Fantasy Football trades: How IBM Granite foundation models drive personalized explainability for millions

Fantasy Football trades: How IBM Granite foundation models drive personalized explainability for millions

With almost 1,700 players in 272 games, the amount of data generated during the NFL football season is enormous. Fantasy football team owners are faced with complex decisions and an ocean of...

With almost 1,700 players in 272 games, the amount of data generated during the NFL football season is enormous. Fantasy football team owners are faced with complex decisions and an ocean of information. Deciding who to start, who to bench and who to trade each week can be a daunting task. It can also be a lot of fun-and that's why the ESPN Fantasy app engages 12 million fantasy football users each year.

For the last 8 years, IBM has worked closely with ESPN to infuse its fantasy football experience with insights that help fantasy owners of all skill levels make more informed decisions. These insights take the form of player grades that help end users find the best players to trade or pick up from the waiver wire. Andthis year, the team is going even deeper, adding a new feature that unpacks the reasoning behind the AI-generated grades. When a user taps on a player to acquire or trade, a list of "Top Contributing Factors" now appears alongside the numerical grade, providing team managers with personalized explainability in natural language generated by the IBM® Granite™ large language model (LLM).

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