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Featured Blog: Injuries - Predicting The Unpredictable

Thu 26th May 2016 | IT & Technology

Stephen Smith, CEO at Kitman Labs looks at the Truth About Injury Prediction

Injury prediction feels like such a dirty word these days. It’s become somewhat of a stigma in this industry because many people have been beating a drum about how they are doing it or going to do it.

We, like many people within the industry do not believe that today there is a solution to predict injury nor do we believe that there will be one available in the near future.

I am not saying we cannot make a huge impact in reducing the prevalence and impact of injuries but as far as prediction goes, it is more complicated than a younger version of me once hoped for. 

When I first founded Kitman Labs and was in the early days of my research around this topic I believed that we would find all of the answers to this and solve a huge problem in sport.

My thoughts on the latter part of that statement have not changed and I have seen the evidence that we are solving a huge problem day to day with the teams that we are privileged to work with. However, the realisation that prediction of injuries is not as straightforward as I initially hoped came after much work and data collection in this space.

Today the focus must be on risk management and risk assessment so that we can pave the way to build robust models that may lead to prediction in the future.

One of the biggest issues we currently have within this industry is that we are trying to provide a simple solution to a complex problem. Injuries are rarely caused by one specific risk factor or problem.

The realisation that humans are complex and that human response and human failure is just as complex and involves the degradation of multiple factors must not be overlooked.

As much as we may want there to be a simple and straightforward answer and solution there needs to be a level of complexity that factors in the uniqueness of humankind.

I was recently at a conference where I heard a practitioner present and discuss the fact he predicted 99 injuries the previous year with a team saving them many millions of dollars.

10 years ago I would have thought “wow, that is amazing”, I need to be able to leverage this and see how they are doing it. Today, I ask a very different question based on the learning and education I have been provided by the other fantastic sport and data science professionals I work with everyday.

The first thing that popped into my mind that day was, if you predicted them, how do you know? If they didn’t happen, how do you know they would have?

It seems simple but honestly how do we know prediction works, it relies on an event to actually happen and for us to showcase that we knew about it beforehand.

Read Stephen’s full blog on www.kitmanlabs.com 

Reuters / Darren Staples

Posted by: Aaron Gourley 

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