Automated machine learning (AutoML) is emerging as one of the technology in the field of sports for analyzing the athlete's and organizer's data. After, the digital disruption sports industry becomes an important part of a country's social and economic health. People consider watching sports as an entertainment factor to relax from daily hustles. Rapidly increased growth in media has changed the dynamics of sports publications, casting, and live telecasts. The time during the sport flews at a pace, where it is hard for the opponent team to master that, coaches can't analyze their individual player’s performance during a play based on throw, swing, or shot and viewers can't enjoy the joy in watching it, especially in sports like basketball, badminton, swimming, wrestling, gymnastics, football, etc.
Measuring and analyzing the athlete's performance, ticketing, player maintenance, social brand image, and fan engagement, were key pain points in commercial sports for a better understanding of their players and trends in the market. Automated machine learning can drive better insights and help commercial sports in making quality decisions at the right time.
A brief history of Sports Analytics – AutoML Importance
Today every major professional sports team has an internal department to perform analytics. The popularity of data-driven decision-making in sports has trickled down to the fans, which are consuming more analytical content than ever. Now there are few businesses that entirely have the analysis of sports statistics and how to relate it to the prediction of a player's performance. The benefits of sports analytics provide full coverage of the performance and physical capabilities of a player or a team. This added advantage to commercial sports. Leveraging AutoML decoding sports analytics by influencing the way distributors, broadcasters, and publishers use the game room.
Sports Analytics owns New Room for AutoML
Automated machine learning allows organizers to build the best-in-class machine learning and deep learning models to analyze the data at a rapid speed with the utmost accuracy. Discover the top two of the AutoML benefits below:
1. AutoML Tables
The machine learning model powered by cloud low-latency serving infrastructure now helps in getting more accurate results with the use of the best algorithm with the accurate parameters to attain the best results possible. For instance, the speed, precision, and scale of AutoML tables allowed Fox Sports to predict the fall of wickets live while broadcasting.
2. Automated Sports Journalism
AI-powered and ML-driven marketing and broadcasting networks now shaping the new era of sports journalism. The auto-generated reports predicted insights, and live interacting state-of-art technologies are now fueling journalism like never. With sports analytical data, AI systems are developing auto-generated articles, PR copies, and more.
Now journalists are covering stories that earn with less manual effort. However, automated journalism is exploring the breadth and depth of current applications across various industries.
The AutoML applications and benefits are still in the “Pilot” stage, and these are affecting nearly every major professional sport. Apart from AutoML, AI applications like smart ticketing, automated video highlights, AI-assistive coaches, computer vision referee, and Wearable AI tech in different sports is also boosting sports analytics in the field of commercial and professional sports.
The continuous effort and scope of development of these technologies will help beyond tracking analytics insights to improve athletes' performance goals. More personalized experiences and more helpful automated interactions can increase the loyalty and engagement of a sport. AutoML definition in sports analytics has different applications that we continue to monitor with the evolution of tech and trends in the industry. And in this article, we tried to interpret a few applications of machine learning that demonstrate the future of sports analytics.
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