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Having previously been in the sports tech industry for several years with my company neo360, I’ve witnessed the evolution of AI in sports. Back in 2017, there were only one or two companies starting to use machine learning for sports training. It’s exciting to see how far things have come in the past seven years.
The NFL’s “Digital Athlete” Initiative
Injuries have always been a critical aspect of football. To address this, the NFL has launched the “Digital Athlete” initiative. This initiative uses AI and machine learning to study players’ movements with the aim of preventing injuries. The technology creates a precise picture of each player’s experience in training, practice, and games. The technology enables teams to understand what specific needs players have in terms of staying healthy, recovering quickly, and optimizing performance.
Data Collection and Injury Prediction
The NFL collects a vast amount of data to predict injuries. One example is the use of sensors in shoulder pads, which capture the player’s real-time location, speed, acceleration, and distance every time a player is on the field. Another method of data collection is through a mouthguard that records the frequency and intensity of head impact contact. The most data, however, is retrieved through game footage. With sophisticated technology, the NFL can automate in real time, synchronizing all data points and running millions of simulations about an event in the game. This allows for a better understanding of when and how injuries happen.
AI in Other Sports
AI is not just transforming football but is also making significant strides in other sports. For instance, AI applications in sports such as basketball, baseball, and cricket are becoming increasingly common. AI is used in various ways, from enhancing fan engagement through chatbots to improving player performance with personalized training and diet plans. AI is also used in scouting and recruitment, match predictions, ticketing, and even automated sports journalism.
Smart wearables, computer vision, and VR have revolutionized training practices for sports teams. With real-time monitoring and identification capabilities, coaches are leveraging these technologies to evaluate the fitness of each player and determine training plans based on that.
The Future of AI in Sports
The future of AI in sports promises to elevate player performance to new heights. Advanced AI analytics will delve deep into player metrics, offering insights into physical condition, injury prevention, and strategic decision-making. This data-driven approach aims to optimize training regimens, enabling athletes to reach peak performance levels.
Generative AI could unlock activities for lower-league, recreational, and youth sport that were previously impossible given a lack of resources. The integration of generative AI into fan engagement is poised to become even more immersive. Future AI systems could create hyper-personalized virtual experiences, such as AI-generated virtual fan meetups, exclusive virtual locker room tours, or even personalized AI-generated commentary tailored to individual fan preferences.
If you or your organization would like to explore how AI can enhance productivity, please visit my website at DavidBorish.com. You can also schedule a free 15-minute call by clicking here
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