Cracking the Code: Can Advanced Analytics Predict NFL Injuries?

The roar of the crowd, the bone-jarring hits, the electrifying plays – these are the hallmarks of the NFL. But behind the spectacle lies a persistent concern: player safety. In a league where careers can be cut short in an instant, teams are increasingly turning to advanced analytics in an attempt to predict and prevent injuries. Can they crack the code and keep their stars on the field?

The Data Deluge: A New Era of Player Analysis

The NFL is awash in data. From wearable sensors tracking every movement to sophisticated video analysis, teams have access to an unprecedented level of information about their players. This data deluge is fueling a revolution in how teams approach player health and safety. The NFL has initiated a “digital athlete” partnership with Amazon’s AWS division to help deploy artificial intelligence and machine learning to enhance player health and safety. The technology initiative studies players’ actions during training, practice, and games. The partnership between the NFL and Amazon AWS will be adopted across all 32 NFL clubs, in an effort to offer personalized injury prevention insights and improvements in player safety.

“When you can integrate and aggregate data across all 32 [teams] for all 53 [players], you have more power in the data that you are generating to model,” said Jennifer Langton, NFL Player Health & Safety Innovation Advisor.

Identifying Risk Factors: More Than Just Bad Luck

For years, injuries were often chalked up to bad luck or the inherent risks of a violent sport. Now, teams are using data to identify specific risk factors that can contribute to injuries. These factors range from player workload and fatigue to biomechanics and even field conditions.

Workload Management: Overuse injuries are a common problem in the NFL. Teams are using GPS player tracking, like RFID chips in player’s equipment, to monitor players’ physical exertion and workload during practices and games. This information assists in implementing load management strategies to reduce the risk of injuries and optimize player performance over the course of a season.
Biomechanical Analysis: Analyzing how players move can reveal potential weaknesses or imbalances that make them more susceptible to injury.
Field Conditions: The debate over the safety of artificial turf versus natural grass continues. Some studies suggest a higher risk of certain injuries on artificial surfaces, and teams are taking this into account when making training and game-day decisions.

Predictive Models: Glimpsing into the Future

The ultimate goal is to use these risk factors to build predictive models that can forecast the likelihood of injuries. These models use machine learning algorithms to analyze vast amounts of data and identify patterns that might not be apparent to the human eye.

One study utilized machine learning (ML) models to investigate the effectiveness of using multifactorial injury conditions to predict lower-limb injuries in NFL players. AdaBoost yielded the highest performance with an accuracy of 90.91%, precision of 89.45%, and recall of 89.45%. A model with such high accuracy, consistent prediction, and large improvement in recall could help predict certain conditions that correlate with the likelihood of specific lower-limb injuries and allow NFL teams to take preventative measures when those conditions do occur.

The NFL is also using data collected from sensors in mouthguards and shoulder pads to collect head kinematic data, including impact speed, direction, force, location, and severity, providing the league with more information about what the head experiences than anything else that can be placed on a player’s body or in his equipment.

The Digital Athlete: A Holistic Approach

The NFL has partnered with Amazon Web Services (AWS) to create the “Digital Athlete,” a comprehensive platform that uses AI and machine learning to provide a complete view of an NFL player’s experience. The Digital Athlete provides a complete view of an NFL player’s experience, taking video and data from training, practice, and in-game action and using AWS technology to run millions of simulations of specific in-game scenarios to tell teams which players are at the highest risk of injury. Coaches and training staff use that information to develop individualized injury prevention, training, and recovery regimens. Starting this season, all 32 clubs have access to the Digital Athlete team portal, which includes daily training volume and injury risk information for their team, as well as league-wide trends and benchmarks.

Real-World Impact: Are Injuries Actually Decreasing?

While it’s still early days, there are signs that advanced analytics are making a difference. The NFL’s data-driven approach to reducing injuries continues to show progress through the help of AI, AWS, and the Digital Athlete program. For the first time ever, the NFL saw a reduction in leg injuries in consecutive summers.

The Human Element: Data Isn’t Everything

It’s important to remember that data is just one piece of the puzzle. The expertise of doctors, trainers, and coaches remains crucial in making informed decisions about player health.

The Future of Injury Prediction: A Continuous Evolution

The field of injury prediction is constantly evolving. As data collection methods become more sophisticated and analytical techniques improve, teams will gain an even deeper understanding of the factors that contribute to injuries. The investment in data capture is paying dividends and, Langton noted, will expand in the future to full-body limb and joint tracking. It has been a challenge to get the necessary precision for actionable insights, particularly with the high rate of occlusion in a contact sport like football. “With the new AWS deal, that's the focus, to build that pose estimation so that we can get to that true Digital Athlete on quantifying body movement,” said Langton.

The ultimate goal is not just to predict injuries but to prevent them altogether, ensuring that players can enjoy long and healthy careers. As the NFL continues to embrace advanced analytics, the dream of cracking the code on injuries may be closer than ever before.