
- **Final calculation**: Divide total daily fees (in USD) by the count of daily active users to produce the average fees per user for each day. Apply a fill_zeros strategy to handle missing data points in the time series, ensuring continuous daily coverage

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

PoolTogetherPOOL

Average fees per user (AFPU)

Average fees per user (AFPU)

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