The purpose of this study was to generate movement category velocity thresholds for elite Gaelic football (GF) and hurling referees using a two-stage unsupervised clustering technique. Activity data from 41 GF and 38 hurling referees was collected using global positioning system technology during 338 and 221 competitive games, respectively. The elbow method was used in stage one to identify the number of movement categories in the datasets. In stage two, the respective velocity thresholds for each category were identified using spectral clustering. The efficacy of these thresholds was examined using a regression analysis performed between the median of each of the velocity thresholds and the raw velocity data. Five velocity thresholds were identified for both GF and hurling referees (mean ± standard deviation: GF referees; 0.70±0.09, 1.66±0.19, 3.28±0.41, 4.87±0.61, 6.49±0.50 m·s−1; hurling referees; 0.69±0.11, 1.60±0.25, 3.09±0.52, 4.63±0.58, 6.35±0.43 m·s−1). With the exception of the lowest velocity threshold, all other thresholds were significantly higher for GF referees. The newly generated velocity thresholds were more strongly associated with the raw velocity data than traditional generic categories. The provision of unique velocity thresholds will allow applied practitioners to better quantify the activity profile of elite GF and hurling referees during training and competition.