Ok … let’s unpack this nature.com/articles/d4158…

The punchline: Despite the claims -- and my desire as well -- nobody is predicting & preventing sports injuries with machine learning/AI. (1/6)
What are they actually doing? They're surveilling athletes 24/7, collecting truckloads of highly intimate and personal information, and calculating ‘workloads’ by way of questionable methods link.springer.com/article/10.100… @francoimpell (2/6)
Methods early proponents (cited by Rossi) are now walking back from ... "player workloads are merely a reference metric rather than a causal prognostic factor and they will never be able to predict injury with accuracy" ✌️@Billy_Hulin
researchgate.net/publication/35… (3/6)
Truest line in nature.com/articles/d4158…?

"There’s a gap between how much data we’ve been capturing and what’s actually been done with it... We’re trying to fill that gap using machine learning.” (4/6)
I’d love someone to show me a single article that uses machine learning/AI to PREDICT and PREVENT sports injuries. This is an aspiration -- but we're currently a long way from it (5/6)
This is why our projects led by @JuliaPowles @uwanews with @Science_Academy @theAIS & more are so crucial.

Let's call the game: boundless data capture is not it. We need evidence-based, mechanistic, scientifically rigorous approaches to the complexities of injury & health (6/6)

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