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Sports IQ to AI. How AI is knocking it out of park in the sporting industry.
Artificial Intelligence (AI) is being incorporated in nearly every professional sport, both on and off the field. Though there may be some challenges and concerns, it’s undeniable that AI integration in the sporting industry has its clear advantages and will be a built-in strategy into the future.
- AI assists on the field
- How AI is improving the game off the field
- Future of AI in sports
- Closing thoughts
In just 1 week, NFL fans all across the nation will tune in to watch the return of football on prime time TV. Good ol’ American football, the game of inches, grit, and AI?
Throughout history, the focus on sports often remained on the players and their performance on the field. Nowadays, player performance goes beyond their natural talent and abilities and often is accompanied by many different factors (on and off the field) including the use of performance data. Whether it’s the Olympics or the MLB playoffs next month, technological advances continue to have a great impact on the lives of athletes, spectators, fans, and event organizers. In this article, we’ll go over several ways AI has impacted the sporting industry and provide some examples for each sport.
AI assists on the field
The summer olympics in Tokyo, Japan was a great showcase of AI integration in sports. Before even hitting the fields and events, Toyota provided electric autonomous vehicles to transport hundreds of athletes around the Olympic village. Also, with the Olympics being a global event, AI-backed real-time translation systems were installed on smartphones or other compatible devices allowing for people who speak different languages to understand each other and instructions. Sports like swimming, gymnastics, and beach volleyball use Omega’s timekeeper which incorporates computer vision and motion sensors to track players’ movements in real-time which is directly analyzed into the competition. Other AI integrations include athlete data tracking tools, coach’s real-time feedback, algorithms to predict injuries, cloud-based broadcasting, robotic assistants, and 5G.
It’s no surprise that the NFL and their billion-dollar franchises have adopted the use of AI in order to assess and evaluate players as a tool to recruit and draft talent while evaluating the potential for injuries. From biometrics and personality assessments to AI, data analytics, and computer vision, general managers are using the latest tools to reach their calculated decisions.
AI and machine learning allow for some of the most innovative technologies in gathering basketball data and analysis. Companies such as Noah Basketball who track shots and produce data on those shots such as arc and trajectory, Stats who was the first company to install camera systems in NBA arenas to track the basketball and player movements and body positions, and ShotTracker that gathers data in real-time, provide a high level of analysis to assist players, coaches, and teams to be better prepared to succeed.
It was recently announced that the English Premier League champion, Liverpool has partnered with DeepMind to explore the use of AI in soccer. With the amount of available data growing in soccer with the use of sensors, GPS trackers, and computer vision algorithms to track the movement of players and the ball, AI offers a way to spot patterns to help both coaches and players make better decisions.
Better decisions… (Source: Giphy)
Fujitsu developed AI and 3D sensor technology to assist judges with their scoring of gymnastic performances. The Judging Support System utilizes AI and 3D sensors to capture each gymnast’s movement before analyzing it as numerical data. The Gymnastic Judging Support System which was jointly developed with the International Gymnastics Federation (FIG) was awarded the highest prize, “Minister of Internal Affairs and Communications Award” in 2019.
IBM, the Official Cloud and AI partner of the US Open, announced the world’s first AI-powered tennis player rankings. The IBM Power Rankings will focus on the player’s most recent history and analyze performance stats and media commentary to measure player momentum in real time. IBM Watson will produce a series of predictive Match Insights to help focus attention on the most intriguing matchups throughout the tournament and identify potential upsets and players with significant momentum.
AI-powered cricket bats called power bats, are used to to collect crucial insights on a batsman. Partnered with Microsoft, Spektacom, uses a mini sticker sensor on a cricket bat to collect data on the quality, speed, twist, and swing of the bat to help professionals improve their game. Snickometer, Hawk-Eye, Drone Cameras are also examples of modern day technologies used in cricket.
How AI is improving the game off the field
Machine learning algorithms can allow for broadcasting companies to pinpoint game highlights by taking players’ actions and fans’ emotional response into consideration. These insights can help advertisers to choose the proper time for commercials to captivate their audience. AI can also help improve marketing efforts with advanced targeting of fans using demographics, media consumption behaviors, personal interests, shopping habits, etc.
By leveraging Natural Language Processing (NLP), AI has already begun changing the scope of journalism. As journalism becomes automated (check out our blog on AI in Media), AI is making use of sports data to create readable information for different sports events. AI platforms can also provide information and stats to commentators to help with better live commentary, provide subtitles for live events according to the language of the location, and provide best camera angles during matches for highlights and replays for fans.
Similarly, as Oakland A’s general manager, Billy Beane, was able to use statistical data to build record breaking teams with a limited budget, AI can be used to predict performance of potential recruits. Organizations can use AI to track performances of players and analyze whether to invest in a potential recruit. Using more complex data and metrics than open stats (hits, runs, passes, goals, etc.), big data and AI in sports management can help streamline the underlying measurements for success.
Future of AI in sports
What will the future of AI in sports look like? Will robots start taking over as players, coaches, or referees? Maybe, but I think we still have a while before that type of transition. We will probably see sports in a form of virtual or augmented reality before that. One thing is for sure, AI is going to increase the competitive nature of sports both on and off the field. Over time, data will continue to swell and predictions will become more accurate affecting players, coaches, advertisers, sports companies, franchise owners and even the fans. The trend of implementing AI in sports will become a must in order to gain a competitive edge over rivals.
They say “champions are made in the off season” and that “practice makes perfect,” but is that enough? The level of competition in sports is greater than ever before. Leveraging performance data and statistics seem to be the new competitive advantage and AI is the tool that will provide those capabilities and set you up for success.
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