On-chain data
Crypto has a data source no other asset class can offer: the ledger itself is public. Every transfer, every balance, every coin's dormancy is visible to anyone. Analysing this is on-chain analysis — fundamental analysis for an asset with no earnings reports.
What the chain records
Addresses and their balances, transfers between them, and timestamps. From these primitives, analysts build higher-level metrics. The big families:
Exchange flows — the most watched
- Inflows to exchanges — coins moving from private wallets onto exchanges. You generally move coins to an exchange to do one thing: sell. Large sustained inflows = potential sell pressure.
- Outflows from exchanges — coins withdrawn to self-custody, typically for holding. Falling exchange balances = shrinking readily-sellable supply.
Adoption and activity
- Active addresses / transaction counts — a network-usage pulse. Price rising while activity falls is a divergence worth respecting.
- Stablecoin supply — total USDT/USDC in circulation is "dry powder" sitting at the door of the market. Expanding supply has historically accompanied bull phases.
Holder behaviour
- Long-term holder supply — coins unmoved for 155+ days. These wallets accumulate through bear markets and distribute into euphoria; their behaviour marks regimes.
- Realised price — the average price at which the existing supply last moved: an on-chain cost basis for the whole market. Price crossing it has historically separated bear from bull regimes.
Where to find it
Glassnode, CryptoQuant and similar platforms publish these metrics with free tiers; exchange-flow alerts also circulate on social media (verify before reacting — big "exchange inflows" sometimes turn out to be internal wallet reshuffles).
On-chain data is slow and noisy. It describes regimes over weeks and months; it will not time a 5-minute entry. Metrics can mislead (exchange wallets get relabelled; one whale can dominate a day's flows). And for the contest specifically: SOL and XRP have thinner, less mature on-chain analytics than BTC and ETH.
On-chain metrics answer "what are holders actually doing?" — accumulation or distribution, supply tightening or flooding toward exchanges. Use them to set your directional bias, and technical analysis to time within it.