Introduction Professional road cycling races vary in format and terrain, resulting in diverse physiological demands on riders. These variations are largely attributable to the race profiles. A better understanding of race demands resulting from different race profiles can optimize cyclists` performance by tailoring training to race types. Additionally, it can support the decision making around a riders` race program, training periodization, and can enhance team composition and scouting by matching riders` strength and weaknesses to specific race profiles. Race organizers or researchers often apply their own criteria to categorize races into distinctive types. There is currently no standardized categorization for professional men`s road cycling. This study aims to develop a categorization model for professional road cycling races using clustering analysis.
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