IMG ARENA achieves up to 100% accurate, engaging MLS commentary with Generative AI

about img arena

 IMG ARENA delivers innovative sports technology solutions, including live streaming, sports betting services, and real-time data insights for global leagues, sportsbooks, and media partners. The company works with leading sports organisations to enhance fan engagement and deliver high-quality sports experiences.

Challenge

IMG ARENA wanted to enhance its Major League Soccer (MLS) match coverage by creating commentary that was both engaging and realistic, while avoiding the mechanical tone often associated with traditional AI-generated output. The commentary needed to focus on key match events – such as goals, red cards, and major plays – while avoiding irrelevant or overly detailed updates that could distract from the fan experience. 

At the same time, accuracy was essential. The system needed to ensure every statement was backed by actual match data, producing commentary in a natural, American-style sports broadcasting voice. The challenge was to strike the perfect balance between entertainment and factual precision to deliver a more compelling viewing experience. 

Solution

An advanced AI-powered commentary system was developed to process raw MLS match data and generate concise, engaging play-by-play updates. Using Amazon Bedrock, the system grouped match events intelligently, filtered out less significant actions, and delivered human-like commentary tailored for American audiences. 

The solution also featured customisable match summaries, including half-time, full-time, and minute-by-minute recaps, enabling fans to quickly catch up on the most important events. This combination of precise data processing and natural-language generation significantly improved the viewing experience for fans while offering valuable tools for broadcasters and betting platforms. 

Services used

  • Amazon Bedrock
  • Amazon S3

The Results

The technology that we use to support Paysafe

JavaScript
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Node.JS
React
Swift
Java
Objective-C
RxJava

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