In a groundbreaking development, scientists have introduced a mathematical model poised to revolutionize training methods for athletes participating in 400-metre and 1,500-metre events. The study, published on Tuesday, leverages performance data from elite athletes, including Olympic 1,500 metres champion Jakob Ingebrigtsen, Dutch world indoor 400m record holder Femke Bol, and Britain’s Matthew Hudson-Smith, gathered at the 2022 European Championships in Munich.
The model delves into the physiological intricacies of both sprinting and endurance racing, providing insights into energy expenditure, maximum oxygen consumption (VO2), running economy, and motor control. Utilizing GPS sensors under athletes’ jerseys, researchers precisely tracked their speeds, with positions indicated ten times per second.
Scientists from the French National Centre for Scientific Research (CNRS) analyzed the data, unveiling the model’s capacity to offer instantaneous access to optimal racing strategies through the quantification of costs and benefits.
Key findings highlighted the critical role of a swift start in the initial 50 metres, linked to oxygen consumption speed, and the significance of minimal deceleration in the latter part of a 400-metre race. Simulations clarified Ingebrigtsen’s performance by emphasizing his ability to rapidly reach and sustain maximum oxygen consumption throughout the race, enabling him to maintain a higher pace than competitors despite a seemingly less forceful start.
The implications of this model extend to the development of performance support software, empowering coaches to fine-tune racing strategies based on the individual physiological profiles of their athletes. This pioneering approach holds the potential to reshape training methodologies and enhance the performance of middle-distance runners.
