Artificial intelligence solutions are being applied in nearly every possible space. Out of all these areas, companies are making interesting AI/ML applications that others would not even consider, like forecasting injuries in sports.
1. Forecasting injuries in sports
For example, in the sports industry, companies are utilizing AI solutions to help in forecasting potential health risks and injuries. In other words, the concept is similar to forecasting weather patterns where predictions are made on the data and information at hand.
Statistically speaking, in top soccer leagues alone, the average cost of player injuries amounts to $12.4 million for each team.
Zone7 is one of the companies working in achieving this goal of maintaining fitness, health, and safety amongst sports teams. A piece of technology like this truly is a game-changer considering the extent of injuries players suffer throughout their careers. Many have to stop playing due to the risks and dangers that come with certain kinds of injuries.
Keep reading to learn more about Zone7 and their AI-powered solution
2. ‘Predicting Injuries’ – is that even possible?
Zone7 does not ‘predict injuries’. We apply AI to understand how workload, biomechanics, and recovery affect ongoing risk and in certain cases suggest derisking strategies manifested in optimal workload bands, not rest.
One can’t predict injuries incidents, just like one cannot predict the exact moment it will rain in a specific street corner. But the right technology and scientific framework can provide a reliable and actionable forecast – quantifying the risk of incident for a well-defined time window.
3. How do you KNOW it works? For real?
On top of standard mathematical methods of validation when developing algorithms, we use two ways of testing to validate our algorithms: ‘retrospective and ‘prospective.
- Retrospective analysis is looking back at data, applying the algorithm to the data, and seeing which incidents would have been identified in time by the algorithm. In our case, we always do an ‘out of sample test’ which is to say the algorithms were NOT allowed to peek at the data before the test.
- Forecasting is looking into the future — analyzing athletes’ data in real-time and flashing alerts and concrete recommendations about impending injury. – this does guarantee prevention but is definitely an opportunity to intervene. We’ve tested the algorithm over many man-years of live, meticulously managed forecasting tests. As well as validating that our intervention is effective and leads to reduced incident rates”.
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