Staking Analysis - Data Collection

Objective

• Retrieve depositor, validator, and staking data.
• Examine the distribution, effectiveness, and diversity of depositors.
• Create a data pipeline to load data into a data store for analysis.

Challenges

• Depositor labelling was the hardest part, as there is no single source of truth.

Steps taken

1. Extracted validator, depositor information from Dune Analytics.

   • Code: dune-to-db.py

2. Obtained labels for some of the depositors from etherscan.

3. Written rules for other depositors (such as Coinbase and RocketPool) who do not deposit from a static address. Coinbase, for example, uses a strategy in which they deposit from their known wallets to a new wallet, send 32 ETH to an eth deposit contract, and then send the excess back to their known wallet. Coinbase has over 60k deposit addresses.

4. Used blockprint data to map depositor to client in order to understand depositor client diversity.

   • Code: sigp-to-db.py

5. Analyzed depositor's consensus reward performance by using beaconchain API.

   • Code: beaconchain-to-db.py