The client, a major MAM and media logistics company, approached Oxagile with the need to scale soccer content monetization and transform the content generation process accordingly. The expectations for the solution were as follows:
After two months of work, the team presented a fully working solution, ready to be deployed on the client’s side.
The system met all the key requirements and successfully supported the client’s business needs in terms of monetization strategies, engagement opportunities, and cost-to-quality ratio.
The platform is pre-trained to detect multiple moments of interest in soccer games. Using human-like ML algorithms, the solution analyzes and decomposes any soccer match to automatically generate a precisely tuned compilation of highlights, while significantly reducing manual effort.
The system recognizes and categorizes everything happening on the screen, including all foul types, red cards, scoreboards, audience reactions, and other replay-worthy moments. It further identifies teams and players based on facial and gear recognition, creating opportunities like compiling Messi’s corner kicks and other hyper-specialized moments.
Faster footage processing allows producing and publishing multiple compilations during and after the broadcast. As compilations arrive earlier, hardcore fans can stay up to date even with the games happening in parallel.
The highlight generation platform enables video providers to deliver highly anticipated content in the crucial first hours after the match when the demand for summary and overview videos is at its peak.
Using smart replay detection technology, the solution is able to process footage and create highlight compilations up to 3.2 times faster. As soon as the match has ended, all processed highlights become available to the editors for a more in-depth scene categorization.
The final product has been delivered within budget and on schedule, ready for launch in the client’s digital ecosystem.
By bringing intelligent automation into the equation, the client’s team has been able to slash the effort associated with additional content creation. Thanks to a reported 70% increase in footage processing speed, the cost of video production and postproduction has gone down significantly.
Beyond these gains, the ML-enabled engine has helped the client to:
