Engineers at Brigham Young University (BYU) are developing a new artificial technology that could significantly reduce the cost and time of game analysis for Super Bowl-bound teams(including all NFL teams). This would also enhance game strategy by leveraging big data.
Researchers at BYU, including Professor D.J Lee, Ph.D. candidates Shad Torrie and Andrew Sumsion, and Master’s student Jacob Newman are automating the laborious task of manually evaluating and annotating game footage. The researchers employed computer vision and deep learning to develop an algorithm that can reliably identify players and know their tactical approach to a game. This operation typically requires the assistance of numerous video assistants.
According to Lee, a computer and electrical engineering professor, the researchers had set up a meeting with BYU football to understudy their game processes.
New AI accurate for player detection
Even though the research is still in its early stages, the team has already achieved greater than 90% accuracy with its algorithm for player labeling and detection, along with 85% accuracy for identifying formations. The researchers believe the AI will help to eliminate the need for the current NFL’s time-consuming and tedious manual annotation and video analysis process.
Lee and Newman started by watching actual game footage that BYU’s football team had provided. On evaluating it, they quickly discovered they required different angles to train their algorithm effectively. They then manually annotated 1,000 photos and videos from Madden 2020. The copy of this game shows the field from above and behind the offense.
According to Lee, the computer can accurately recognize formations 99.5% of the time when the player’s location and labeling information is precise. One of the most challenging formations to identify was the I Formation, which has the center, the quarterback, the fullback, and the running back lined up one in front of the other.
Use in other sports
Lee and Newman also claimed that AI technology is useful in other sports. For instance, in baseball, it may map out player locations on the field and pinpoint recurring trends to help teams improve their defense against particular batters. Alternatively, it might be used to locate soccer players to develop more successful formations.
“Once you have this data, there will be a lot more you can do with it; you can take it to the next level. “
“Big data can help us know the strategies of this team or the tendencies of that coach. It could help you know if they will likely go for it on 4th Down and 2 or if they will punt. The idea of using AI for sports is cool, and if we can give them even 1% of an advantage, it will be worth it.”
Professor D.J Lee, Researcher at Brigham Young University
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