Develop your own data-driven Lightning Network insight

Discover network-wide statistics on nodes, interactively explore node local networks, measure the impact of opening or closing a channel, and identify potentially profitable paths in the network


Summary stats


See node stats on

Step 2: enter or select pubkey/alias of up to 3 nodes with which to simulate adding or removing channels

Optional: apply filters to pubkey or alias menu choices

Node centrality ranks

Centralization scores of the network

Source code

See the code here .

Betweenness centrality

Betweeness centrality measures the number of shortest paths that pass through a node. A higher number of shortest paths a node has to any two other node in the network, the more likely they will be included in a route depending on the liquidity balance of each channel in the path.

Closeness/hopness centrality

Closeness/hopness centrality is a measure of how many hops it takes to reach any node on the network from a given node. The better the rank, the fewer the hops required to reach any and all nodes.

Eigenvector/hubness centrality

Eigenvector/hubness centrality measures influence of a given node in the network. Higher ranks imply a well-connected node that is linked to other well-connected nodes. A lower eigenvector centrality could also imply a new and/or underserved node in the network.

Maximum liquidity flow

Maximum flow is the highest amount of sats that can theoretically be pushed through a path if liquidity were 100% outbound. In reality, outbound across a path is likely 50% or less.

Community

The communities are inferred with the Louvain algorithm. It detects clusters of nodes. It could be a useful metric to identify groups of nodes further away from a given node in the network.