The art of sport has evolved a lot over the years to become what it is today. It has become a significant source of entertainment for many around the world and a massive business venture, generating billions in revenue. Many sports teams rely on success in their campaign to earn their money and will use any method to improve their training to win.
To improve performance, coaches and players implement outside methods into their game. Artificial Intelligence allows coaches and players to see details in their sport that are not quickly apparent, such as statistics. AI can also help enforce the rules within a sport, providing less human error when referees make a controversial decision.
Here are five sports that have implemented AI into their gameplay:
Known as “the beautiful game,” football has been the most popular sport in the world and has evolved dramatically since the first professional club was established in 1857. As the improvement of football continues, AI is making its way into the industry, altering the sport as we know it.
Getafe, a football club in Spain, has recently implemented Zone7 into their seasons. Zone7 is an AI-driven company that takes gameday, medical, and training data points and provides assessments that prevent injuries before they occur.
Getafe’s use of Zone7 has paid off tremendously, with the club reporting:
- 70% reduction in injuries per 1000 hours
- 65% reduction in match injuries
- 65% reduction in days lost
As Zone7 makes its way into football, more clubs have gravitated toward these AI capabilities, like Rangers and various MLS sides. Zone7 is influential by taking out the injury aspect of the game. Being able to predict injuries can affect the game’s tactics and the player’s health on the pitch in a positive way.
Among the more brutal sports is rugby. It is sometimes difficult to discern what happens during the game, as the players are supposed to charge into each other, creating large “dogpiles.” To analyze and prevent confusion for the referees, highly complex AI video analysis tools to help with game calls.
Toshiba has introduced a new video and audio analysis software that tracks the game in real-time. Using Machine Learning capabilities, the software tracks the players and the ball, even calling whether a “scrum,” “pass,” and “tackle” has occurred.
Additionally, audio analysis software tracks when a whistle is blown by looking into the audio frequencies of the recorded game. This is useful to coaches and players that learn by watching video playbacks.
Researchers at the Queensland University of Technology in Australia have developed a sports AI system that could change the game of tennis. Using the Hawk-Eye Ball Tracking System, the researchers recorded data points on tennis shots provided by professional players from Rafael Nadal to Roger Federer. The data from these shots were used in their AI system and accurately predicted how a player’s shot would successfully play out.
Using data points like the trajectory of the ball and player movements, this software predicted whether a shot would be returned or win the round. As well, the software was able to pinpoint the potential location of a returned ball.
Data learning technology benefits players in their training by providing a “bird’s eye view” of the match and predicting the outcomes before they happen.
In fast-paced sports like basketball, AI has proven beneficial in gathering data sets and numbers that may be difficult for humans to grasp. NBA teams have implemented optical tracking technology, like SportVU, to track the finer details during a game to better their playing style.
Softwares like SportVU provide pattern recognition capabilities to predict how the game is played. SportVU can track a player’s movement 25 times a second. This AI software has also provided many values on the most detailed aspects of basketball, like the arc of players’ shots. The numbers provided by AI benefit coaches and players by improving aspects of their game that would not be seen with the naked eye.
A bad call by an umpire in baseball can either make or break a game’s final result. Major League Baseball (MLB) has been experimenting with AI to improve the game adored worldwide.
In 2018, umpires in the MLB had missed an average of 14 ball-strike calls a game. To combat this inaccuracy, robot umpires have been tested in baseball. “TrackMan” is designed to sit above home pate and accurately read pitches using a 3D radar doppler dish. This robotic umpire will also analyze the players’ size and create a strike zone based on their height. This combats inaccuracy by providing an “umpire” with perfect reflexes to see the ball clearly and unbiased refereeing to baseball.