How to Build a Crypto Whale Tracker with On-Chain and Off-Chain Data

Whale watching in crypto is a legitimate trading edge. When wallets holding millions in tokens start moving, the market often follows. By combining on-chain transaction data with off-chain signals like exchange announcements and social media, you can build an early warning system. Here's how to build a complete whale tracker in Python. What Makes a Whale? In crypto, a "whale" is typically: Top 100 holders of any given token Wallets with >$1M in a single asset Wallets associated with known funds, exchanges, or early investors Setting Up pip install web3 requests pandas websockets On-Chain: Monitoring Large Transactions from web3 import Web3 from datetime import datetime import time class WhaleMonitor : def __init__ ( self , rpc_url : str , min_value_eth : float = 100.0 ): self . w3 = Web3 ( Web3 . HTTPProvider ( rpc_url )) self . min_value_wei = Web3 . to_wei ( min_value_eth , " ether " ) self . known_wallets = { " 0x28C6c06298d514Db089934071355E5743bf21d60 " : " Binance Hot Wallet " ,