Kinetic time-curves can classify individuals in distinct levels of drop jump performance.
Panoutsakopoulos V., Chalitsios C., Nikodelis T., Kollias IA.
This study examined whether analysing kinetic features of drop jumps (DJ) as one-dimensional biomechanical curves can reveal specific patterns that are consistent and can cluster DJ performance. Hierarchical clustering analysis on DJ from 40 cm data performed by 128 physically active male participants (23.0 ± 4.5 yrs, 1.84 ± 0.07 m, 79.1 ± 10.8 kg) was performed on the derived time-normalised force, power and vertical stiffness curves to unmask the underlying patterns and to explore the dissimilarities identified from the subgroup (cluster) analysis. Results revealed poor, average and top DJ performers. Top performers exhibited larger peak force, power and vertical stiffness compared to the other two groups, and the poor performers had lower values compared to the average performers (p