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Blockchains (L2)

Zeitgeist

# Zeitgeist Block time Methodology

## 1. Overview

The Zeitgeist block time metric measures the average time interval between consecutive blocks on the Zeitgeist blockchain, aggregated daily. This metric provides insights into blockchain network performance and consensus efficiency. The calculation determines how long, on average, it takes for the Zeitgeist network to produce each new block by measuring the time differences between consecutive blocks and averaging these intervals within each day.

## 2. Data sources

- **Zeitgeist blockchain data**: Raw block headers and metadata from the Zeitgeist blockchain network, including block timestamps and block numbers for each block produced on the network

## 3. Step-by-step calculation

### Component A: Block data extraction
- **Purpose**: Retrieves and cleans basic block information from the Zeitgeist blockchain
- **Logic**: Extracts block timestamps and block numbers from raw Zeitgeist blockchain data. Casts the raw `timestamp` field to a proper timestamp data type and the `number` field to an integer for the `block_number`. Excludes the genesis block (where `block_number` is 0) since it has an artificial timestamp at the start of Unix time that would skew calculations
- **Key fields**: `block_timestamp` (when each block was created) and `block_number` (sequential block identifier)

### Component B: Block interval calculation  
- **Purpose**: Calculates the time difference between consecutive blocks
- **Logic**: Uses a lag window function to pair each block with the timestamp of the previous block, ordered by `block_number` in ascending order. Calculates the time difference in milliseconds between each block and its predecessor using `timestamp_diff`. Filters out the first block since it has no previous block to compare against
- **Key fields**: `block_timestamp`, `block_number`, `previous_timestamp` (timestamp of the preceding block), and `block_time` (milliseconds between consecutive blocks)

### Component C: Daily aggregation
- **Purpose**: Groups block intervals by day and calculates daily averages
- **Logic**: Truncates block timestamps to daily boundaries using `timestamp_trunc` with day granularity. Groups all block intervals within each day and calculates the average `block_time` across all blocks produced on that day. Adds standard metadata fields including `chain_id` set to 'zeitgeist', `market_sector_id` set to 'blockchains_l2', `business_segment_id` set to 'blockchain', and `product_id` set to null
- **Key fields**: `timestamp` (daily boundary), `timestamp_grain` (set to 'day'), chain and business metadata fields, and `block_time` (average milliseconds per block for that day)

### Final aggregation
- **Combining components**: The daily averaged block times flow through a standardization macro (`finalize_metric_block_time`) which applies consistent formatting, data validation, and fills any missing days with zeros using the 'fill_zeros' strategy
- **Time aggregation**: Block intervals are aggregated within daily boundaries, with each day containing the average block time across all blocks produced during that 24-hour period
- **Final calculation**: The final metric represents the average number of milliseconds between consecutive blocks for each day on the Zeitgeist blockchain, providing a daily measure of network block production speed

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

avg(block_timestamp - previous_block_timestamp)

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