We built a platform that used game performance and news data to predict outcomes for fantasy football.
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.
As a small team, I was in charge of all interface design, product feature development, branding, marketing, and general experience.
Our six-person team included business, engineering, and design staff.
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.
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:
Main Product Challenge:
Main Design Challenge:
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.
What we accomplished:
We were invited by IBM to speak about our platform and how we were using cognitive computing in fantasy sports.