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

Fantom is a smart contract platform for decentralized applications (a blockchain). Fantom was founded by Dr. Ahn Byung Ik and launched in 2019.

FTM holders own and govern the protocol. They currently take a cut of the total transaction fees paid by users (revenue). Fantom’s investors include DHVC, Arrington XRP Capital, 8 decimal Capital, etc.

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# Fantom Average transaction fee Methodology

## 1. Overview

The average transaction fee metric measures the mean cost per transaction on the Fantom network in USD. It provides insight into transaction costs and network usage patterns by calculating the daily average fee paid by users. The metric divides total daily transaction fees by the total number of transactions executed on that day.

## 2. Data sources

- **Fantom transaction records**: Complete transaction data from the Fantom blockchain including gas usage, gas prices, transaction hashes, and block timestamps
- **End-of-day token price feeds**: Daily price data for WFTM (Wrapped Fantom) token used for USD conversion
- **Token metadata**: WFTM token contract information (`0x21be370d5312f44cb42ce377bc9b8a0cef1a4c83`) used as the price reference

## 3. Step-by-step calculation

### Component A: Transaction data extraction
- **Purpose**: Extracts and processes raw Fantom transaction data with gas information
- **Logic**: Retrieves all transactions from Fantom blockchain records, focusing on gas-related fields. The `effective_gas_price` is converted from wei units to FTM by dividing by 10^18. Each transaction includes the `gas_used` amount and the converted gas price. Transactions are filtered to include only valid records with gas information.
- **Key fields**: `transaction_hash` for unique identification, `gas_used` for gas consumption, `effective_gas_price` for price per gas unit, `block_timestamp` for timing, and WFTM token address as reference

### Component B: Daily fee calculation
- **Purpose**: Calculates total transaction fees paid on each day
- **Logic**: Groups transactions by day using timestamp truncation. For each transaction, multiplies `gas_used` by `effective_gas_price` to get the fee amount in FTM. All transaction fees within each day are summed to produce total daily fees. This creates a daily aggregate of all fees paid on the Fantom network.
- **Key fields**: Daily `timestamp` for grouping, calculated `fee_amount` as the product of gas used and gas price

### Component C: USD conversion
- **Purpose**: Converts daily FTM fees to USD values
- **Logic**: Takes the daily FTM fee amounts and applies end-of-day price conversion using WFTM token price data. The conversion uses established price feeds to translate native FTM values into USD equivalents. This ensures all fee calculations are standardized in USD for cross-chain and temporal comparisons.
- **Key fields**: `fees` in USD after price conversion, `token_address` referencing WFTM for price lookup

### Component D: Daily transaction counting
- **Purpose**: Counts the number of unique transactions per day
- **Logic**: Groups transactions by daily timestamp and counts distinct `transaction_hash` values. This provides the denominator for the average calculation by determining how many individual transactions occurred each day on Fantom. Duplicate transaction hashes are eliminated to ensure accurate counting.
- **Key fields**: `transaction_count` as count of distinct transactions, daily `timestamp` for grouping

### Final aggregation
- **Combining components**: The daily fee totals (in USD) are joined with daily transaction counts using the timestamp field as the key. Both datasets are aligned on the same daily boundaries to ensure accurate pairing of fees and counts.
- **Currency conversion**: All fees are converted to USD using end-of-day WFTM price feeds before the final calculation
- **Time aggregation**: Data is aggregated on daily boundaries using timestamp truncation to day granularity
- **Final calculation**: The average transaction fee is calculated using safe division of total daily fees by total daily transaction count. Safe division handles edge cases where transaction count might be zero, preventing division errors and returning null for such cases.

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

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