WagerWave
A social sports betting app, designed from a startup founder's brief.
Context
Sports bettors were already sharing picks and following each other, just not anywhere built for it. That activity lived on social media, where a claimed win record is unverifiable and following the wrong account can cost real money. There was no central space where a novice could learn from someone credible, and no way for an expert to prove a track record or build a following around it.
User Research + User Stories
With our target audience of sports fans, betting experts and novices, I posed this question: How do I create one platform where someone with no knowledge on sports betting can have the same experience as someone with a professional background in sports betting? Streamlining one platform to have different levels of accommodations was a crucial part of this project. For this project, I created user stories of what I thought would be useful for WagerWave after analyzing existing sports betting applications.
Community, Picks, and Monetization
- As a novice, I want to copy or follow someone's bet without placing real money.
- As an expert, I want to share my tips and grow a community around them.
- As a novice, I want to learn inside a community, and send sports videos and messages.
- As an expert, I want to monetize my knowledge by creating a subscription-based group.
Key Pain Points
No central place for the community: Novices and experts had no shared space to post picks or tail each other's wagers. The activity already existed, scattered across platforms never built for it.
Credibility was unverifiable: Following someone on social media meant trusting a claimed record with nothing behind it, which left people exposed to accounts only performing expertise.
No way to build on a track record: Experts had no mechanism to prove results over time, or to turn a following into something durable — whether monetized or completely free.
Data Flow Diagram
After the initial discovery meeting with the client, I began to work on Data Flow Diagrams for the User.
Low Fidelity Wireframes
I wireframed the core flows, from account creation and linking sportsbooks to the feed, groups, and profiles, and reviewed them with the client before UI design began.
Solution
Once the client approved the wireframes, I worked alongside our senior designer to complete the UI.
We were able to make sports betting accessible for all types of users. Professional sports bettors could utilize WagerWave to build a community and monetize their knowledge, while novice bettors would have a platform to share bets without needing to place actual money on the bet.
The mechanic that connected the two was tailing. When someone shared a pick, another user could copy that wager onto their own account in a single tap, which meant a novice could follow an expert's judgment without needing to interpret the odds themselves. Groups, leaderboards, and paid subscriptions all built on top of that one interaction.
Finalized Screens
Project Outcome
A platform where a first-time bettor and a seasoned expert share the same feed, with the option to participate without wagering real money.
I delivered the project brief, functionality lists, data flow diagrams, and wireframes, and with our senior designer, the final UI mockups. As an early-stage startup, building the app depended on the founders raising funding.
What I took from this
One interface can serve a novice and an expert, but only if the expert's tools stay out of the novice's way rather than being hidden from them entirely.
Tailing someone else's bet had to cost a single tap. A feature that depends on people participating has to be nearly free to use, or the social layer becomes decoration rather than the product.
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