Can We Really Predict Injury?
I want to take you all back a couple of years. I was an up and coming sports scientist for a National Rugby League Club in Australia. It was my dream job, with my one goal being to ensure the team performed to the best of their ability. This included eradicating the long line of injuries that had occurred over a number of years. One instance clearly stands out in my mind. I had an athlete returning from a long stint on the sideline due to an ACL reconstruction. Returning to training saw him nowhere near his best and GPS data only highlighted the fact he was struggling. As his training continued, the data he returned only got worse and 2 months into pre season training, saw him snap his kneecap in half. Did I actually predict his injury? I mean, I knew something was going to happen, the data told me that much, but did I know exactly how the injury was going to occur? Lets present the facts below.
What does the GPS data tell us?
These days, you would be hard pressed to find a high performance sports team without a Global Positioning System (GPS). GPS data is the most accurate form of data collected on what athletes are actually doing out on the field. As sports scientists we gain a greater insight into distances, speeds, heart rates, impacts and work rate. These markers can be used to determine what is considered normal for an athlete. GPS data is our greatest asset in understanding what athletes are actually doing and how we can plan for the future.
Not all injuries are the same, so how do we predict them?
I am yet to come across two injuries that are exactly the same and happen in the same manner. I am sure they exist, they are just incredibly rare. Therefore how can we predict them if they are yet to have occurred. What causes one hamstring strain could be completely different to the cause of another hamstring strain, despite the fact they both come under the same injury category. We would require thousands upon thousands of data entries to even begin to predict injuries and this is just to begin predictions on one injury type. Surely by now you have noticed the big dilemma.
It is all about data collection and comparison
The data we collect today allows us to understand the importance of information and how we use it to aid in our future decision making. As we collect data, patterns form, we obtain a greater picture of athletes and can assess what is and is not normal. The challenge for us right now is to ensure data is clean and there is a common standard for processing it. This is the information that will one day go beyond correlation, leading into predictive analytics.
It is all about risk assessment and management.
If the injury didn’t actually happen, how do we know we predicted it and in turn how do we know we prevented it from occurring? If we are looking towards the future to predict injuries, should we not be looking towards the data we currently collect. Teams and sports scientists need to focus on assessing the risks and managing them as they present rather than spending time predicting them. This information should be shared with strength and conditioning coaches, physiotherapists, medical staff and head coaches to develop training programs based off facts rather than feeling. When unexpected data is returned programs need to be evaluated to prevent further damage.
So did I really predict the injury? Well to this day I still believe I did to some extent. Yes, I knew something was going to happen, the data told me that much. But did I know he was going to break his knee cap in half, definitely not. A much wiser me suggests a wider data pool would be required to have actually predicted this injury. That is not to say that we can’t significantly decrease the impact injuries have on high performance sporting teams. This is what sports scientists should be working towards. And who knows what the future holds in regards to injuries and predictive analytics.
Naomi Wallis
Product Manager
Naomi speaks all things functional movement. She loves it so much, she adopted it into her daily fitness routine. To say sport was ingrained in Naomi is an understatement.
In fact, she loved it so much, she went on to study sports science at university and has worked for some of the best NRL teams in the country.
Her world is revolved around the sport and she brings this enthusiasm to the table every single day.
