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Engineers' AI Tech Could Change Game Prep for Super Bowl Teams

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BYU's Shad Torrie, Professor D.J. Lee, and Andrew Sumsion

Algorithm team members Shad Torrie (left), Professor D.J. Lee (center), and student Andrew Sumsion sit in the press box at LaVell Edwards Stadium.

Credit: Nate Edwards / BYU

Artificial intelligence technology being developed by engineers at Brigham Young University could significantly cut down on the time and cost that goes into film study for the Super Bowl-bound Philadelphia Eagles and Kansas City Chiefs, and other football teams, while enhancing game strategy by harnessing the power of big data.

The researchers are using deep learning and computer vision to automate the time-consuming process of analyzing and annotating game footage manually. They've created an algorithm that can consistently locate and label players from game film and determine the formation of the offensive team.

While still early in the research, the team has already obtained better than 90% accuracy on player detection and labeling with their algorithm, along with 85% accuracy on determining formations. They believe the technology could eventually eliminate the need for the inefficient and tedious practice of manual annotation and analysis of recorded video used by NFL and college teams.

From Brigham Young University
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