Role
UX Researcher & Designer
Timeframe
Fall 2025 Semester
Platform
Mobile App
Team
6 UX Designers
Overview
WalterPicks is an app used to gain fantasy and betting insights while leveraging machine learning to deliver smarter decisions. Users can link their different betting accounts to access accurate predictions, actionable advice, and expert insights to enhance their fantasy and betting experiences.
I joined this project as part of Purdue’s Experience Studio course, where our six-person team was tasked with evaluating and redesigning WalterPicks’ game betting and player prop evaluator (PPE) interfaces. While the app offers powerful individual tools, the current design lacks integration between them. My goal was to help bridge the gap between what the technology could do and what users could actually understand and use.
Problem Space
Central Question
How might we redesign the UI to emphasize its core betting features and deliver a cohesive, seamless experience?
User Group
Sports fans and sports bettors (ages 18+) with varying levels of experience who utilize digital platforms to place wagers.
Core Issues:
• The Player Prop Evaluator and Game Betting features felt like disconnected experiences rather than parts of a unified platform.
• Users were confused by terminology like “EV Edge,” overwhelmed by information density, and unable to differenciate different screens.
• The lack of visual hierarchy and intuitive labeling meant that even experienced bettors were struggling to extract information from the app’s core features.
Research
01
Literature Review
02
App Store Review
Analysis
03
Competitive Analysis
04
User Interviews
(Round 1)
05
Usability Testing
(Current State)
Literature Review
I started by immersing myself in the psychology of sports betting. Our literature review surfaced key behavioral concepts that would later inform our design decisions.
Takeaways
Loss aversion drives users toward small bets with better odds. Confirmation bias means bettors rely on prior intuition and social media, not raw data. Customization expectations have been set by competitor platforms offering personalized bet-building and tailored recommendations. These insights helped me understand that our design needed to prioritize scannability and surface high-confidence metrics upfront, rather than burying users in granular data.
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Ideation
Round Robin Sketching & Low/Mid Fidelity Mockups
We kicked off with a Round Robin Sketching session, rotating sketches every two minutes so each team member could build on others’ ideas. This exercise produced a set of group-annotated concepts that directly fed our wireframes.
Takeaways
Dropdown filter for sports categories.
A wider search bar spanning the full width.
Player profile pictures added to prop cards for faster scrolling.
Simplified footer for more intuitive navigation
Game/Player toggle to switch between central screens
Developing User Personas
Drawing from our interview data, I helped create three initial personas that captured varied segments within WalterPicks’ user group. We focused on differences in experience level, betting motivations, information sources, and pain points. These personas guided our design priorities and helped us evaluate whether our solutions served different user types:
Mitchell Grant
Ideal user, 27-year-old sales representative, frequent WalterPicks user, data-driven, motivated by profit. Wants shorter navigation paths and prioritized insights for efficient bets.
Brad Cheddar
22-year-old college student, experienced bettor but not a WalterPicks user. Motivated by social competition, needs reliable analytics and efficient workflows to balance betting with school.
Jonah Jones
32-year-old data scientist, WalterPicks user focused on fantasy football. He wanted comprehensive league views and optimal lineup recommendations, but only used the app seasonally.
Iteration
With our initial designs taking shape, the project transitioned from exploration to validation. I participated in multiple rounds of testing that progressively refined our concepts.
Second-Round User Interviews
The WalterPicks sponsor provided an interview protocol and a list of their own users willing to give feedback. We combined this with our original protocol, adding a prioritization ranking activity and concept-specific questions. The interviews confirmed that users were conservative bettors who preferred betting on favorite teams and valued simple interfaces.
The ranking activity was particularly insightful — users showed a strong preference for high-level decision drivers like Win Probability, Team Stats, and Opponent Historical Stats. Conversely, they deprioritized granular raw data. This validated our design direction of surfacing key metrics prominently while reducing information overload.
Concept Testing
We tested two major design concepts: a Toggle design (Game/Player switch at the top of a unified Betting screen) versus a Non-Toggle design (integrated game and player data on the same page). Participants favored both approaches for different reasons — the Toggle reduced visual clutter while the Non-Toggle allowed seamless workflow. We ultimately chose the Toggle design for its cleaner hierarchy.
For team visuals, we tested helmet icons versus color-coded rectangular blocks. While opinions split, we selected the block design because it was consistent with the existing design system and offered better scalability across all sports — helmets are football-specific, but colored blocks are universal.
Final Designs
Main Page
Unified Betting Page with Game/Player Toggle
The original app treated Game Betting and Player Props as entirely separate flows, creating a disjointed experience. The redesigned Betting page features a prominent Game/Player toggle at the top, allowing users to switch content with a single tap.
Vertical Card Layout for Game Betting
Our initial testing revealed that users felt overwhelmed by the horizontal, dense layout of the original betting screen. We implemented a vertical card layout that presents each matchup as a distinct card with teams displayed side-by-side.
Player Prop Cards
Player & Team Displays
Player headshots and team logos were added to each card, as our research determined that increasing visuals to reduce cognitive load. Users can quickly identify players and teams without reading every line of text.
Refining Terminology
“EV Edge” was renamed to “Value” per the sponsor’s decision, and moved to a high-visibility badge in the corner of each card. This ensured the most critical decision-making metric stood out immediately.
Filtering
Auto-Filtering for Selected Games
When a user tapped “Top Player Props” on a game card, the Player Prop tab now automatically filtered to show only athletes in that matchup. A blue banner confirmed the active filter to the user. This eliminated the “lost in navigation” feeling that novice users reported in our initial testing and created a seamless bridge between game-level and player-level analysis.
Enhanced Search and Filtering
An enlarged search bar now spans the full width of the screen, with dedicated filter and sort options. This addressed the line shopping pain point, where users wanted quick access to specific players or matchups without scrolling through the entire list.
Visual Additions
Weather Icons and Contextual Data
Small weather icons were added to game cards to provide at-a-glance context for outdoor matchups. While this was a subtle addition, it addressed user requests for factors that affect game outcomes and betting decisions.
Scalable Team Visual System
Instead of sport-specific assets like football helmets, we designed color-coded rectangular blocks with team abbreviations. This universal visual language scales to all sports without requiring unique design assets for every league — a critical consideration for WalterPicks’ multi-sport ambitions.
Reflection
Never Slack On Research
Research is not optional it’s the foundation. Every major design decision in our final prototype traced directly back to a specific research finding. The literature review shaped our understanding of betting psychology, the usability testing gave us a prioritized pain point roadmap, and the concept testing validated our specific visual approaches. Without this rigor, we would have been designing based on assumptions.
Terminology matters as much as layout. The “EV Edge” confusion was a powerful lesson in how domain-specific jargon can create barriers. Renaming it to “Value” and giving it visual prominence transformed a point of frustration into the app’s clearest value proposition. Iterative testing builds conviction. Each round of testing refined our direction incrementally. The concept testing resolved debates within our team (Toggle vs. Non-Toggle, helmets vs. blocks) with data rather than opinion, making our final decisions defensible
Key Learnings
Sports fans and sports bettors (ages 18+) with varying levels of experience who utilize digital platforms to place wagers. Sports fans and sports bettors (ages 18+) with varying levels of experience who utilize digital platforms to place wagers.Sports fans and sports bettors (ages 18+) with varying levels of experience who utilize digital platforms to place wagers.
What I Would Do Differently
Given more time, I would have loved to conduct A/B testing on the live product to measure actual behavioral changes, not just stated preferences. I also think there’s an opportunity to explore personalization features — our literature review highlighted customization as a key driver of engagement, but scope constraints kept us focused on the core navigation and display redesign. Finally, I’d push for accessibility auditing to ensure the color-coded Value badges and team visuals work for users with color vision deficiencies.
