How do Zone7 validate injury risk detection?

Zone7 uses sophisticated technology - Artificial Intelligence and Machine Learning – to help ensure athletes can train towards peak performance with minimal risk of injury.  Tal Brown, Zone7 CEO, believes it is important to back this up with evidence. He sat down to answer some of the top questions asked about the company. 

1. "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. 2. How do you KNOW it works? For real? There are two ways to validate algorithms that forecast (and create an opportunity to prevent) incidents: ‘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 peak 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. Zone7 has both types of evidence – plenty of it. To see more, you can view the rest of this article here

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