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Data Analytics: Applications of Big Data in Sports Medicine

21Feb
Read Time: 3 minutes

Forget Brad Pitt and “Moneyball,” data analytics in sports have come a long way since then. Big data-based predictions are now making sports a different ball game… literally. At Wimbledon, IBM’s SlamTracker used around 39 million data points from historical data and live-game footage to predict which player would win – imagine that!

Sports medicine is only now beginning to look at the greater potential of big data and data analytics. Advanced real-time video capture and big data algorithms are helping to reduce injuries and alter training to keep athletes performing at the top of their game.  

Personalized and Optimized Health Regimens

Success in sports can come down to millimeters and milliseconds. A strong training regimen, apart from natural talent, has long been considered the backbone of success. Players often talk about the consistent hours they put into their training. But there are many factors that contribute to peaking at just the right time. 

In fact, how much sleep a player gets, what they eat, how these affect their time on the field, heartbeat, breathing rate, and stamina, can now be quantified. This vast amount of data can be analyzed by advanced analytical tools to create individual training profiles. 

The gains are big in more ways than one, since reducing the risk of injuries could mean saving millions of dollars.

Utilizing predictive analytics patterns to improve performance in pro sports is now a given. Now, high school and college sports are also actively looking for answers in Big data analytics.

Big Data in Sports: Biomechanics Analysis

Let’s go back to 2012 to see biomechanics analysis in action. Trainers working with Great Britain’s Olympic long jumping team knew that 3 variables affect a jump when a runner hits the board – speed, the force exerted and the takeoff angle. The first two factors were based on technique and athletes at that level already had it. The only variable that could be changed was the angle of take-off, which was never really given any attention until then. For two years, this is all they worked on. When the Olympics rolled around, the athlete not considered among the top 10 came away with the gold medal. Drilling down into the big data made all the difference in knowing what to focus on.

Sports biomechanics has everything to do with analyzing movements. An athlete can be monitored through motion capture analysis and pressure sensors to understand if there is any deviation from an optimal trajectory. For example, stride during running, stroke patterns during swimming, body position when lifting, the release of a javelin or a ball in a jump shot. Predictive analytics then comes in to answer the “what if” questions to suggest corrections for better results. 

Data Analytics Tools: Wearable Technology

Is the athlete’s heart rate higher at game-time compared to training? What about hydration levels? Wearable devices like heart rate monitors, GPS motion trackers, accelerometers that track strain and effort are among the many that are answering these questions. These devices use advanced embedded technology and cloud services and are now instrumental in reducing injuries, detecting psychological conditions like nerves in play, and much more. 

The problem with all this data is that it is very subtle. Without the right tools, there is no way to analyze such moment to moment monitoring. Advanced data analytics is providing this power to sports physiologists, doctors and coaches to come up with personalized strategies.

Soft tissue injuries are often the most common type of injury that cuts into an athlete’s sports time. Overexertion, dehydration and poor conditioning can be detrimental to an athlete’s performance and health. Technology that can track exertion and performance through physiological/biological monitoring is helping teams train smarter and prevent injuries. Florida State Football Team credits this technology with an 88% drop in their soft tissue injury rate. Wearable devices are now as important to an athlete as the designer sports shoes they choose. Data analytics not only helps with injury prevention but can also help speed up recovery time as well.

If “Moneyball” taught us anything, it is that merely having the data is not enough. The ability to ask the right questions is what makes all the difference. 

Leveraging Big Data Insights

Effective data analytics starts with reliable data storage options. Data lakes enable the storage of both structured and unstructured data, providing a flexible, scalable and cost-effective solution for businesses. When you choose a self-service data governance and data lake creation platform like Sertics, you can even integrate with leading data visualization tools such as Tableau and PowerBI to gather comprehensive insights from your analytics.

To discuss your big data project or to schedule a Sertics demo, reach out to 7T today. 


Reach out to our team today!

Shane Long

As President of 7T, Shane Long brings experience in mobility that pre-dates the term “smartphone” and the release of the first iPhone. His work has helped revolutionize the growth of mobility by bringing to market one of the first graphics processors used in mobile phones, technology that after being acquired by Qualcomm lived well into the 4th generation of smartphones, as well as helped pioneer the first GPS implementations in the segment. With a strong engineering and business background, Shane understands how the rise of mobility and Predictive Analytics is crucial to greater business strategies geared toward attaining competitive advantage, accelerating revenue, and realizing new efficiencies. As the leader of a B2B mobility solutions provider, he partners with business leaders including marketers and product developers to leverage enterprise mobile applications, big data and analytics, and mobile strategy.

Shane earned a B.S. at Texas A&M (whoop!) and studied mathematics as a graduate student at Southern Methodist University.

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