Picture this: You’re an elite athlete at the top of your game. You have a huge event coming up, say, the Olympics. You’re on a strict training regimen which culminates in your Olympic event. You head to the gym for a routine session nothing out of the ordinary. As you’re going through the motions of your session, *POP* a searing pain shoots through your knee and you immediately know something is very wrong. You see a doctor as quickly as you can and they confirm your worst fears. Diagnosis: ACL Tear Treatment: Surgery Recovery time: 8-12 months. There goes your Olympic dream. Absolutely heartbreaking.
This is truly a tale as old as time in the world of elite sports and is also one that the sports medicine field is looking to prevent through the use of big data and analytics. Most athletes are utilizing wearable devices or smart apparel during both training and on the field. These devices are capturing thousands of data points on a daily basis from steps to heart rate and everything in between. Combining the data from these devices as well as biometric data gathered from each athlete, athletic trainers and physical therapists are able to establish an athlete’s unique baseline and monitor any significant changes throughout the training cycle. This consistent monitoring and re-measuring allow trainers prevent any injuries that may be brought on by overuse or inconsistent training.
Now that you know why it’s important and how it’s being done, let’s look at some use cases.
The NBA is on the forefront of utilizing data from each athlete in order to *hopefully* prevent an injury. Each NBA player is monitored through wearables, sleep monitors, diet tracking and saliva samples to assess fatigue and predict performance. Prior to every game a report similar to the one below is printed by each team to determine what each player’s playing time should be. The results of this report are also used during the broadcast of the game to indicate to viewers why their favorite player may be on the bench tonight. The report for each game looks similar to the one below.
Not only is the NBA using data to fuel decisions about players, but it is also using it to enhance the viewing experience by allowing viewers a glimpse into the decision making process that goes into each game.
Next up is a company called Sparta Science. Sparta Science makes products used specifically to project performance potential and identify injury risks. The company offers a suite of machine learning software paired with force plate technology to assess and predict results for each athlete. Athletic trainers will take each individual athlete and walk them through a set of baseline scans on the force plate. The data produced from these scans is then ran through a ML model with over 2 million other scans to assess the athlete’s movements in 3 segments – jump, plank, balance. The model then suggests exercise recommendations for movement health improvement to hopefully prevent future injury.
With that small summary of what Sparta Science is doing, they have contracted with a ton of major league and D1 sports teams throughout the world simply demonstrating that teams are starting to think very proactively about athlete health and injury prevention rather than reactively after the athlete sustains an injury. I believe the adoption of these kinds of technologies will not only be the new standard for athletic trainers and the sports medicine industry in general but will also start to filter down to the average Joe. We’ve already seen some of that with the Whoop band that assesses your daily activity, sleep and diet and then provides your fatigue level in a sleek app.
We’ve heard approximately 1 million times about how much money Tom Brady spends on his health and wellness (it’s millions in case you don’t follow sports). I believe as we move forward and the adoption of data analytics becomes the standard, we will no longer be shocked that professional athletes are paying millions of dollars to keep their body in top notch condition. I think it will actually become surprising if an athlete is NOT using all of the new tech and data analytics to prevent injury and stay in the game longer. Fewer injuries thanks to personalized data analytics means that athletes could play longer if they so choose and it will be very interesting to see if this truly plays out.
I think it is very interesting to see that Sports Medicine is really buying into the data analytics movement and utilizing all kinds of new technology to help prevent injuries among athletes since typically medicine as an industry takes a while to catch up with the new thing. With that being said I am very excited to see more applications of injury prevention data and tech filter down to the average person who may not be actively participating in a sport but enjoys exercising 4-5 times a week. Obviously, I am alluding to selfish motivations for this as I am someone that very much knows the pain and frustration of an injury which could have easily been prevented if I was just a bit better informed…maybe.
All of this leaves me with the final question I will pose to you, dear blog audience.