Blast batches users' transactions and submits them to Ethereum, paying a share of the transaction fees to Ethereum validators (expense). Bridge depositors deposit ETH or stablecoins to Blast and receive a yield from ETH staking or T-bill strategies.

Blast is an L2 smart contract platform for decentralized applications on Ethereum. Blast has an inherent yield generation mechanism, coming from ETH staking and RWA protocols. Blast was founded by Pacman and launched in 2023.

Blast team and investors currently own and govern the protocol. Blast's investors include Paradigm, Standard Crypto, Santiago, etc.

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Blast

# Blast Average fees per user (AFPU) Methodology

## 1. Overview

Average fees per user (AFPU) measures the average amount of transaction fees paid per daily active user on the Blast network. This metric provides insight into user engagement costs and network fee efficiency by dividing total daily fees by the number of unique daily active users. The calculation combines both Layer 2 execution fees and Layer 1 data availability fees that users pay when transacting on Blast, converted to USD for standardized reporting.

## 2. Data sources

- **Blast transaction records**: Complete transaction data including sender/receiver addresses, gas usage metrics, gas prices, and Layer 1 fee components
- **End-of-day token price feeds**: ETH price data used to convert gas fees from native ETH denomination to USD
- **Token metadata**: Information about token decimals and addressing to ensure proper fee calculations

## 3. Step-by-step calculation

### Component A: Daily active users extraction
- **Purpose**: Identifies unique users transacting on Blast each day
- **Logic**: Extracts distinct sender addresses (`from_address`) from all Blast transactions, grouped by day. Uses HyperLogLog data structure for efficient distinct counting across large datasets. Users are classified as "Transaction sender" type within the "blockchains_l2" market sector and "blockchain" business segment.
- **Key fields**: `from_address` as user identifier, `block_timestamp` truncated to day boundaries, user classification metadata

### Component B: Daily fees calculation  
- **Purpose**: Calculates total fees paid by all users each day, combining Layer 2 and Layer 1 costs
- **Logic**: Sums two fee components for each transaction: L2 execution fees calculated as `gas_used` multiplied by `effective_gas_price`, and L1 data availability fees calculated as `l1_gas_used` multiplied by `l1_gas_price` multiplied by `l1_fee_scalar`, divided by 1e18 to convert from wei to ETH. All transactions are grouped by day and aggregated.
- **Key fields**: `gas_used`, `effective_gas_price`, `l1_gas_used`, `l1_gas_price`, `l1_fee_scalar`, with results denominated in ETH

### Component C: USD conversion
- **Purpose**: Converts ETH-denominated fees to USD for standardized reporting
- **Logic**: Uses end-of-day ETH price feeds to convert fee amounts from native ETH to USD. The conversion process treats fees as originating from the Ethereum network for price lookup purposes, then recasts the chain identifier back to 'blast' for final output.
- **Key fields**: `fees` converted from ETH to USD using daily price feeds, maintaining daily timestamp boundaries

### Component D: User DAU aggregation
- **Purpose**: Aggregates daily active user counts across different dimensional breakdowns
- **Logic**: Uses HyperLogLog functions to efficiently count distinct users across multiple dimensions including project level, chain level, user type, and product breakdowns. Applies gap-filling strategies to ensure complete time series data with zeros for days with no activity.
- **Key fields**: `user_dau` count extracted from HLL structures, dimensional breakdown fields, timestamp boundaries

### Final aggregation
- **Combining components**: The AFPU calculation divides total daily fees (Component C output) by daily active user count (Component D output) using a macro-based approach that handles the division safely
- **Currency conversion**: All fee amounts are in USD based on end-of-day ETH prices, ensuring consistent currency reporting
- **Time aggregation**: Daily boundaries are maintained throughout, with timestamp truncation to day level ensuring proper alignment between fee totals and user counts  
- **Final calculation**: AFPU equals total daily fees in USD divided by daily active user count, with data quality checks and gap-filling applied to create a complete time series

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

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