Introduction: The BMX start is crucial for race performance, often measured by the time to the kink at 3.15 m from the start.
Objective: This study aims to optimize the BMX SX gate start using predictive optimal control techniques, focusing on the effects of maximal crank torque and reaction time on performance.
Method: Two models were used: The ‘upper extremities’ model analysed varying crank torques (250 Nm to 350 Nm) and reaction times (0.14 s, 0.16 s, 0.18 s).
The ‘two legs’ model was assessed under a single condition to better reproduce crank torque and track experimentally measured kinematics.
Results: Higher crank torques led to more forward initial positions, reduced recoil, and increased final velocities. The velocity of the start gate was a limiting factor initially, with timing and technique being crucial until the gate is halfway open. Reaction time variations showed minor effects on performance, and no strategy adaptation was needed within the tested range. The ‘two legs’ model accurately tracked experimental kinematics with low RMSE values. The predictive simulation with the ‘two legs’ model showed an improvement in kink time. The kink time for the predictive optimal control solution was 1.15 s compared to 1.23 s in the experimental trial.
Conclusion: This framework for researching the BMX start using predictive optimal control offers a systematic basis for future research. Insights can improve training strategies focusing on technique, timing, and initial start position. Future research could explore the effects of leg strength, hip range of motion, and gear ratios or crank lengths on performance.