Collators aggregate parachain transactions block candidates and producing state transition proofs for validators based on those blocks.

Frequency is a blockchain specialized for digital identity, data ownership and online presence powered by Polkadot Relay chain.

FRQCY holders own and govern the protocol.

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Blockchains (L2)

Frequency

# Frequency Block time Methodology

## 1. Overview

Block time measures the average time interval between consecutive blocks on the Frequency blockchain, aggregated daily. This metric indicates the network's block production speed and consistency, providing insights into blockchain performance and validator efficiency. The calculation determines the millisecond differences between consecutive block timestamps and averages them for each day.

## 2. Data sources

- **Frequency blockchain block headers**: Raw block data containing timestamps, block numbers, and author information from the Frequency blockchain network
- **Block timestamp data**: Precise timestamps indicating when each block was produced on the network
- **Block sequence data**: Sequential block numbers that establish the chronological order of blocks

## 3. Step-by-step calculation

### Component A: Block data extraction
- **Purpose**: Retrieves raw block information from the Frequency blockchain
- **Logic**: Extracts block timestamps, block numbers, and author identifiers from Frequency blockchain block headers. Filters out the genesis block (block number 0) since it has an artificial timestamp set to the Unix epoch start, which would skew block time calculations. Casts timestamp and block number fields to appropriate data types for subsequent processing.
- **Key fields**: `block_timestamp` (when the block was produced), `block_number` (sequential block identifier), `author_id` (block producer identifier)

### Component B: Consecutive block pairing  
- **Purpose**: Creates pairs of consecutive blocks to enable time interval calculation
- **Logic**: Uses a LAG window function ordered by `block_number` to retrieve the previous block's timestamp for each block. This creates consecutive block pairs where each row contains both the current block's timestamp and the immediately preceding block's timestamp. Excludes the first block since it has no predecessor.
- **Key fields**: `block_timestamp` (current block time), `previous_timestamp` (preceding block time), `block_number` (for ordering)

### Component C: Block time interval calculation
- **Purpose**: Calculates the time difference between consecutive blocks
- **Logic**: Computes the millisecond difference between each block's timestamp and its predecessor using `timestamp_diff`. Truncates block timestamps to daily boundaries to prepare for daily aggregation. Filters out rows where `previous_timestamp` is null (the first block with no predecessor).
- **Key fields**: `timestamp` (daily boundary), `block_time` (millisecond interval between blocks)

### Final aggregation
- **Combining components**: Groups block time intervals by daily timestamp boundaries and calculates the average block time for each day
- **Currency conversion**: Not applicable - block time is measured in milliseconds
- **Time aggregation**: Daily boundaries using timestamp truncation, with all blocks produced within the same calendar day grouped together
- **Final calculation**: Averages all block time intervals within each day to produce a daily average block time in milliseconds. Applies standardization metadata including `chain_id` as 'frequency', `market_sector_id` as 'blockchains_l2', and `business_segment_id` as 'blockchain'. Uses the `finalize_metric_block_time` macro for consistent formatting and applies chain availability filtering.

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

avg(block_timestamp - previous_block_timestamp)

FrequencyFRQCY

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Block time

Block time

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