On-chain analytics means reading a public blockchain's own records, such as transfers, wallet balances and the price at which each coin last moved, to judge whether holders are sitting on profits, taking them, or moving coins towards a sale. Traders mostly use it to place the market within a cycle, for example whether most holders are in deep profit or underwater. It is not a tool for timing a single entry. The handful of metrics below cover most of what it can do, and each one has limits.
What on-chain data can and cannot see
A blockchain like Bitcoin records every transaction permanently. From that record, analytics providers can work out:
- transfers between addresses, and the age of the coins being moved;
- deposits to and withdrawals from wallets that the provider has labelled as exchange wallets;
- the price at which each coin last moved, which is the basis of "realized" metrics;
- smart contract activity, including value locked in DeFi protocols.
It cannot see trades that settle inside an exchange's own books, over-the-counter deals, or derivatives positions. Exchange and custodian figures are only as good as the provider's address labelling. Since the US Securities and Exchange Commission approved the listing and trading of spot bitcoin exchange-traded products on 10 January 2024, part of demand has come through funds whose coins sit with custodians. Whether a given dataset counts those wallets as exchange balances depends on how its provider labels addresses, so check the methodology before comparing reserve charts from different sources.
The building block: market value vs realized value
Most cycle metrics compare two numbers:
- Market value (market cap): the current price multiplied by the coins in circulation.
- Realized value (realized cap): each coin valued at the price when it last moved, summed across the supply.
Realized value approximates the market's total cost basis. When market value is far above it, holders as a whole sit on large paper profits. When market value falls below it, the average coin is underwater.
Metric 1: NUPL (Net Unrealized Profit/Loss)
What it measures: the share of market cap that is unrealized profit or loss.
Formula: NUPL = (Market Cap − Realized Cap) / Market Cap
How it is read: Glassnode describes readings above zero as the supply sitting in net paper profit, with high extremes historically marking euphoric phases. Readings below zero are characteristic of late bear markets and capitulation lows.
Many chart sites split NUPL into named bands. The common convention is:
| NUPL | Label |
|---|---|
| above 0.75 | Euphoria / greed |
| 0.5 to 0.75 | Belief / denial |
| 0.25 to 0.5 | Optimism / anxiety |
| 0 to 0.25 | Hope / fear |
| below 0 | Capitulation |
These thresholds come from third-party guides and indicator scripts, not from Glassnode's documentation, and the exact boundaries differ between sites.
Metric 2: MVRV Z-Score
What it measures: how far market cap sits from realized cap, scaled by how volatile market cap has been.
Formula (Glassnode): MVRV Z-Score = (Market Cap − Realized Cap) / Standard Deviation of Market Cap
How it is read: Glassnode says readings well above realized value have historically coincided with market tops (the red zone) and readings at the opposite extreme with bottoms (the green zone). LookIntoBitcoin, which hosts a widely used version of the chart, credits it to @aweandwonder, building on earlier MVRV work by Murad Mahmudov and David Puell. It says the indicator has picked each cycle's high to within two weeks.
The difference from NUPL: both start from the same gap between market cap and realized cap. NUPL divides that gap by market cap, so it reads as a share of value. The Z-Score divides it by market cap's standard deviation, which is meant to make extremes comparable across cycles.
Metric 3: SOPR (Spent Output Profit Ratio)
What it measures: whether coins that actually moved were sold at a profit or a loss. Glassnode defines it as the realized USD value of a spent output divided by its value when the output was created, counted only for coins moved in the chosen timeframe.
How it is read (Glassnode):
- Above 1: coins moved at a profit on average, so profits are being realized.
- Exactly 1: coins moved at break-even.
- Below 1: coins moved at a loss.
In bull markets, Glassnode notes, resets often take SOPR near or below 1. In bear markets, local capitulations usually push it below 1, and SOPR can stay below 1 for a long time during final capitulation. Some traders treat the 1 level as support or resistance. That is a trading interpretation, not part of Glassnode's definition.
Metric 4: Long-term vs short-term holders
Glassnode splits holders by coin age. Coins with a lifespan of more than 155 days count as long-term holder (LTH) supply. Glassnode says such coins "are less likely to be spent" and are generally treated as part of the illiquid supply. Coins moved more recently count as short-term holder (STH) supply. Its Studio breakdowns weight supply with a logistic function centred on 155 days, so the cut-off is a gradual transition rather than a hard line.
The split matters because the two groups behave differently. Glassnode notes that over a 155-day window, price usually resolves in one direction, so when long-term holders spend, they tend to realize large profits or losses. Variants such as LTH-SOPR and STH-SOPR apply the profit-ratio idea to each cohort separately.
Which on-chain metric answers your question?
Pick what you want the chain data to tell you, and see which metric the article points to and how its source reads it.
What do you want the on-chain data to tell you?
- Where the market sits in its cycle → next question
- Whether coins that moved were sold at a profit or a loss → next question
- Whether coins or buying power are heading to trading venues → next question
- When to enter a single trade today or on an intraday chart → On-chain metrics are the wrong tool here
How do you want the gap between market cap and realized cap expressed?
- As a share of market value → NUPL (Net Unrealized Profit/Loss)
- Scaled by volatility, so extremes compare across cycles → MVRV Z-Score
Do you need to know which group of holders is selling?
- No, all coins that moved together → SOPR (Spent Output Profit Ratio)
- Yes, long-term versus short-term holders → Long-term vs short-term holders (LTH-SOPR, STH-SOPR)
Which flows are you watching?
- Bitcoin moving to and from exchange wallets → Exchange inflow, outflow and netflow
- Stablecoins and their buying power → Stablecoin Supply Ratio and stablecoin netflow
NUPL = (Market Cap − Realized Cap) / Market Cap. Glassnode reads values above 0 as the supply in net paper profit and values below 0 as typical of late bear markets. Named bands such as above 0.75 or below 0 come from third-party guides, and their boundaries differ between sites.
MVRV Z-Score = (Market Cap − Realized Cap) / Standard Deviation of Market Cap. Glassnode says readings far above realized value have historically coincided with tops (red zone) and the opposite extreme with bottoms (green zone). It describes past cycles; it does not predict the next one.
Glassnode's SOPR divides the realized value of coins that moved by their value when created. Above 1 means coins moved at a profit on average, exactly 1 at break-even, below 1 at a loss. Treating 1 as support or resistance is a trading interpretation, not part of the definition.
Glassnode counts coins with a lifespan of more than 155 days as long-term holder supply, with a gradual weighting around that cut-off. LTH-SOPR and STH-SOPR apply the profit ratio to each group, showing which cohort is realizing profits or losses.
CryptoQuant defines netflow as inflow minus outflow. It reads rising BTC inflows as mostly bearish and rising outflows as generally bullish, with caveats: derivatives-wallet inflows point to volatility, and staking or airdrop deposits are neutral. Check how the receiving address is labelled first.
SSR compares Bitcoin's market cap with the combined market cap of stablecoins; CryptoQuant links a low SSR to more stablecoin buying power. Growing stablecoin inflows to exchanges are read the reverse of BTC flows, as usually bullish. The metric assumes a closed crypto-only market.
The article says these metrics work over weeks and months and add little on intraday charts. Analysts use them to place the market in a cycle, look for several metrics pointing the same way, and check that against price structure and macro conditions.
This only maps a question to the metric the article describes; it shows no live readings, does not compare providers' address labelling, and is not trading or investment advice.
Metric 5: Exchange flows
Definitions (CryptoQuant): inflow is coins deposited into exchange wallets, outflow is coins withdrawn from them, and netflow is inflow minus outflow.
How it is read: CryptoQuant calls rising BTC inflows "mostly a 'Bearish' sign", because deposited coins are often headed for sale. It reads rising outflows as generally bullish, since holders may be moving coins to long-term storage. It adds caveats: inflows to derivatives wallets point to higher volatility rather than a clear direction, and deposits for staking or airdrops are neutral.
Context matters. A large transfer between a company's own wallets or to a custodian is not a deposit for sale, even if it looks like one on social media. Check what the receiving address is labelled as before reading anything into it. Understanding how blockchain transactions work makes these flows easier to interpret.
Metric 6: Stablecoin Supply Ratio (SSR)
What it measures (CryptoQuant): Bitcoin's market cap compared with the combined market cap of stablecoins.
How it is read: CryptoQuant links a low SSR to more stablecoin buying power relative to BTC, and a high SSR to thinner buying power. It also reads a falling SSR trend as bullish and a rising one as bearish or sideways. The metric assumes a closed market made up only of crypto assets and stablecoins, which real markets are not.
For stablecoin exchange netflow, CryptoQuant's interpretation is the reverse of BTC flows: growing stablecoin inflows to exchanges are usually read as bullish, because they can fund purchases.
Metric 7: Pi Cycle Top
The Pi Cycle Top is a price indicator usually shown next to on-chain charts, not an on-chain metric itself. Philip Swift created it in April 2019. It fires when the 111-day moving average crosses above twice the 350-day moving average (the multiple applies to price, not to the number of days). LookIntoBitcoin says it has marked cycle highs within 3 days over the past three market cycles. It also warns that the indicator worked during Bitcoin's adoption phase and may be less relevant after the launch of Bitcoin ETFs.
Beyond Bitcoin: Ethereum and DeFi metrics
The same ideas apply to other networks, with chain-specific additions:
- Fee burn: under EIP-1559, Ethereum's base fee "is always burned (i.e. it is destroyed by the protocol)", so heavy network use removes ETH from supply.
- Total value locked (TVL): DefiLlama's methodology counts "the value of any tokens locked in the contracts of a protocol / platform as TVL". It shows where capital sits in decentralised finance.
- Activity: active addresses and transaction counts show usage trends. For newer tokens, holder concentration (how much supply sits in a few wallets) often matters more than cycle metrics.
Cycle indicators such as NUPL and MVRV rest on Bitcoin's long history. On younger assets, the same formulas have not been through multiple cycles, so their extremes carry less information. More on how Ethereum smart contracts work helps when reading contract-level data.
Putting the metrics together
On-chain analysts usually work through three layers in order:
- Cycle position: NUPL and MVRV Z-Score show how far price sits above or below the market's aggregate cost basis.
- Behaviour: SOPR and the LTH/STH split show whether holders are realizing profits or losses, and which group is selling.
- Supply moving to market: exchange and stablecoin flows show whether coins or buying power are heading to trading venues.
A single reading carries little weight on its own. Analysts look for several metrics pointing the same way, then check that against price structure and macro conditions such as interest rates and liquidity. The metrics work over weeks and months. On intraday charts they add little.
Where to get the data
- Glassnode: realized-value metrics, SOPR and holder cohorts, with methodology in its documentation.
- CryptoQuant: exchange flows and stablecoin metrics, with a public data guide.
- LookIntoBitcoin: free cycle charts including MVRV Z-Score, NUPL and Pi Cycle Top.
- Dune: a web-based SQL editor and dashboard builder for querying blockchain data yourself.
- DefiLlama: protocol TVL.
Different providers label addresses differently, so the same metric can differ between sites. Read the methodology page before comparing figures.
Limitations: these metrics describe past behaviour and patterns from a small number of cycles; they do not predict prices, and nothing here is trading or investment advice.
