Our aim was to use a self-organising map (SOM) to examine key biomechanical variables previously identified to discriminate best from worst placekicking attempts. Placekicker and ball 3D biomechanics were acquired from three competitive placekickers who performed 10 kicks outdoors, 35-m from the posts. Seven key variables were extracted for SOM analysis and kicks were categorised into "best", "typical", and "worst" for each placekicker based on kick outcomes and player and coach ratings. SOM output indicated that three clusters best explained intra-cluster similarities and inter-cluster differences. The three clusters highlighted differences between the biomechanical variables of the three placekickers rather than the best, typical, and worst kicks. Within-clusters, however, the best and worst kicks tended to be represented by nodes in separate map regions.