When thinking about technology and sports, most would probably not see much opportunity to combine the two. Steve Ballmer would strongly disagree with this. He believes that there is incredible potential to apply AI to sports such as basketball. In every NBA game, there are six cameras above the court that have an unobstructed view of the whole game. Ballmer suggests that these cameras, paired with the right software, should be able to analyze each play in extreme detail. The system would know which player is which, where the ball is, what the score is, field goal percentages based on where a player is shooting from, and many more other analytical details. He even suggests that the software would be able to synthesize a player’s point of view from on the court, giving the fan the ability to see the game through their teams, favorite player. Ballmer being the smart businessman that he is has already created a software that can do these types of things and more and planned to have it enter the market in 2018.
The way sports games are broadcasted has evolved in recent decades. Television has had a monopoly on the way sports get broadcasted to viewers ever since it was created. However, our technology is now at a point where the internet is the primary mode of how we follow sporting events. This has caused the media and broadcasting industry to make major changes. Due to the high demand to see highlights quickly after the play or game has occurred, there will always be a media provider to post that video first. The television industry is adapting by trying to be the first ones to post this content to the internet.
The sports broadcasting industry can also benefit from the application of AI in their work. Software similar to what Ballmer mentioned earlier could help give commentators data in real time about many different aspects of a game. Software that could instantly send statistics to them would allow them to give more in-depth analysis about the game in which they are commentating, which would make the overall viewing experience more enjoyable
AI can also be used the benefit the coaches and players of any sport. One article suggests that athletes of sports such as tennis could improve their game by wearing a small device on their wrist that could pair with the software used in the cameras to help deliver data to the player about how he was playing. The main problem right now is developing this software to help the players but is something we should expect to see in the future because athletes are always striving to be the best in their sport through any means necessary.
Works Cited:
Beyond Moneyball: How AI is Transforming Sports
Steve Ballmer talking about AI in the NBA:
(18:45-26:50)
How AI can help improve sports performance
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AI and technology are also being used in soccer to help improve the game performance for players. A GPS monitoring system by VX sports is used on players in practice and games to track their distance covered, speed, accelerations, and number of sprints. This system is being implemented on a lot of professional teams and even some college soccer team, including the Loyola men’s soccer team. The system is a little GPS device that is worn attached to a small vest underneath the jersey. This is especially helpful for soccer players because the data can be used to track the workload of each player. With the data collected after a practice or a game, it can be used to prevent injuries by telling if a player’s workload was too high, or if a player is unfit. This creates a big advantage for the teams who use the GPS system. Every soccer team would benefit from this GPS technology, but the only problem is the price, this technology can cost a team thousands of dollars.
AI is something that could dramatically help improve sports. Many smart owners have already put groups in place to use technology to analyze their own team and opposing teams throughout its league. One great case of this is the MLB. Major League Baseball has been using Amazon Web Services since 2015. At first the league just stored its data on the service. Over the past few years however, teams started to use this data to analyze its team and other opposing teams. An example of using this new AI technology was the stolen base success probability. This prediction indicator takes tons of data points into account including a runner’s stolen base attempts, a pitcher’s pickoff rate and a catcher’s pop time (the time it takes for the ball to get from his glove to second base) to create a runner’s likely success rate of stealing a base. This is great for baseball because the data helps teams create a game plan for certain players and the indicator is visually stimulating for the viewers. Below is a clip of how the predictor worked last season. This probability indicator is part of the MLB’s development called Statcast AI powered by AWS. Statcast is behind all of these new developments with AI in the MLB. Another example of AI in the MLB is a pitch predictor. Right now, the MLB and Amazon are working on an indicator that could predict the next pitch thrown by a pitcher. This will predict the type of the pitch as well as its location. It will do this by evaluating the pitcher, batter, catcher and the situation in the game. If the MLB and Amazon get this predictor right enough, it could change the game. Teams will now know what type of pitch a specific pitcher is going to throw in certain situations. Statcast in the MLB is also widely used for smaller things such as projected distance of a home run, exit velocity of a ball hit and its launch angle. The use of AI is very beneficial for all sports, not just the MLB. The NFL and NBA are just two other leagues that use AI to improve its sport.
Link to Video: http://newsvideo.su/tech/video/268177
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