TVConal boosts sports analytics with AI

Sports analytics is becoming an integral part of sports — from athletics to football. The army of video cameras deployed to cover events produce a slew of data.

Singapore startup TVConal is leveraging AI to harness this vast amount of data to up the game. It uses NVIDIA AI and computer vision to power its sports video analytics platform, which enables users to gain performance insights from these massive amounts of data in real time.

Powered by the NVIDIA Metropolis application framework for vision AI, the platform can detect important in-game events, model athlete behaviour, make movement predictions and more. It all helps dissect the minute details in sports, enabling teams to make smarter decisions on the field.

Match tagging creates a timeline of significant in-game events. This is crucial to sports video analytics. Tags are used to generate detailed reports that provide performance statistics and visual feedback for referees, coaches, athletes, and fans.

Since plays and other in-game events occur in mere instants, up to 20 loggers work together to accomplish live tagging for some sports matches. This can be time consuming and labor intensive.

With TVConal’s platform, sports analysts can extract insights from video frames with just a few clicks. AI helps to automatically and accurately tag matches in real time. This gives analysts the time to dig deeper into the data and provide more detailed feedback for teams.

The platform can also catch critical moments or foul plays that the naked eye might miss.

“If a player does an illegal action that’s beyond a human’s ability to process in a few milliseconds, the platform can detect that and inform the umpires to take an action just in time,” said Masoumeh Izadi, Managing Director of TVConal.

TVConal’s platform is built using NVIDIA Metropolis, which simplifies the development, deployment and scale of AI-enabled video analytics applications from edge to cloud.

“NVIDIA’s software tools, frameworks and hardware allow us to iterate faster and bring ideas to market with shortened life cycles and reduced costs,” said Izadi.

“There is an increasing volume of sports content to extract value from. Automated video processing is revolutionary in sports, and we are excited to build more advanced models and pipelines to keep the revolution going,” he added.