How AI is improving the Sports industry!

Source: imacimi

Playing different sports such as Cricket, Volleyball, Badminton, Soccer, etc had always been part of my life in some or the other way. It gives me a boost in my work and increases my cognitive abilities to the next level. Initially, we used to play or watch play athletes on television in a mundane way, now the era has completely changed!

I have literally seen different kinds of statistics and metrics coming into the picture in different sports and as years pass-through, so are the advancements in these technologies. In the past few years AI techniques such as predictions, computer vision, etc, and also technologies like Virtual Reality(VR) and Augmented Reality(AR) are been used extensively and improving the output in different forms of an athlete.

The sports industry is increasingly adopting various AI tools and technologies to enhance performance analysis, player monitoring, and strategic decision-making. Let’s explore some of these AI tools and their functionalities:

Sports Analytics Platforms:

Source: Soccerscene

• Examples: Catapult Sports, Stats Perform, Second Spectrum
• Functionality: These platforms utilize AI algorithms to analyze vast amounts of data collected from sensors, cameras, and other tracking devices. They provide valuable insights into player performance, team strategies, and game patterns. They enable coaches and analysts to make data-driven decisions, optimize training programs, and gain a competitive advantage.

Athlete Monitoring Systems:

Source: Adam Virgile Sports Science

• Examples: Zebra Technologies, Kitman Labs, PlayerMaker
• Functionality: These systems use AI to monitor athletes’ biometric data, movement mechanics, and workload. They track parameters like heart rate, speed, acceleration, and distance covered during training and matches. AI algorithms analyze this data to identify patterns, optimize training loads, prevent injuries, and monitor an athlete’s overall well-being.

Computer Vision for Performance Analysis:

Source: Murray Hill Tennis & Fitness

• Examples: ChyronHego, Playsight, Sportlogiq
• Functionality: Computer vision-based AI tools analyze video footage of sports events to extract valuable information. They can track player movements, identify key events like goals or shots, and provide detailed statistics. Coaches and analysts can use this information to assess player performance, identify strengths and weaknesses, and devise game strategies.

Virtual Reality (VR) and Augmented Reality (AR) Training:

Source: Engadget

• Examples: STRIVR, Rezzil, Sense Arena
• Functionality: VR and AR technologies offer immersive training experiences for athletes. They can simulate game scenarios, provide virtual environments for practice, and allow athletes to improve their decision-making skills. AI algorithms can enhance these simulations by adapting to the athlete’s behavior, providing real-time feedback, and customizing training programs based on individual performance.

Sports Prediction and Betting:

Source: sportico

• Examples: Sportradar, IBM Watson, Stratagem
• Functionality: AI-powered prediction tools analyze historical and real-time sports data to forecast game outcomes, player performances, and betting probabilities. These tools use machine learning algorithms to detect patterns, consider various factors, and generate accurate predictions. They are used by sports analysts, betting companies, and fantasy sports platforms to provide insights and assist in decision-making.

Automated Video Highlights Generation:

Source: Mt. Airy News

• Examples: WSC Sports, Keemotion, Pixellot
• Functionality: AI-powered video editing tools automatically analyze sports footage and create highlights packages. Using computer vision and machine learning, these tools can identify key moments, goals, and exciting plays. They enable sports broadcasters, media outlets, and teams to generate engaging content quickly and efficiently, enhancing fan engagement.

These AI tools are just a glimpse of the technologies being employed in the sports industry. The applications of AI in sports continue to expand, driving innovation, performance optimization, and fan experiences.

I hope you gained some latest trends that are being around Sports Industry. You can still read more about them in detail on your own if this industry interests you. I would try to give more insights into the internal workings of each of these Sports companies and how they work in upcoming blogs. Until then, stay tuned!

That’s from my side, keep exploring and learning!