Not clustered: 23. Hossain Tefaili — only 8 of 20 metrics available (needs ≥ 60%); 24. Adrian Connor — only 9 of 20 metrics available (needs ≥ 60%); 25. Dustan Hansen — only 9 of 20 metrics available (needs ≥ 60%); 26. James Atkinson — only 3 of 20 metrics available (needs ≥ 60%); 27. Randall Clotworthy — only 1 of 20 metrics available (needs ≥ 60%); 28. Marcus De Vecchi — only 3 of 20 metrics available (needs ≥ 60%); 29. Neil Hooke — only 5 of 20 metrics available (needs ≥ 60%); 30. Jason Lannstrom — only 1 of 20 metrics available (needs ≥ 60%); 31. Keith Lavers — only 3 of 20 metrics available (needs ≥ 60%); 32. Paul Lawrence — only 1 of 20 metrics available (needs ≥ 60%); 33. Colin Mackie — only 1 of 20 metrics available (needs ≥ 60%).
GlideComp groups the pilots by flying style, and not by score. It transforms the rank of every behavioural metric to a percentile inside the field. It then compares two pilots by the mean percentile gap over the metrics that both pilots have, and never fills in a missing value. Ward-linkage agglomeration forms the groups, and the best mean silhouette selects the number of groups. Each group carries the spread of the GAP ranks of its members, which shows where a style paid and where it did not.
k was searched from 2 to 6. The mean silhouette is 0.20 — a value near 0 means soft group boundaries, and a value near 1 means tight, well-separated groups.