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

Polkadot is a security & interoperability platform for blockchains and applications. Polkadot was founded by Gavin Wood and launched in 2020.

DOT holders own and govern the protocol. They currently take a cut of the total transaction fees paid by users (revenue). Polkadot’s investors include Polychain, IOSG Ventures, Hashkey, etc.

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Polkadot

# Polkadot Block time Methodology

## 1. Overview

The Polkadot block time metric measures the average time interval between consecutive blocks produced on the Polkadot relay chain, aggregated daily. This metric provides insight into the network's block production performance and consensus mechanism efficiency. Block time is calculated by measuring the time difference between consecutive block timestamps and averaging these intervals within each day.

## 2. Data sources

- **Polkadot relay chain block data**: Raw blockchain block headers containing block numbers and timestamps from the Polkadot relay chain
- **Block metadata**: Core blockchain data including block production timestamps and sequential block numbers

## 3. Step-by-step calculation

### Component A: Block data extraction
- **Purpose**: Retrieves block timestamps and numbers from the Polkadot relay chain
- **Logic**: Extracts `block_timestamp` and `block_number` fields from raw Polkadot block data. Excludes the genesis block (block number 0) as it contains an artificial timestamp set to the Unix epoch start, which would skew block time calculations
- **Key fields**: `block_timestamp` contains the block production time, `block_number` provides sequential ordering

### Component B: Timestamp preparation
- **Purpose**: Pairs each block with its predecessor's timestamp to enable interval calculation
- **Logic**: Uses a window function to lag timestamps, creating pairs of consecutive blocks ordered by block number. Each block is matched with the timestamp of the immediately preceding block
- **Key fields**: `block_timestamp` for current block, `previous_timestamp` for the preceding block, `block_number` for ordering

### Component C: Block time calculation
- **Purpose**: Calculates the time interval between consecutive blocks
- **Logic**: Computes the millisecond difference between each block's timestamp and its predecessor's timestamp. Truncates timestamps to daily boundaries for aggregation purposes. Filters out null previous timestamps (which occur for the first block in the dataset)
- **Key fields**: `block_time` measured in milliseconds, `timestamp` truncated to day level

### Component D: Daily aggregation
- **Purpose**: Calculates average block time for each day
- **Logic**: Groups block intervals by day and calculates the average block time across all blocks produced within each daily period. Adds standard metadata fields including chain identifier, market sector, and product identifiers
- **Key fields**: `block_time` as daily average in milliseconds, standard metadata fields for classification

### Final aggregation
- **Combining components**: Sequential processing through CTEs where block data flows from extraction through timestamp pairing, interval calculation, and daily averaging
- **Currency conversion**: Not applicable for time-based metrics
- **Time aggregation**: Daily boundaries using timestamp truncation, with averaging of all block intervals within each day
- **Final calculation**: The final metric represents the average millisecond interval between consecutive blocks for each day, standardized through the finalize metric macro and filtered for chain availability

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

avg(block_timestamp - previous_block_timestamp)

PolkadotDOT

Block time

Block time

Competitive landscape

Chain breakdown