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
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
See the code here .
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 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 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.
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.