Performance Measurement 2.0: Towards a Data-Driven Cyclist Specialization Evaluation

Current cycling analytics solutions do not account for either the raced course profile or the level of the competition. Therefore, this paper suggests a two-stage approach which initially clusters races into coherent clusters based upon both elevation and road surface type. Subsequently, underlying skill levels are determined per cluster through the observed race results. Our results indicate that the methodology results into clusters which match the commonly known specializations in road cycling. The ranking methodology results into skill ratings which enable the identification of specialization and can be used in other downstream tasks.