Scroll batches users' transactions and submits them to Ethereum, paying a share of the transaction fees to Ethereum validators (expense).

Scroll is an L2 smart contract platform for decentralized applications on Ethereum. Scroll was founded by Sandy Peng, Haichen Shen, and Ye Zhang and launched in 2023.

SCR tokenholders own and govern the protocol. Scroll's investors include Polychain, Qiming Venture Partners, etc.

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Blockchains (L2)

Scroll

# Scroll Transactions per second Methodology

## 1. Overview

Transactions per second (TPS) measures the average number of transactions processed by the Scroll blockchain per second on a daily basis. This metric provides insight into network throughput and usage patterns by taking the total daily transaction count and dividing by the number of seconds in a day (86,400). The calculation aggregates all successful transactions recorded on the Scroll blockchain and presents the average processing rate as a daily metric.

## 2. Data sources

- **Scroll blockchain transaction records**: Raw transaction data from the Scroll L2 blockchain containing transaction details including timestamps, hashes, addresses, gas usage, and fees
- **Chain availability data**: Information about when the Scroll blockchain was operational and available for processing transactions
- **Table modification cache**: Metadata tracking when data tables were last updated to optimize incremental processing

## 3. Step-by-step calculation

### Component A: Transaction data extraction
- **Purpose**: Extract and standardize raw transaction records from the Scroll blockchain
- **Logic**: Select core transaction fields from Scroll blockchain transaction records and cast them to standardized data types. Add metadata including the chain identifier ('scroll'), native token information (ETH at address `0x5300000000000000000000000000000000000004`), and other dimensional attributes. This creates a clean, standardized view of all Scroll transactions.
- **Key fields**: `block_timestamp` (transaction time), `transaction_hash` (unique identifier), `from_address` and `to_address` (sender/receiver), `gas_used` (computational cost), `l1_fee` (L1 settlement cost), `gas_price` (price per gas unit)

### Component B: Daily transaction aggregation  
- **Purpose**: Count total daily transactions and prepare dimensional attributes
- **Logic**: Group transactions by day using timestamp truncation to daily boundaries. Count distinct transaction hashes within each day to get total daily transaction volume. Add dimensional metadata including chain identifier, market sector (blockchains_l2), and business segment (blockchain). Apply data quality macros that validate the data schema, ensure no gaps in the time series, and fill missing days with zero values where appropriate.
- **Key fields**: `timestamp` (daily boundary), `transaction_count` (distinct transactions per day), `chain_id` ('scroll'), dimensional identifiers for categorization

### Final aggregation
- **Combining components**: The daily transaction counts flow directly from the aggregation component to the final TPS calculation
- **TPS calculation**: Divide the daily transaction count by the number of seconds in a day (86,400) using safe division to handle edge cases where transaction counts might be null or zero
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation, with each day representing the average TPS for that 24-hour period  
- **Chain availability filtering**: Apply filters to exclude periods when the Scroll blockchain was not operational or available, ensuring TPS calculations only reflect active network periods
- **Final calculation**: The final transactions per second value equals the daily transaction count divided by 86,400 seconds, representing the average transaction processing rate for each day

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

Average confirmed user transactions added per second.

ScrollSCR

Transactions per second

Transactions per second

Competitive landscape

Chain breakdown