On-Chain Analytics

Public blockchains record every transaction in a ledger anyone can read. On chain analytics turns that raw data into insights about who holds coins, how they move, how much profit holders are sitting on and how heavily networks are used. It is a kind of alternative data unique to crypto: in stock markets, you cannot see every share transfer in real time, but in Bitcoin and Ethereum you can. Traders use on chain metrics to gauge market cycles, sentiment and supply and demand, alongside price charts and derivatives data.

Types of on chain data#

Key metrics#

Realised price and MVRV#

Market value counts every coin at today's price. Realised value counts each coin at the price when it last moved on chain, approximating the average cost basis of holders.

realised price = realised value / circulating supply
MVRV ratio = market value / realised value

SOPR (spent output profit ratio)#

SOPR compares the value of coins when spent with their value when acquired. Above 1 means coins moved on average are sold at a profit; below 1, at a loss. In bull markets, SOPR dipping to 1 and bouncing has often marked support; in bear markets, rallies to 1 have often met selling.

Long term and short term holders#

Analysts often classify coins unmoved for more than about 155 days as held by long term holders. When long term holders sell into rallies and short term holders accumulate, markets are often late in a bull cycle.

Network activity#

Rising active addresses and fees can signal growing usage; falling activity can signal declining interest. These are noisy and can be distorted by spam or batch transactions.

Data providers#

Companies such as Glassnode, CryptoQuant, Nansen, Dune and Arkham collect and label blockchain data. Labelling, identifying which addresses belong to exchanges, funds or known entities, is crucial and imperfect.

Using on chain data in trading#

• Cycle analysis: profitability metrics for long horizon positioning.
• Flow tracking: large exchange inflows can precede selling. See Wallet and Exchange Flows.
• Whale watching: tracking large holders' movements.
• Confirmation: combine with price action, funding and open interest. See Funding Rates.

Limitations#

• Attribution errors: addresses can be mislabelled; one entity can control many addresses.
• Off chain activity: trades inside exchanges, ETFs and custodians do not appear on chain individually.
• Changing structure: ETFs and layer 2 networks shift where activity happens, weakening old relationships.
• Small samples: Bitcoin has had only a few market cycles.
• Overfitting: many metrics can be tuned to past data. See Overfitting and Curve Fitting.

Frequently asked questions#

What is on chain analysis?#

The study of public blockchain data, such as transactions, addresses and holdings, to understand market behaviour and sentiment.

What is MVRV?#

The ratio of market value to realised value, showing whether holders on average are sitting on gains or losses.

Is on chain data reliable for trading?#

It provides unique information, but labelling errors, off chain activity and limited history mean it should be combined with other analysis.

Next, track how coins move between wallets and exchanges in Wallet and Exchange Flows.