Decision Support: ESPN Fantasy Football and the power of IBM Watson

By | 2 minute read | September 7, 2021

Life is full of tough decisions. Some are inconsequential (Should I get an ice coffee or a caramel ribbon crunch crème frappuccino?) Others have a profound and lasting impact (Should I apply to law school or pursue my passion for rescuing sea turtles?)

When we engage in these internal decision-making dialogues, what we’re really doing is trying to predict the future. Consciously or subconsciously, we make little pros-and-cons lists, weigh the tradeoffs, and make educated guesses about how it will all play out. (I can probably make at least $80K out of law school, but am I going to be happy working 100 hours a week?)

These are deeply imperfect decision-making systems, subject to countless biases, irrational thinking, and insufficient data. And that’s why I’m so fascinated by what is happening in the ESPN Fantasy Football app right now.

For the last four years, IBM has been working with ESPN to integrate the artificial intelligence of IBM Watson into their fantasy football platform. And the goal of this work is to help fantasy team owners make better decisions about their rosters. To do it, Watson analyzes an ocean of structured and unstructured data — from player stats to media commentary – to predict whether a player will boom or bust in any given week. 

And this year, we’re introducing a new and improved Trade Assistant with Watson, which serves up personalized trade recommendations that are fair and mutually beneficial. And you can see Watson’s rationale for each proposed trade. You can watch this video to see how Professor Eli Manning explains it.

Obviously, fantasy football roster decisions do not have a “profound and lasting impact” on our lives. But I would argue that the decision-support capabilities on display in the ESPN Fantasy Football platform are far from inconsequential. In fact, I believe we are witnessing the future of decision making, in which AI helps predict outcomes by quantifying the tradeoffs of a particular course of action.

In business, the applications of this capability are endless. And I’m not just talking about trading stocks. Consider a clothing retailer deciding which products to put on the showroom floor. Or a healthcare provider deciding between two potential treatment options for a patient.

I’m not arguing that Watson — or any AI for that matter — can predict the future with certainty. But it can augment the undeniably flawed decision-making process we use every day, distilling vast quantities of relevant information into trusted insight.

So whenever you find yourself deliberating a consequential business decision, ask yourself two things: 1.) Am I taking all of the available information into account? And 2.) Do I have the right tools to support the decision-making process?

If your answer to either of these questions is “no,” come talk to us about IBM Watson.

It’ll be the easiest decision you make all year.