The effect and complexity of various pacing strategies on the energy expenditure during a 20km cycling time trial

Pacing strategy is important in athletic competition so that the available metabolic resources are used effectively to complete a physical activity in the minimum time possible1. According to the Central Governor Model2, 3 (CGM), there is a central regulator that paces the peripheral systems during an exercise task to reach the endpoint of that activity without homeostasis failure4, 5. In this study, the energy expenditure through aerobic and anaerobic metabolisms is investigated for various pacing strategies that are self-paced, even-paced and variable-paced for a 20 km cycling time trial. Fractal analysis using the Higuchi algorithm is applied to the power outputs to determine the fractal dimension (FD) or complexity of these pacing strategies. There is no significant difference in the gross mechanical efficiency of mean (±SD) of 18.1±1% in between the pacing strategies for all cyclists. The total amounts of work done by all the cyclists for self-paced, even- paced and variable-paced strategies are 5.14 MJ, 5.15 MJ and 5.13 MJ, respectively, and the means of the fractal dimensions for these pacing strategies are 1.33±0.03, 1.0 and 1.38±0.01 respectively. It is found that there is a significant difference (p