How A.I. could help sports teams predict and prevent injuries

Sports have always been a human drama, with loud coaches and outstanding players making crucial choices that determine the fate of the team, says  Toni Witt in his article for AccelerationEconomy.com from 2023. With the development of artificial intelligence (AI), machine learning (ML), and data science, sports teams can now predict and prevent injuries by analyzing vast amounts of biometric data collected from sensors placed directly on athletes. Traditionally, these decisions are based on the coach's intuition and experience.

To forecast up to 80% of probable injuries, ML models like decision trees may examine data such as total distance run, distance runs faster than 5.5 meters per second, and the amount of high-intensity accelerations and decelerations. The National Football League has reduced injuries by 26% year over year by using injury prediction data to modify players' training routines and playing time.

While some coaches are cautious to use forecasts in their decision-making, there are limitations to employing data science to anticipate injuries in sports. However, certain sports benefit more from the data-centric strategy than others.

The Special Olympics Abu Dhabi deployed artificial intelligence (AI) technology to anticipate potential health problems, enabling medical staff to provide prompt care as needed. This highlights how significant data and machine learning (ML) have become in sports, how they may help players live healthier lives, and how they can provide competitive teams an advantage.

The predictive capability of ML may go beyond sports to enhance consumer health and performance in other spheres including business, the arts, and the military. In the AI/Hyperautomation channel, we will continue to investigate and share insights on these issues.