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

Mode Network is an L2 smart contract platform for decentralized applications on Ethereum. Mode Network was founded by James Ross and launched in 2024.

Mode Network team & investors own and govern the protocol. Mode Network has received a $6 million grant from the Optimism Foundation.

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Blockchains (L2)

Mode Network

# Mode Network Block time Methodology

## 1. Overview

Block time measures the average time interval between consecutive blocks on the Mode blockchain, expressed in milliseconds. This metric indicates how frequently new blocks are produced on the network and reflects network performance and block production consistency. The calculation takes raw Mode blockchain block data, calculates time differences between consecutive blocks, and averages these intervals by day to provide a daily block time metric.

## 2. Data sources

The calculation uses the following raw data sources:
- **Mode blockchain block headers**: Raw block metadata from the Mode network including block timestamps and sequential block numbers
- **Block production data**: Fundamental blockchain data capturing when each block was mined/produced on the Mode network

## 3. Step-by-step calculation

### Component A: Block timestamp extraction
- **Purpose**: Extract clean block timestamp and number data from Mode blockchain
- **Logic**: The calculation starts by selecting block timestamps and block numbers from Mode blockchain block headers. The data is cast to proper types with `block_timestamp` as timestamp and `block_number` as integer. The genesis block (block number 0) is explicitly excluded since it has a timestamp at the start of Unix time which would skew block time calculations. For incremental processing, only recent blocks within the lookback period are processed.
- **Key fields**: `block_timestamp` contains when each block was produced, `block_number` provides sequential ordering of blocks

### Component B: Consecutive block pairing
- **Purpose**: Create pairs of consecutive blocks to calculate time intervals between them
- **Logic**: Using a window function with LAG, each block is paired with the timestamp of the immediately previous block when ordered by block number. This creates consecutive block pairs where each row contains the current block timestamp and the previous block timestamp. Rows where the previous timestamp is null (the first block after genesis) are filtered out since no time interval can be calculated.
- **Key fields**: `block_timestamp` for current block, `previous_timestamp` for the preceding block, `block_number` for ordering

### Component C: Block interval calculation
- **Purpose**: Calculate the actual time difference between consecutive blocks
- **Logic**: For each consecutive block pair, the time difference is calculated in milliseconds using timestamp difference functions. Each block timestamp is truncated to the day level to enable daily aggregation. The millisecond precision provides granular measurement of block production intervals while daily truncation allows for meaningful averaging periods.
- **Key fields**: `timestamp` (day-level), `block_time` in milliseconds representing interval between consecutive blocks

### Final aggregation
- **Combining components**: Block intervals are grouped by day and averaged to produce a daily average block time
- **Currency conversion**: Not applicable for this time-based metric
- **Time aggregation**: Daily boundaries are created by truncating block timestamps to day level, then averaging all block time intervals within each day
- **Final calculation**: The average block time per day is calculated across all consecutive block intervals within that day. The result includes standard metadata fields identifying Mode as the blockchain (chain_id='mode'), categorizing it as a layer 2 blockchain (market_sector_id='blockchains_l2'), and classifying it under blockchain business segment (business_segment_id='blockchain'). The finalize_metric_block_time macro applies standardization and the fill_zeros strategy, while chain availability filters ensure data quality.

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

avg(block_timestamp - previous_block_timestamp)

Mode NetworkMODE

Block time

Block time

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