Module 6: On-Chain Analysis
DeFi and Token Data On-Chain
Chapter 9 of 12 · about 5 minutes
9.1 Every loan in public
"In traditional finance, you'd never know how much leverage people have against a particular asset," said Hash. "In DeFi, you can see every loan, every collateral position, and the exact price where each one gets liquidated."
Mint was amazed. "So I can see where the forced selling would happen?"
"For on-chain lending, yes," said Hash. "And a lot more besides."
Because DeFi protocols run entirely on smart contracts, their activity is completely visible. This chapter covers how to use that data for analysis, building on Module 5's fundamental analysis.
9.2 Lending protocol data
Lending protocols (covered in depth in the DeFi module) let users deposit collateral and borrow against it. On-chain, you can see:
| Data | What it tells you |
|---|---|
| Total deposits and borrows | How much is being lent and borrowed |
| Utilisation rate | Borrows as a share of deposits; high utilisation means high demand to borrow |
| Borrow rates | The cost of borrowing; rising rates suggest strong demand for leverage |
| Collateral composition | Which assets back the loans |
| Liquidation levels | Prices at which positions become eligible for liquidation |
| Actual liquidations | Positions being closed, and when |
Utilisation example:
| Value | |
|---|---|
| Stablecoins deposited | $1,000 million |
| Stablecoins borrowed | $850 million |
| Utilisation | 85% |
High stablecoin utilisation means many people are borrowing dollars, often against crypto collateral, to buy more crypto or to trade. That's a sign of leverage building up in the system.
9.3 On-chain liquidation levels
Each borrowing position in a lending protocol has a liquidation price, determined by its collateral and debt. Analytics tools can add up all positions to show how much collateral would be liquidated at each price level.
| ETH price falls to | Collateral eligible for liquidation (illustrative) |
|---|---|
| $2,800 | $40 million |
| $2,600 | $180 million |
| $2,400 | $350 million |
Chapter 9 · On-chain liquidation levels
A ladder below the current ETH price, which is above $2,800. If ETH falls to $2,800, $40 million of collateral becomes eligible for liquidation; this is the nearest trigger. At $2,600, $180 million. At $2,400, $350 million. Between the levels, notes say forced selling can push price down to the next level. Amounts are illustrative.
Large clusters show where a price drop could trigger significant forced selling, potentially accelerating a decline. This complements the liquidation heatmaps from centralised exchange derivatives in Module 7, Chapter 10. Unlike those, which are estimates, on-chain lending liquidation levels are calculated from actual positions, though borrowers can add collateral or repay before liquidation happens.
9.4 DEX data
Decentralised exchanges record every trade on-chain.
| Metric | What it shows |
|---|---|
| DEX volume | Trading activity, by token, pair, and chain |
| DEX share versus centralised exchanges | Whether trading is moving on-chain |
| Liquidity depth | How much can be traded without large price impact (Module 1, Chapter 8) |
| New pools and tokens | Speculative activity, often in new or small tokens |
| Number of unique traders | Breadth of participation, with sybil caveats |
A surge in new token launches and DEX trading in small tokens often signals a speculative phase of the market, sometimes called "risk-on." When that activity collapses, risk appetite has usually faded.
9.5 Token holder analysis
For any token, on-chain data shows who holds it and how that's changing. This is especially useful for the due diligence in Module 5.
| Analysis | What to look for |
|---|---|
| Holder count over time | Growing or shrinking base of holders |
| Concentration | Share held by top wallets, excluding exchanges and contracts (Chapter 2) |
| Insider wallet activity | Team, investor, and treasury wallets moving to exchanges |
| New versus long-term holders | Whether holders are staying or churning |
| Liquidity pool ownership | Whether liquidity can be pulled (Module 2, Chapter 11) |
A practical example. Before buying a newer token, Mint checked its insider wallets. Two investor wallets had received unlocked tokens last month (Module 5, Chapter 5), and one had already sent 60% of its tokens to an exchange deposit address.
"That's not proof they sold," said Mint. "But it's a strong hint."
"And it's a hint you'd never get in the stock market," said Hash.
9.6 Smart money and wallet profiling
Many platforms label wallets as smart money based on past performance: wallets that bought tokens early and sold profitably, funds, or experienced DeFi users. Some traders watch what these wallets buy.
The cautions from Chapter 4 apply even more strongly here. Labels are based on past success, which may not continue. Profitable wallets may be insiders with information you don't have. Watching the same wallets as thousands of others means you're late. And some "smart money" wallets are traders who deliberately buy small amounts to attract followers, then sell to them.
Use smart money data as one input for discovering what's getting attention, not as a signal to copy.
9.7 Protocol-level fundamentals
On-chain data verifies the business metrics from Module 5, Chapter 7, directly at the source:
- Fees and revenue can be calculated from contract events, rather than trusting a project's announcements.
- Unique users and retention can be measured, with sybil filtering.
- Incentive payouts can be tracked to see how much activity is subsidised.
- Treasury balances and spending can be monitored.
"So I can check whether a project's marketing matches reality," said Node.
"That's one of the most valuable uses of on-chain data," said Hash. "Trust, but verify. Actually, in crypto: verify, then decide how much to trust."
9.8 Try it yourself
Find a lending protocol's analytics page or a third-party dashboard. Note the total deposits, borrows, and utilisation for the main stablecoin. Then find a chart of liquidation levels for ETH collateral and identify the largest cluster below today's price.
For a token you're researching, find its top holders on a block explorer, identify any team or investor wallets, and check whether they've sent tokens to exchanges recently.
Key takeaways from this chapter
- DeFi activity is fully on-chain, so loans, collateral, trades, and liquidations are visible.
- Lending utilisation and borrow rates show how much leverage is building.
- On-chain liquidation levels are calculated from real positions and show where forced selling could occur.
- DEX volume, new pools, and token launches reveal speculative activity and risk appetite.
- Token holder analysis shows concentration, churn, and insider wallet behaviour.
- Smart money labels are based on past performance and should be used for discovery, not copying.
- On-chain data lets you verify protocol fees, users, incentives, and treasuries directly.