Field-testing to determine power – cadence and torque – cadence profiles in professional road cyclists.

Taylor, Kurt Bergin; Deckert, Sebastian; Sanders, Dajo

The aim of this study was to evaluate a field-based approach to determine torque-cadence and power-cadence profiles in professional cyclists and establish if this field-based protocol can differentiate between varying rider specialisations. Twenty-four male professional athletes from a World Tour cycling team participated in this investigation (Height = 1.84 ± 0.05 m, Weight = 72.3 ± 5.6 kg, Age = 25 ± 4 y). All riders were subsequently categorised into the following groups: 1) General Classification (GC) group; 2) sprinter group; and 3) classics group. All participants completed a specific sprint protocol in the field which included 6 times 6s sprints with varying gearing, starting cadences, starting speeds and position (i.e. seated vs standing). Power-cadence and torque-cadence profiles were determined based on the sprint outputs. There was a significant main effect of rider specialisation on the measured (sprint) variables (P≤0.03). Body weight, maximum power outputs (1s, 10s and modelled) and maximum torque were highest in the sprinter group, followed by the classics group, followed by the GC group. The protocol was able to differentiate between different rider specialisations (i.e. GC, sprinters, classics). The proposed methodology can contribute to individualising training content in the short-duration domain. Highlights Commercially available power metres can be used to assess power-cadence and torque cadence relationships in the field Key differences are present for the modelled parameters between cyclists of different specialisations Profiling a cyclist's power-cadence and torque-cadence relationship provides greater insight into the physiological mechanisms behind maximal power production

TORQUE; FIELD research; STATISTICS; BODY weight; ONE-way analysis of variance; STANDING position; EXERCISE physiology; CYCLING; PEARSON correlation (Statistics); SITTING position; EXERCISE intensity; DESCRIPTIVE statistics; BIOMECHANICS; ATHLETIC ability; DATA analysis software; DATA analysis

European Journal of Sport Science, 2023, Vol 23, Issue 7, p1085

1746-1391

Academic Journal

10.1080/17461391.2022.2095307