We investigate the relationships between age and race performance in women`s road cycling. Therefore, we consider public data from ProCyclingStats (PCS) on race results of 558 female riders present in the top 500 of one of the yearly rankings between 1993 and 2021. We apply a data-driven approach consisting of three subsequent steps. First, we train decision tree classifiers to distinguish between race profiles. Second, we cluster the riders based on the fraction of PCS points obtained in different race types and uniquely identified the speciality of a rider as Sprinter, All Rounder or One Day. Third, we use polynomial regression to determine relationships between age and a rider`s yearly race performance, defined as the average number of points per race entered in a single year, for each cluster. We obtain that the yearly performance is independent of age for one-day specialists. For sprinters and all-rounders, we found that the race performance increases until it reaches a maximum at 28.7 (sprinters) and 27.0 (all-rounders) years and then decreases again. Our findings can be used as a benchmarking tool for monitoring the development of women`s road cyclists, talent identification or constructing long-term training programmes.
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