Sevilla FC leverages Meta’s Llama and IBM’s watsonx AI to enhance player scouting, cutting analysis time and improving talent identification.
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Sevilla FC enhances scouting with Meta’s Llama and IBM’s watsonx, streamlining player analysis and recruitment strategies. Image: Meta |
Seville, Spain – March 1, 2025:
Sevilla Fútbol Club (Sevilla FC), a seven-time Europa League champion, is harnessing artificial intelligence to refine its player scouting process. Partnering with IBM and Meta, the club has introduced Scout Advisor, an AI-powered tool built on IBM’s watsonx platform and Meta’s Llama 3.1 70B Instruct model.
Meta said that with over 300,000 scouting reports, Sevilla FC faced challenges in efficiently analyzing potential recruits. Scout Advisor streamlines this process by using natural language processing to bridge the gap between human insights and quantitative data, dramatically reducing the hours needed for evaluations.
“Scout Advisor allows us to merge data-driven analytics with expert human judgment, making our scouting operations more efficient and informed,” said Elias Zamora, Sevilla FC’s Chief Data Officer.
The AI system refines queries using soccer-specific terminology, ensuring precise and relevant results. Instead of sifting through hundreds of reports manually, recruiters can now ask Scout Advisor detailed questions about player traits and receive AI-generated summaries within minutes.
IBM’s watsonx and Meta’s Llama enable Sevilla FC to enhance talent identification, strengthen its competitive edge, and even attract interest from other clubs looking to adopt AI-driven scouting solutions.
“This is a revolutionary tool for a football director,” said Sevilla FC’s Sporting Director, Víctor Orta. “I no longer need to read 45 reports to understand what my scouts think of a player. Now, in just two minutes, I get all the insights I need.”
Sevilla FC continues to refine Scout Advisor and plans to integrate future versions of Meta’s Llama, ensuring they remain at the forefront of AI-driven football analytics.