On-Chain Analysis
Every transaction on a public blockchain is recorded forever. Learn how to extract insights from on-chain data to track wallets, analyze flows, and follow smart money.
What is On-Chain Analysis?
On-chain analysis examines blockchain data directly—transactions, smart contract interactions, token transfers, and wallet balances—to understand market behavior and identify opportunities.
Transparent
All data is public and verifiable
Immutable
Historical data cannot be changed
Real-Time
Track activity as it happens
Types of On-Chain Analysis
Wallet Analysis
Track any address's balance history, transaction patterns, and token holdings.
- Current and historical balance
- Transaction count and volume
- Token holdings and NFTs
- First/last activity dates
- Interaction patterns
Token Flow Analysis
Monitor how tokens move between exchanges, DeFi protocols, and wallets.
- Exchange inflows/outflows
- Whale wallet movements
- Smart money flows
- Bridge transfers
- DEX routing paths
Whale Tracking
Identify and follow large holders to spot market-moving activity.
- Wallet size rankings
- Accumulation/distribution
- Movement alerts
- Cluster analysis
- Historic patterns
Transaction Analysis
Deep dive into individual transactions and their effects.
- Internal transactions
- Token transfers
- Contract interactions
- Gas usage patterns
- MEV detection
Understanding Wallet Tiers
| Tier | ETH Balance | % of Supply | Significance |
|---|---|---|---|
| Whale | > 10,000 ETH | ~40% | Can move markets, track closely |
| Shark | 1,000 - 10,000 ETH | ~15% | Significant players, early adopters |
| Dolphin | 100 - 1,000 ETH | ~20% | Active participants |
| Fish | 10 - 100 ETH | ~15% | Retail investors |
| Shrimp | < 10 ETH | ~10% | Small holders, high count |
Note: These tiers are for ETH. For tokens, adjust thresholds based on total supply and market cap.
Common Analysis Queries
Top ETH Holders
Find wallets with the most ETH
SELECT
address,
eth_balance,
tx_count,
last_active
FROM ethereum.balances
WHERE eth_balance > 1000
ORDER BY eth_balance DESC
LIMIT 100;Exchange Inflows (24h)
Track tokens flowing into exchanges
SELECT
exchange_name,
SUM(value_usd) as total_inflow,
COUNT(*) as tx_count
FROM token_transfers
WHERE to_address IN (SELECT address FROM exchanges)
AND block_time > NOW() - INTERVAL '24 hours'
GROUP BY exchange_name
ORDER BY total_inflow DESC;Whale Accumulation
Find wallets accumulating tokens
SELECT
address,
SUM(CASE WHEN is_buy THEN amount ELSE -amount END) as net_change,
COUNT(*) as trades
FROM trades
WHERE token = '0x...'
AND block_time > NOW() - INTERVAL '7 days'
GROUP BY address
HAVING SUM(CASE WHEN is_buy THEN amount ELSE -amount END) > 10000
ORDER BY net_change DESC;Smart Money Wallets
Identify consistently profitable traders
SELECT
address,
total_pnl,
win_rate,
avg_hold_time,
trade_count
FROM wallet_pnl
WHERE trade_count > 50
AND win_rate > 0.6
ORDER BY total_pnl DESC
LIMIT 50;Key On-Chain Metrics
Exchange Net Flow
Inflows minus outflows. Positive = selling pressure, Negative = accumulation
Holder Distribution
Concentration of tokens among wallets. High concentration = centralization risk
Active Addresses
Number of unique addresses active in a period. Measures network usage
MVRV Ratio
Market Value to Realized Value. Above 1 = profit, below 1 = loss on average
Dormancy Flow
Old coins moving. High dormancy = long-term holders selling
NVT Ratio
Network Value to Transactions. High NVT = overvalued, low NVT = undervalued
Best Practices
Verify Wallet Labels
Don't blindly trust labels. Cross-reference with multiple sources and verify through transaction history. Labels can be outdated or incorrect.
Consider Context
Large transfers might be internal movements, not market activity. Check if source and destination are related (same entity, protocol, or exchange).
Look at Trends, Not Single Events
One large transaction doesn't tell the full story. Look at patterns over time, aggregate flows, and compare to historical behavior.
Combine with Off-Chain Data
On-chain data is most powerful when combined with price action, news, social sentiment, and other market indicators.