I computed graph embeddings on Athletes in a graph modelling Olympic Games in Neo4j. I was then able to compute the most similar Athletes to any given Athlete using Node2Vec. I could then visually appreciate this similarity by looking at the corresponding subgraph subsuming the related nodes and their edges.
The repository with the code and the example subgraphs can be found here.
An interesting future application to accompany this analysis would be to verbalize nodes similarities and differences with a template-based Natural Language Generation system.