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

TierETH Balance% of SupplySignificance
Whale> 10,000 ETH~40%Can move markets, track closely
Shark1,000 - 10,000 ETH~15%Significant players, early adopters
Dolphin100 - 1,000 ETH~20%Active participants
Fish10 - 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.