With the upcoming NFL draft, the stakes are high for the league's billion-dollar franchises. Few events represent greater opportunities than the annual talent assessment undertaken by professional football teams. In a highly competitive league with fixed salary caps, the selection of new talent can make or break football operations. If you make the right choices, your team's fortunes can sky-rocket while personnel mistakes consign your team to below-average performance. In this type of situation, it is little surprise that teams are deploying the latest technologies as part of their skills assessments, talent recruitment, and evaluation of injury proneness.

Intel today revealed that its 3D Athlete Tracking (3DAT) technology is being employed by Exos, a firm that focuses on human performance conditioning, to help train professional athletes aspiring to join the National Football League (NFL) and other organizations. Intel's 3DAT technology captures skeletal data when an athlete is sprinting, using a video camera running at 60 frames per second. That data is then analyzed using Intel Deep Learning Boost AI capabilities that have been built into the latest generation of Intel Xeon Scalable processors Intel has deployed in a cloud it manages. The goal is to make it simpler for coaches and athletes to understand how different types of skeletal structures may give one athlete an edge over another, said Ashton Eaton, two-time Olympic gold medalist in the decathlon and a product development engineer in Intel's Olympic Technology Group. "We don't know why people won or lost," Eaton said. "There are a lot of unknowns."

Spotting the next star athlete has always been as much art as science, but artificial intelligence of the sort that's transforming everything from business to healthcare is starting to muscle in on professional athletics too. Computer vision, machine learning and other forms of AI use algorithms to analyze player performance statistics, game videos, and data from various sensors to identify talent that coaches and scouts might otherwise miss. And since the algorithms comb through data far faster than humans can, they give teams in-depth information on more players than previously possible. Professional baseball, basketball and hockey are among the sports now using AI to supplement traditional coaching and scouting. Baseball scouts in particular have long used statistics to evaluate players.

The NFL is joining Major League Baseball as an AWS customer, announcing a deal today to provide real-time statistics running on AWS. The tool is part of the NFL's Next Gen Stats program, which will take advantage of AWS machine learning and data analytics tools to enhance its current offering. MLB has had a similar deal in place with its StatCast tool. The NFL uses RFID tags in player equipment and the ball to capture real-time location, speed, and acceleration data. Much like the MLB product, this data can be used to heighten the NFL broadcast experience by showing viewers a unique data-driven view of the play on the field.