ESPN, IBM Consulting and the power of data-driven decision making in fantasy football

Fantasy football has been around since the 1960s, when a part-owner of a professional football team gathered with friends to “draft” athletes into fantasy leagues and accrue points based on the actual performance of those players in their real-life games. It was an early effort to gamify the experience, have fun with friends, and increase interest in the football season.

It worked. Today, fantasy sports aren’t just fun and games; they’re an $8.8 billion-dollar business. An estimated 45 million Americans play fantasy football, dedicating nearly seven hours a week to researching players and managing their rosters throughout the season. And ESPN is the undisputed champion of the fantasy football platforms, with a record 11 million players managing more than 17 million teams.

“We want ESPN to be the destination for all fans playing Fantasy Football, whether it’s their first time or they’ve been managing a league for 20 years.,” said Chris Jason, Executive Director, Product Management at ESPN. “To meet that bar, we have to continuously improve the game and find ways to enhance the experience with new innovations.”

To keep that constant innovation moving, ESPN has been working closely with IBM Consulting over the last six years, designing, developing and delivering new features that enhance the user experience. In particular, ESPN is eager to develop ways to serve up insights that help fantasy players make great roster decisions.

“Football produces a massive amount of data,” says Stephen Hammer, Sports CTO, distinguished engineer, ES&iX, IBM Consulting. “There are 1,900 players in the league. Every time they take the field, they produce a whole series of data. And that’s just the structured data. Millions of blogs, articles, and podcasts about football are produced every season. And those contain important insights as well.”

To get a handle on all this data, ESPN worked closely with IBM Consulting to visualize the kinds of features and insights end users were looking for. They used IBM Design Thinking to understand the different personas of fantasy football players and map out the various user journeys they undertake. And they worked in the IBM Garage model, a proven methodology for co-creation that accelerates the innovation process.

The teams co-created two solutions, Player Insights with Watson and Trade Analyzer with Watson.

Player Insights combine analysis of structured data like scores and statistics, with AI-powered analysis of media commentary using Watson Discovery. This results in comprehensive and user-friendly insights designed to help fantasy managers understand a player’s boom or bust chances, or to assess how injuries will affect their lineup.

Trade Analyzer with Watson uses those same analyses to evaluate potential trades between fantasy managers. When one fantasy manager proposes a trade, Trade Analyzer examines the strengths and weaknesses of their team and shows which positions the manager needs to fill to make their team stronger.

In just the first week of the 2022 season, more than 6 million trades were proposed on ESPN’s platform. And last year alone, IBM served up more than 34 billion AI-powered insights through the ESPN fantasy app.

“This is the same technology we’re using to help clients transform data into insight in every industry,” says Hammer. “Whether it’s fantasy football or financial services, it’s all about data-driven decision making.”

The post ESPN, IBM Consulting and the power of data-driven decision making in fantasy football appeared first on IBM Business Operations Blog.

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