Lenders deposit funds into Spark and receive interest payments from borrowers (supply-side fees).

Spark is a non-custodial lending protocol built on Ethereum. Spark’s development team Phoenix Labs was founded in early 2023.

SPK tokenholders own and govern the protocol. They currently take a cut of the total interest paid by borrowers (revenue).

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Lending

Spark

SparkLend | Data breakdown

# Spark Token incentives Methodology

## 1. Overview

Token incentives measures the value of native assets that are paid out by Spark to its supply/demand-side users, core contributors, and/or investors. The assets are primarily used to compensate stakeholders either retroactively or on an ongoing basis to bootstrap liquidity and reward active participants within SparkLend. The metric is analogous to stock-based compensation in traditional finance.

## 2. Data sources

- **Blockchain events**: `RewardPaid` events from `StakingRewards` contracts, covering Ethereum
- **External data**: End-of-day price feeds and asset metadata

## 3. Step-by-step calculation

### Component A: Reward distribution extraction

- **Purpose**: Extract raw reward distribution events from staking contracts
- **Logic**: `RewardPaid` events are parsed from `StakingRewards` contracts on Ethereum. For each event, the reward amount and the associated reward asset address are extracted along with the transaction details and block timestamp.
- **Key fields**: `block_timestamp` (timing), `amount` (reward quantity), `token_address` (reward asset identification)

### Component B: Decimal normalization and USD conversion

- **Purpose**: Normalize reward amounts by asset decimals and convert to USD
- **Logic**: Raw reward amounts are normalized by matching the asset address with asset metadata to apply the correct decimal precision. The normalized amounts are then multiplied by the end-of-day price of the reward asset, sourced from end-of-day price feeds matching the transaction day and chain.
- **Key fields**: `token_address` (asset identification), `price_usd` (asset price)

### Component C: Daily aggregation and finalization

- **Purpose**: Aggregate values to daily granularity and apply final filters
- **Logic**: The USD-denominated reward values are aggregated by day, chain, and product. Missing days within the time series are filled with zeros to ensure continuity. Chain availability filters are applied to align the data with approved freshness boundaries.

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

Value of native tokens distributed as incentives.

SparkSPK

Token incentives

Token incentives

Competitive landscape

Chain breakdown