Validators process transactions and receive fees from users (supply-side fees).

Astar is a collective driving web3 adoption by connecting people through blockchain technology, business innovation, decentralized applications, and seamless digital experiences in the Polkadot ecosystem. Astar was founded by Sota Watanabe and launched in 2021.

ASTR tokenholders own and govern the protocol. Part of the transaction fees is burned (revenue). Astar’s investors include Binance, Polychain Capital, Crypto.com, etc.

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Blockchains (L2)

Astar

# Astar Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average transaction fees paid per daily active user on the Astar network. This metric provides insight into user monetization and network fee efficiency by dividing total daily fees collected by the number of unique daily active users. Astar operates as a dual-layer blockchain supporting both native substrate transactions and Ethereum Virtual Machine (EVM) compatible transactions, requiring fee collection from both layers.

## 2. Data sources

The calculation uses the following raw data sources:
- **Astar blockchain events**: Parsed event logs from Astar's substrate runtime, including `TransactionFeePaid` events from the `transactionPayment` pallet and balance `Withdraw`/`Deposit` events from EVM operations
- **Astar substrate extrinsics**: Native Astar transaction records containing sender addresses and execution metadata
- **Ethereum pallet events**: `Executed` events from Astar's ethereum pallet that indicate EVM transaction completion
- **End-of-day price feeds**: Daily Astar (ASTR) token prices from CoinGecko for USD conversion
- **Token metadata**: Astar token configuration including decimal precision (18 decimals) for proper unit conversion

## 3. Step-by-step calculation

### Component A: L1 substrate fee collection
- **Purpose**: Captures transaction fees from native Astar substrate transactions
- **Logic**: Extracts `TransactionFeePaid` events from the `transactionPayment` pallet, which contain both base transaction fees and optional tips. The `transaction_fee` and `transaction_tip` values are extracted from event data positions 1 and 2 respectively, then summed together. Events are filtered to daily boundaries and associated with their originating extrinsic identifier
- **Key fields**: `transaction_fee` (base fee amount), `transaction_tip` (optional tip amount), `extrinsic_id` (transaction identifier), `timestamp` (daily boundary)

### Component B: L2 EVM fee collection  
- **Purpose**: Captures transaction fees from Ethereum-compatible transactions on Astar's EVM layer
- **Logic**: Identifies EVM transactions through `Executed` events in the ethereum pallet, then tracks associated balance changes via `Withdraw` and `Deposit` events in the balances pallet. Withdraw events (positive fees) are summed with Deposit events (negative adjustments) to calculate net fees per transaction. Only balance changes where the signer matches the original transaction executor are included to ensure fee attribution accuracy
- **Key fields**: `transaction_fee` (net balance change), `signer_address` (fee payer), `extrinsic_id` (transaction identifier), `event_method` (Withdraw/Deposit type)

### Component C: User identification
- **Purpose**: Identifies unique daily active users across both substrate and EVM layers
- **Logic**: Extracts user addresses from two sources: substrate extrinsic senders (native transactions) and ethereum pallet `Executed` event data (EVM transactions). For substrate transactions, the `id` field from extrinsics provides the sender address. For EVM transactions, the first element of `event_data` contains the executing user address. All addresses are collected with daily timestamps and deduplicated using HyperLogLog aggregation
- **Key fields**: `user_address` (transaction sender), `block_timestamp` (transaction time), `user_type` (always "Transaction sender"), `chain` (astar or astarevm)

### Component D: Fee aggregation and conversion
- **Purpose**: Combines L1 and L2 fees and converts to USD
- **Logic**: Unions L1 and L2 fee data streams, converts amounts from 18-decimal native units to standard units by dividing by 10^18, then applies end-of-day Astar token prices from CoinGecko to convert to USD values. Daily fees are summed across all transactions within each day boundary
- **Key fields**: `fees` (converted fee amounts), `chain_id` (astar/astarevm), `product_id` (Astar Substrate), `daily_timestamp` (day boundary)

### Component E: User aggregation
- **Purpose**: Counts unique daily active users using efficient approximation
- **Logic**: Applies HyperLogLog (HLL) aggregation to user addresses within daily boundaries to efficiently count distinct users. The HLL algorithm provides approximate distinct counts with controlled memory usage. Users are aggregated across multiple dimensional breakdowns including project-level, chain-level, user-type-level, and product-level views
- **Key fields**: `user_dau` (distinct user count), `dimensions` (breakdown type), `timestamp` (daily boundary)

### Final aggregation
- **Combining components**: The `calculate_arpu` macro divides the daily fees (revenue) by the daily active user count to produce the average fees per user. Both metrics are aligned by timestamp and data identifier (astar) before division
- **Currency conversion**: Fees are converted to USD using end-of-day CoinGecko price feeds for the Astar token, ensuring consistent valuation timing across all fee calculations
- **Time aggregation**: All data is aggregated to daily boundaries using timestamp truncation. Missing days are filled with zero values to maintain continuous time series
- **Final calculation**: AFPU = Total Daily Fees (USD) ÷ Daily Active Users, where both numerator and denominator represent the same 24-hour period. The result is processed through the `finalize_metric_afpu` macro which applies standardized formatting, metadata addition, and zero-filling strategies

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

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Average fees per user (AFPU)

Average fees per user (AFPU)

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