PredictionStrike is a new take on sports investing: a stock market for professional athletes.

iOS app
Social, Gaming
New York, NY
Company size

Key services

UI Design, UX design, Information Architecture, Site Mapping, Responsive Design, Mobile App Development, Web Development

Here’s a sneak peek of the results 2 months after launch:

0 %
Average Sessions/User
0 %
Conversion from Sign Up to Purchase
0 %
Number of Deposits >$100
0 %
average number
of deposits per user
0 %
number of users with over 30 minute long sessions
0 %
number of users with over 60 events per session

“Amazing & Innovative App.
Easy to use application that strives to evolve the way in which people view players across all sports.”

App Store Review

About PredictionStrike

PredictionStrike is essentially a stock market for professional athletes. The founders saw a unique market opportunity. Sports betting, as it exists, is generally short-term, winner-take-all, and often involves a lot of luck. PredictionStrike, instead, gives users the ability to actually invest in athletes they care about instead of just betting on a game. This means you could’ve bought Tom Brady when he got drafted, hold him over the long term, and well…made a lot of money.

Product Goals

  • Increase User Base
  • Increase Screen Time and General Engagement
  • UX/UI Redesign and Build (PredictionStrike “2.0”)
  • Decrease user support tickets

The Process

8 Unmoderated Usability Tests (UT) with We were approaching the project with a pretty big blind spot into the issues our users could be facing on PredictionStrike’s site, so we leaned in to usability to get honest insights from behavior (rather than surveys.)

User Segmentation: through testing, we segmented our user groups by young males who were self-described sports fans. We tested our target users through a “scavenger hunt” research method of sending users on a task and having them think out loud as they attempted to complete the tasks, supplemented by asking feedback questions.

Surveys: to learn more general information about our users. We asked what other sports betting platforms our target users used, frequency of PredictionStrike usage, and which sports they favored (among other questions.)

Competitive Research: We divided into competitive research into two basic concepts. We wanted to encompass both the world of sports—so apps like fantasy football—and the world of stocks and alternative assets—such as Robinhood, Coinbase, etc.



  • Raw research data
  • Research report
  • Product strategy recommendations


  • Site map
  • Low-fidelity wireframes
  • High-fidelity wireframes

App Development

  • ReactNative Application
  • iOS & Android Apps
  • Testing & QA

Web App Development

  • React.JS Web application
  • Marketing Website
  • Testing & QA

The Impacts

Week of Launch:

+ 80% users registrations

2 Months Post-Launch:

+ 2168% total sessions

+ 3637% avg sessions per user

+ 81% sessions over 30 minutes

+ 1305% deposits over $100

+ 434% users making 1 deposit/session

+ 71% users with over 60 events/session

App Store Reviews:

“The interface is easy to use…if you have a hunch over a player likely to have a breakout year, you can win a decent amount! LaMelo Ball went up around 400% last year in the NBA, so I can’t wait for what the NFL season has in store! Highly recommend for sports fans!”

“This app is what I’ve been looking for in virtual sports and I’m glad finally someone capitalized on the opportunity.”

The Challenges

  • Reducing the scope to accommodate the time constraint of launching by football season. This time constraint meant determining which features were absolutely crucial and which features were worth saving for the extended Phase 2 launch.
  • We entered the project with almost zero prior research. This meant that before we jumped in headfirst, we had to discover if the business goals were actually the right goals to be focused on for a successful re-launch.

The Insights

  • Our users were having issues finding information. They wanted to use the site to search and explore but there were no real explore features. The only way they would identify an athlete was to directly search the name of the athlete. Users had to rely on external resources to strategize.
  • Our users didn’t trust the previous site—particularly significant as a site that collected financial information.
  • Users were having issues understanding exactly what “the stock market of sports” meant. Different users had different explanations. This became increasingly important as users went to invest. If they didn’t understand how the pricing worked, they weren’t going to put their money into the platform.

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