Validating an Adjustment to the Intermittent Critical Power Model for Elite Cyclists-Modeling W′ Balance During World Cup Team Pursuit Performances

Purpose: Modeling intermittent work capacity is an exciting development to the critical power model with many possible applications across elite sport. With the Skiba 2 model validated using subelite participants, an adjustment to the model's recovery rate has been proposed for use in elite cyclists (Bartram adjustment). The team pursuit provides an intermittent supramaximal event with which to validate the modeling of W ' in this population. Methods: Team pursuit data of 6 elite cyclists competing for Australia at a Track World Cup were solved for end W ' values using both the Skiba 2 model and the Bartram adjustment. Each model's success was evaluated by its ability to approximate end W ' values of 0 kJ, as well as a count of races modeled to within a predetermined error threshold of +/- 1.840 kJ. Results: On average, using the Skiba 2 model found end W ' values different from zero (P = .007; mean +/- 95% confidence limit, -2.7 +/- 2.0 kJ), with 3 out of 8 cases ending within the predetermined error threshold. Using the Bartram adjustment on average resulted in end W ' values that were not different from zero (P = .626; mean +/- 95% confidence limit, 0.5 +/- 2.5 kJ), with 4 out of 8 cases falling within the predetermined error threshold. Conclusions: On average, the Bartram adjustment was an improvement to modeling intermittent work capacity in elite cyclists, with the Skiba 2 model underestimating the rate of W ' recovery. In the specific context of modeling team pursuit races, all models were too variable for effective use; hence, individual recovery rates should be explored beyond population-specific rates.

Automated summary

Analyzing the modeling of intermittent work capacity in elite cyclists, the Bartram adjustment was found to be an improvement over the Skiba 2 model, with a focus on W' in this population. However, in the specific context of team pursuit races, all models were too variable for effective use, indicating the need for exploration of individual recovery rates beyond population-specific rates.