Power Profiling, Workload Characteristics, and Race Performance of U23 and Professional Cyclists, 2021, Leo et al

Full title: Power Profiling, Workload Characteristics, and Race Performance of U23 and Professional Cyclists During the Multistage Race Tour of the Alps

Purpose: The aim of this study was to compare the power profile, internal and external workloads, and racing performance between U23 and professional cyclists and between varying rider types across 2 editions of a professional multistage race.

Methods: Nine U23 cyclists from a Union Cycliste Internationale “Continental Team” (age 20.8 [0.9] y; body mass 71.2 [6.3] kg) and 8 professional cyclists (28.1 [3.2] y; 63.0 [4.6] kg) participated in this study. Rider types were defined as all-rounders, general classification (GC) riders, and domestiques. Data were collected during 2 editions of a 5-day professional multistage race and split into the following 4 categories: power profile, external and internal workloads, and race performance.

Results: The professional group, including domestiques and GC riders, recorded higher relative power profile values after certain amounts of total work (1000–3000 kJ) than the U23 group or all-rounders (P ≤ .001–.049). No significant differences were found for external workload measures between U23 and professional cyclists, nor among rider types. Internal workloads were higher in U23 cyclists and all-rounders (P ≤ .001–.043) compared with professionals, domestiques, and GC riders, respectively. The power profile significantly predicted percentage general classification and Union Cycliste Internationale points (R2 = .90–.99), whereas external and internal workloads did not.

Conclusion: These findings reveal that the power profile represents a practical tool to discriminate between professionals and U23 cyclists as well as rider types. The power profile after 1000 to 3000 kJ of total work could be used by practitioners to evaluate the readiness of U23 cyclists to move into the professional ranks, as well as differentiate between rider types.

Human Kinetics: https://doi.org/10.1123/ijspp.2020-0381

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