Average Channel CapacityTRINITY EXCLUSIVE
Average BTC capacity per Lightning channel over time. Rising average capacity suggests larger (institutional) channels are opening, while falling capacity suggests a shift toward smaller (retail) channels. A proxy for the institutional vs retail mix of the network.
Trinity exclusive model
This metric is a proprietary Trinity Insights model. Its formula, inputs, weights and parameters are NOT disclosed. The page documents only the output (bounded scale, interpretation zones, historical context). Access to the score and its time series is via the REST API and the MCP server, subject to the required tier.
What is it?
This chart shows average BTC capacity per Lightning channel over time, calculated as total network capacity divided by public channel count. Rising average capacity suggests larger (institutional) channels are opening, while falling capacity indicates a shift toward smaller (retail, mobile) channels. It is a simple but effective proxy for the institutional vs retail composition of the network. Data comes from mempool.space (public channels only).
How to read
The line shows average BTC capacity per channel. An uptrend indicates larger channels opening (institutional, LSP). A downtrend marks a proliferation of small channels (mobile wallets, retail). Sudden spikes may indicate large channel openings by a major player (exchange, enterprise).
Key zones
Historical average capacity oscillates between 0.02 and 0.05 BTC per channel. Values > 0.05 BTC mark increased institutional concentration. Values < 0.02 BTC indicate retail dominance. The 90-day trend is more informative than daily values.
What to observe
Correlation with channel count is key: if channel count rises but average capacity falls, the network is expanding via small channels (retail adoption). If channel count stagnates but average capacity rises, large players are consolidating positions. Divergences between these two metrics are the most informative readings.
Historical context
Institutional activity became detectable starting in 2022-2023 with the entry of major players like River, Cash App, and early exchanges integrating Lightning. The whale component amplified in subsequent phases with Taproot adoption and the generalisation of submarine swaps.
Expert notes
⚠️ Trinity Exclusive Model - The heuristics used are probabilistic, not deterministic. Estimated false positive rates are: institutional ~20%, retail ~15%, whale ~30%. The 'whale' classification is least reliable because the techniques used (Swaproot, submarine swaps) are also used by automated services. This chart is an exploration tool, not a surveillance tool - it does NOT allow identifying specific entities.
Common mistakes to avoid
DO NOT interpret as identification of specific actors. Heuristics classify PATTERNS, not identities. An 'institutional' in this context means 'acts like an institutional' - not necessarily that it is one. Participant anonymity is preserved by design.
Programmatic access
REST API
curl -sS \
'https://api.trinityinsights.io/api/v1/onchain/ln-institutional-fingerprint/history?days=90' \
-H 'X-API-Key: $TRINITY_API_KEY'MCP server
{
"tool": "get_chart_value",
"metric_id": "ln-institutional-fingerprint",
"timeframe": "1y"
}Required tier: performance. See the pricing grid for the tier list and the MCP documentation for multi-client configuration.
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Institutional disclaimer
Trinity Insights is an educational and analytical tool. The metric above does not constitute investment advice. Trinity Insights is not a Crypto-Asset Service Provider (CASP) registered under MiCA Regulation (EU) 2023/1114. See the full disclaimer.