On-Chain: How to Read Crypto Data and Metrics

When you first enter the crypto market, price charts are usually one of the first tools you turn to. Then as you become more familiar with crypto, your questions will likely extend beyond price movements, and price charts are simply not enough anymore. 

This is where on-chain activity can step in to help you answer those advanced questions..

1What Does On-Chain Even Mean?

On-chain refers to activity that is processed and stored directly on a blockchain. 

For a basic transaction, the blockchain may record details such as the sender, recipient, transferred value, transaction fee, timestamp, and block information.

On-chain activity is any action processed and recorded directly on a blockchain.

On the other hand, transactions on smart contract-enabled networks such as Ethereum, BNB Chain, and Avalanche can also produce event logs. These logs provide structured information about actions carried out during smart contract execution, such as a token swap, liquidation, or staking deposit. 

Since these records are all available on the blockchain, virtually everyone can verify what happened. Then again, that is pretty much the most useful thing that these data points can do on their own. 

If investors’ purpose is to reveal broader market patterns, then these individual records need to be processed and aggregated into on-chain metrics.

2The Main Categories of On-Chain Metrics 

Different metrics will help you answer different questions about a blockchain. 

Network Activity

If investors wonder whether a network has any activity at all, active addresses is a good place to start. This metric measures how many unique addresses are participating in at least one successful transaction during a given period. Sustained growth in active addresses could (emphasis on could) be an indication that more people are interacting with the network. 

Higher activity alone, however, does not tell us whether the network is attracting new participants. This is where new addresses come into play, since it shows you addresses that appear on-chain for the first time.

Active addresses help show how much a network is being used, while new addresses provide additional context.

To further this knowledge, analysts may want to discover how much transactional activity those addresses actually generate. Transaction count fills this gap by measuring the number of confirmed transactions over a given period. 

This metric, however, treats every transaction equally regardless of how much value it carries. To tell between a network processing many tiny transactions and one handling fewer but larger transfers, transfer volume would be an ideal tool, since it tracks the total value moved on-chain.

After tracking these figures, investors would generally have a hang of whether or not crypto is moving on the blockchain. But where exactly is this value going?

Capital Flows and Exchange Activity

The simplest way to examine crypto movements is to look at exchange inflows and outflows. While the former measures assets moving into exchange wallets, the latter measures assets that are moving out. 

Comparing these two will give you exchange netflow. A positive netflow means more assets entered exchanges than left them, while a negative netflow indicates the opposite. 

However, since netflow only captures movement during a specific period, it does not show how much of the asset remains on exchanges overall. Exchange reserves provide this broader view by measuring the total amount held in exchange wallets. 

Naturally, these crypto movements change how the asset's supply is distributed across holders. To assess how ownership is shifting though, investors need to move beyond capital flow and also look at supply-related figures.

Supply and Holder Behavior

Supply distribution shows how holdings are spread across different wallet-size groups. Changes in these groups can demonstrate whether supply is becoming more concentrated in the hands of crypto whales (large holders) or more widely distributed. 

Another way for investors to examine the supply is through holding duration, which is commonly used to distinguish between long-term holders (LTH) and short-term holders (STH).

Investors should examine both supply distribution and holding duration.

For a coin to be classified as part of the LTH supply, it generally needs to have remained dormant for 155 days or longer. Any coins that have been moved more recently would typically be classified as STH supply.

In this sense, a relatively large LTH balance can suggest that veteran investors remain confident enough to hold through market fluctuations. By contrast, a rising STH share points to more crypto supply being in the hands of newer participants, whom may be more sensitive to short-term market conditions and price changes.

On another note, just because people are holding a certain position for a long time does not necessarily guarantee that those cryptos are profitable (sunk costs are a pretty common determinator). Metrics related to valuation, therefore, will be useful to examine before any decision is made.

Valuation and Profit/Loss

One way to assess whether investors are sitting on unrealized gains or losses is by using Realized Cap. This metric provides a reference point by valuing each unit of supply at the price when it last moved on-chain.

MVRV (Market Value to Realized Value) builds on this baseline and calculates the current market value (Market Cap) relative to the realized value (Realized Cap). A higher MVRV generally indicates larger unrealized gains across the supply. By contrast, a value below 1 would suggest that the supply is collectively in unrealized loss. 

NUPL (Net Unrealized Profit/Loss), meanwhile, expresses this difference by showing net unrealized profit or loss relative to the current market value. 

Besides unrealized positions, investors may also want to examine what happens to the coins that actually move. SOPR (Spent Output Profit Ratio) measures whether coins are being transferred at a profit or a loss based on their value when they last moved. A SOPR above 1 tells investors that spent coins are being moved at a profit on average, and the opposite is true when the calculation plummets below 1.

DeFi and Protocol Activity

On-chain analysis can also help investors assess how capital is being used within DeFi protocols. 

If investors want to see how much capital is currently committed to a protocol, Total Value Locked (TVL) is a useful starting point. A rising TVL can indicate that more capital is being deposited in a protocol's smart contracts, though that’s not necessarily always the case. Since TVL is usually measured in USD, it can rise simply because the prices of deposited assets have gone up.

TVL shows how much capital is deposited in DeFi smart contracts.

To assess whether the capital committed to a protocol is accompanied by actual usage, investors can look at DEX volume. It captures the value of trades executed through decentralized exchanges over a given period. Comparing trading activity with TVL can, therefore, help put the protocol's capital base into perspective.

The final question is whether this activity creates economic value. Protocol fees and revenue answer this question by showing how much users pay for using the protocol and how much income that activity generates.

3How to Analyze On-Chain Data

So then, what can you do with all this knowledge about on-chain metrics? 

Start with a Question

Defining what you want to find out is the ideal first step that you should take. For instance, you might ask whether network adoption is growing, whether large holders are increasing their positions, or if capital is moving toward exchanges. Your specific question will determine which data is relevant and the metrics you will likely use.

By contrast, starting with a chart instead will very likely encourage confirmation bias, since you may end up searching for a validation for the pattern you have already noticed.

Define the Scope of the Analysis 

Once you have a question, identify where the relevant activity takes place. Just to give you an example, if a token is widely used across Ethereum, Base, and Arbitrum, analyzing Ethereum alone may make its network activity appear lower than it really is.

Similarly, the timeframe should also match the question. Shorter periods should be used when investigating recent changes. Otherwise, if you’re trying to identify broader trends then longer periods (think, 90 days or a full market cycle) would be more useful.

Identify the relevant networks and timeframe before analyzing on-chain activity.

Choose Complementary Metrics 

With the scope defined, you should pick around 3 - 5 metrics that bring together different pieces of the bigger picture. An analysis of market activity, for instance, could combine network activity, exchange flows, holder behavior, and valuation metrics. 

You should be careful when using metrics that are based on the same underlying data though. Exchange inflow and exchange reserves, for instance, both rely on labeled exchange wallets. Therefore, they should not automatically be treated as two independent confirmations.

Compare Trends and Relationships

By this point, we already know that a single data point rarely provides enough context to support a conclusion. In this regard, comparing the current reading with historical performances (say, 7-day or 30-day averages) and looking at how quickly changes happen would be much more useful.

A single on-chain data point should be compared with historical averages and the speed of change.

The relationship between metrics can also reveal more than readings of a single metric. To demonstrate, rising prices alongside growing active addresses may indicate that the price increase is supported by broader participation in the network. On the other hand, when prices rise is accompanied by active addresses remaining flat or decline, this same price movement may be because of existing participants

Check the Data Before Interpreting It

A metric is only useful if you understand what its value represents. 

This includes looking at which assets and blockchains are covered, whether the metric uses raw data or adjusts for multiple addresses belonging to the same entity, and whether volume is measured in the native asset or USD. Analysts also need to check which timezone is used for timestamps, and when the data was last updated.

Any mismatch in these details can all be the reason why two platforms report different values for what appears to be the same metric. Two providers, for instance, may report different active-address counts for the same blockchain and day. This likely comes down to differences in either their address labels, coverage, or calculation methods.

4Which Tools Should You Use?

The best tool for on-chain analysis depends on how specific your question is and how much control you need over the data.

You can utilize multiple tools for on-chain analysis.

Start With Standardized Metrics

If you want to monitor established on-chain metrics without building them yourself, Glassnode and CryptoQuant are likely where you’ll find the most comfort in.

Glassnode covers a wide range of metrics, including holder cohorts, entity-adjusted data, realized capitalization, MVRV, and SOPR. It is particularly useful for studying broader market and cycle trends.

CryptoQuant puts more emphasis on exchange flows, miner activity, and trading-related data, making it a better fit when your question centers on where assets are moving and how that may relate to market activity.

When Standard Metrics Are Not Enough

Sometimes an existing metric cannot answer the question you have in mind. This is where Dune becomes useful. It allows users to query blockchain data with SQL and build their own metrics and dashboards.

For example, instead of asking whether Ethereum activity is increasing overall, you could use Dune to investigate a specific protocol, smart contract, or type of transaction. Of course, the trade-off is that you need more technical knowledge to work with the underlying data.

Investigate Wallets and DeFi Activity Separately

If the question is about who is moving funds, wallet-focused tools can provide more useful context. Nansen and Arkham both provide wallet labels and entity information, with Nansen focusing more on wallet and smart-money activity and Arkham offering broader address intelligence.

For questions about DeFi protocols, DeFiLlama provides metrics such as TVL, protocol fees, DEX volume, and revenue across multiple ecosystems.

Finally, when you need to verify what actually happened on-chain, a blockchain explorer is the most direct source. It lets you inspect individual transactions, addresses, and blocks rather than relying on an already-processed metric.

5Limitations and Common Mistakes

On-chain metrics make blockchain activity easier to interpret, but the data still has limits.

On-chain metrics are useful but limited.

Address Data Does Not Directly Represent Users 

First of all, blockchain data can only identify addresses. Why do we need this clarification in the first place? 

It’s because one person may control multiple addresses, while an exchange may operate many wallets on behalf of its customers. As a result, counting addresses does not necessarily tell us how many users are participating or how much activity comes from a particular entity.

To make the data more meaningful, analytics providers may identify addresses that belong to the same exchange, fund, protocol, or other entity and group them together. This is called entity-adjusted data. 

Though, these identifications are based on available evidence and are not always complete or consistent. Different providers may, therefore, classify the same addresses differently. Newly created wallets or changes in wallet usage may also take some time to be identified.

Recorded Activity Does Not Always Equal Economic Activity

Even when the addresses involved are known, the amount of on-chain activity does not always accurately reflect the amount of economic activity. The reason is that a blockchain records transactions and transfers regardless of what caused them. 

Some may come from bots or smart contracts rather than independent user actions. Transfers between wallets controlled by the same entity can also create additional activity.

A rise in either metric, therefore, does not automatically mean more users are participating or more capital is changing hands.

On-Chain Data Does Not Cover the Entire Market

That said, not every crypto transaction is on-chain. In case a trade is settled outside of the blockchain, it would be considered an off-chain activity. 

On-chain analysis, therefore, can only provide a detailed view of activity within its observable domain, rather than a complete picture of the crypto market. Other data sources may be needed to understand activity taking place outside the blockchain.

Correlation Does Not Mean Causation

Even when a metric accurately captures the activity it is designed to measure, it does not necessarily explain why that activity occurred or what will happen next.

This is particularly important when interpreting historical levels of metrics such as MVRV and SOPR. A threshold that coincided with a market top or bottom in one cycle may not produce the same result in another.

6A Final Word on On-Chain Analysis

CoinMinutes' final goal when writing this article is not to tell you what to buy or sell. Rather, we hope to provide you with the information needed to understand and make informed decisions when using on-chain data.

Now that you've somewhat grasped some of the main concepts of on-chain analysis, perhaps a more in-depth look into specific metrics and how to interpret them is in queue. Or maybe exploring other ways to analyze the crypto market is more so your cup of tea?

If those are the kinds of crypto coverage you are looking for, check out our website at https://coinminutes.com/ for more updates.