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Software that can predict athletic performance created by researchers

 

Agence France-Presse

 /  Tue, July 16, 2019  /  03:07 am
Software that can predict athletic performance created by researchers

Published in the journal Plos One, the study measured athletes’ metabolic and neuromuscular fatigue.  (Shutterstock/areebarbar)

Researchers in Australia have developed prototype software that studies the impact of fatigue on athletic performance.

Published in the journal Plos One, the study measured athletes’ metabolic and neuromuscular fatigue. The software algorithm developed by the researchers enables athletes’ energy levels to be calculated and predictions to be made about how their level of fatigue might affect their performance.

“Let us say you have a game tomorrow and the model predicts you are going to be very fatigued, that might change the coach’s strategy,” said Dr. Paul Wu, a researcher at Australia’s Queensland University of Technology and the study’s lead author.

While metabolic fatigue requires only a few hours of recovery, the same is not true for neuromuscular fatigue, which can take up to 48 hours or more to recover from.

“In the elite sports setting, athletes often train twice a day, five days or more a week. If you develop neuromuscular fatigue and have training or competition the next day, you will still be fatigued and have an elevated risk of injury,” Dr. Wu said.

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Comparing your performance to others

To design the software, Dr. Wu’s team subjected a dozen non-professional athletes to a “countermovement jump” test, which involves standing on a force plate, squatting and jumping as high as possible.

“In our study, we tested the athletes after low, moderate and high-intensity training sessions. We did many jumps over time, from just before training sessions, to right after, and then at regular intervals up to 48 hours later,” he explained.

The scientists then used a statistical analysis tool to process the athletes’ physiological data. “By doing a few jump tests up to 30 minutes after training, and then doing our analysis, we can predict the degree of neuromuscular fatigue,” said Dr. Wu, who also sees it as an opportunity for athletes to compare their performance with others.