Fantasy Football Analysis Platform

2015

We built a platform that used game performance and news data to predict outcomes for fantasy football.

The Problem

In 2015, fantasy football was exploding, and with that explosion came more and more data.

Veterans and newcomers alike were drowning in data to stay competitive, spending hours each week in spreadsheets. Something that should have been fun was a real hassle.

We set out on a journey to bring data together and deliver insights that saved players time and made fantasy football fun again.

Resources/Constraints

  • Extremely limited early-stage capital locally (Kansas City, MO)
  • Less than 30k of initial seed capital
  • Initial MVP needed to be launched within 12 weeks from scratch
  • Data had to be acquired by pricey official providers from the NFL

My Role in the Project

Coty Beasley - Designer
Coty Beasley (Me)
Founder, Head of Product

As a small team, I was in charge of all interface design, product feature development, branding, marketing, and general experience.

Initial Research

It's no shock to anyone that football is popular in the US. In 2014, Fantasy Football was $11B, Football Media Rights was $7B, and sports analysis was set to reach $4.7B by 2021.

We realized more people were playing than ever before (33,000,000) and participation in managing fantasy leagues was at an all-time high. The average fantasy player was spending over eight hours consuming information a week and spending over $100  on fantasy-related activities per year.

For a more qualitative perspective, we interviewed a few dozen players about their experiences about where they were spending the most time and what was most painful.

It seemed that people were looking for a way to break out of their spreadsheets and wanted a coach to help in decisions.

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Early Explorations + Planning

When we started, we needed to hone in on the initial feature set. We decided that our platform would be a supplemental tool to normal roster management and as such, would need a lot of bite-sized insights for people to consume.

Initial Feature Guideline:

  • We wanted users to be able to look up players, import rosters from other platforms like Yahoo, and catch up on news

Main Product Challenge:

  • Categorizing data and then figuring out what insights we'd develop

Main Design Challenge:

  • Creating a sophisticated design system to support multiple team brands and dozens of contextual data cards that would be presented programmatically
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Production Designs + Interactions

We settled on a responsive web app, since it would be the easiest and fastest given our skill sets at the time. We created several major versions of the application, seen below.

All versions focused around delivering insight cards, which were programmatically generated and presented under certain circumstances.

Later, we developed an "Edge Score" that was able to wrap up all factors into a simple recommendation.

Later version of the web application

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Outcomes

What we accomplished:

  • Launched a successful Kickstarter
  • Generated a significant amount of press
  • Launched an MVP
  • Created a useful news feature
  • Consolidated many data insights into one place

Official Kickstarter Video:

Featured at World of Watson in New York:

We were invited by IBM to speak about our platform and how we were using cognitive computing in fantasy sports.


Press Coverage: