ATHLETE MOVEMENT SIGNALS KEY TO AVOID INJURY SETBACK
- Amelia Taylor
- Aug 30
- 2 min read
Injuries don’t just sideline professional footballers - they plague everyday Australians too, from weekend joggers to netball players and school kids on the footy field.
New research from QUT has developed a tool that can predict when athletes of all levels are most at risk of another setback.
The system draws on wearable sensors - the same kind of tech already found in popular smartwatches and fitness trackers — and combines that data with information about past injuries and context (whether you’re in a game or just training). The result? A risk profile that shows when someone is especially vulnerable.
Associate Professor Paul Wu, Distinguished Professor Kerrie Mengersen, and Yu Yi Yu from QUT’s School of Mathematical Sciences and Centre for Data Science led the project, alongside the Australian Institute of Sport, statisticians from UNSW, and potential end-users, including coaches and medical staff.
“With the rapid rise of wearable and other sensing technologies, the time is ripe for building next-generation models to make sense of complex data and patterns, and support anticipative management and prevention of subsequent injuries,” Professor Wu said.
The numbers show why this matters beyond elite sport. In 2023, Australians recorded 3.47 million sports injuries, with more than 66,000 serious enough to require hospital treatment.
The QUT model interprets changes in performance to flag elevated risk. In one AFL dataset, it explained injury occurrences correctly 77 per cent of the time, with 90 per cent specificity.
“Age emerged as the strongest factor influencing how an athlete might transition from a more susceptible to less susceptible state or vice versa, followed by context (for example, games carry higher risk than training), and the severity of the last injury,” Professor Wu said.
“Self-rated exertion and running speed also proved to be key indicators of injury risk.”
While the immediate applications are clear for pro athletes returning from injury, Wu said the benefits could eventually extend to community sport.
“We can run ‘what-if’ scenarios, such as adjusting training or match loads to see the potential impact on injury risk or estimate an athlete’s susceptibility right after a game or training session.”
The vision is straightforward: to empower both professionals and amateurs to train harder, recover smarter, and avoid preventable setbacks.
“Our vision is to give athletes, coaches and support staff, whether in elite sport or the community, tools that help them make sense of complex data, to allow them to train and compete at their best while managing the risk of subsequent injury,” Professor Wu said.
