Playing the Field with AI and Adobe Analytics

Once a hobby for football-obsessed math whizzes, fantasy football has grown into a movement and time suck for millions of people across the world. With fans involved in multiple leagues, competing for bragging rights and often the big bucks, it’s becoming increasingly competitive. Fans understand the value of researching which players to place their bets on each week, and which players perhaps deserve a spot on the bench.

Data analysis isn’t a new concept for the sports world; leagues such as the NFL and MLB leverage Adobe Analytics to gain insight into their customers’ journey and actions, helping to personalize experiences effectively. And specific to fantasy football, consumers have recently realized how data can help them shape their teams in the right way.

Today, Adobe is announcing a new way for fans to get in the game with Adobe Analytics, unleashing the power of AI. Leveraging the leading analytics and measurement tool for brands across the world, consumers can tap into enterprise-grade analytics, as well as artificial intelligence with Adobe Sensei, our AI and machine learning technology, to manage fantasy football teams.

Coupled with data from Sportradar, fans can log in Adobe Analytics to make informed decisions before accepting a trade, benching a player or draft day. Every play of every game from the past three football seasons are included, including more than 170,000 player actions, nearly 1000 players and 50 different types of metrics.

For example:

In an industry-first, fans can use AI to help build their teams. By tapping into AI-powered features in Adobe Analytics with Adobe Sensei, such as Contribution Analysis, Anomaly Detection, Segment Comparison, fans can compare different groups of players to dig into specific details. For example, a fan can compare running backs vs. wide receivers, and make an informed decision on which player is best to draft. Or, if looking for a prediction on how a match-up will play out, a fan could add their team, as well as their competition for the week, and predict who will come out on top. Leveraging this information, fans can determine whether to change up their line-up for the coming week, or stay put.

This builds off our success with March Madness, opening up Adobe Analytics the past two years to the general public, so fans could better predict basketball winners based on which team had a statistical advantage in each category.

Football is largely unpredictable, but that’s the fun of it: why else would millions of people gather around the game each Sunday? But, with Adobe Analytics, fans can use data to help predict some of that unpredictability. Fans can also enter into a sweepstakes with the chance to win $5000; more details here.