1. Overwhelmed by the amount of in-game information
Many players wanted context, not just raw statistics. From our survey, 63% of participants wished the game to better explain why something happened instead of only showing raw data.
Industry Project Capstone Project for EA Games
FC 26 Manager +
An AI-powered companion experience that delivers personalized insights, smart recommendations, and real time support for FC 26 Career Mode managers.
- Type
- Player Experience Design
- Timeline
- Jan 2026 - June 2026
- Team
- 1 Mentor (Sponsor)
1 PM
1 UX Researcher
2 UX Designers (Me) - Deliverables
- Interactive Prototype
Presentation
Demo Video
Poster
Showcase
td;lr
Designing beyond the game
We partnered with Electronic Arts for this industry-sponsored capstone to explore how AI could shape second-screen experiencesWhat are second-screen experiences?Second-screen experiences are the apps and platforms players use outside the game while they play. for sports video games.
Rather than designing for a specific title, we started with an open-ended challenge: understand how players engage with digital experiences before, during, and after gameplay. Through interviews, concept exploration, and iterative testing, we identified an opportunity within EA SPORTS FC 26 Career ModeWhat is Career Mode?Career Mode is one of FC 26’s game modes, where players take on the role of a football manager building their own club. and designed an AI-powered companion app that extends the immersive experience beyond the game.
JUMP TO FINAL SOLUTIONScreen Highlights
The Problem
How might we design AI-powered second-screen experiences that help players interpret gameplay, reflect on performance, and build stronger connections to their club journey?
To improve their gameplay, many players rely on Discord, YouTube and various stat websites to compare tactics, learn mechanics, and seek advice from the community. We found examples of many dedicated fans creating spreadsheets and systems to track their career mode gameplay.
These resources demonstrate how invested players are, but they also reveal a fragmented experience. Information is scattered across different platforms and often requires manual tracking and organization. From there, we saw an opportunity to explore how AI could connect these experiences into a single decision-support system.
Research
Understanding player behaviors
105
Survey responses
14
Interviews
18-35
Age Range
We asked gamers across multiple platforms (PC, console, and mobile players) including our prior target, sports game players. We focused on four areas: gaming habits, second-screen behavior, AI perceptions, and information-seeking behaviors, and were able to find three key insights.
2. Second screen experiences rarely being used to improve gameplay
Second screens were often treated as a way to fill downtime (e.g., scrolling on social media or texting friends) instead of enhancing the gameplay experience.
3. Open to AI, but not AI playing for them
Players wanted AI to explain gameplay statistics and offer helpful suggestions, but worried it might reduce the challenge or take away the satisfaction of improving on their own.
One insight that stood out specifically among sports game players was the strong connection between real-world fandom and in-game engagement. Unlike many other game genres, players often started playing because they already loved the sport itself. Their attachment to clubs, players, and the broader community made community discussions, shared knowledge, and immersive experiences a much bigger part of how they played and learned the game.
Fragmented player ecosystem
We analyzed 12 platforms across gaming, sports, social, and performance ecosystems. Analytics tools often overwhelm players with information overload, while content platforms provide general inspiration rather than actionable guidance. Although AI has begun appearing across these platforms, it is primarily used for content recommendations or performance summaries rather than providing contextual support.
As a result, most platforms lack personalization tied to individual’s gameplay behavior in real time. The overall experience is further affected by fragmented workflows, limited real time support, and a heavy reliance on multiple tools.,
Initial design opportunities
Based on the gaps we identified, we initially explored three design opportunities. Rather than building another analytics tool, we wanted to investigate how community, real-world football, and contextual AI could create a more connected second-screen experience.
Why
?
To validate these ideas, we needed the right ecosystem. With the 2026 FIFA World Cup approaching, we saw an opportunity to connect real-world football with in-game experiences. Beyond that, players already relied heavily on companion apps, stat websites, and community resources for tactics, transfers, and team building, so FC26 felt like an ideal environment for exploring AI-supported second screen experiences.
Pivot
Testing our first direction with real FC Players
- Participants
- 6 FC 26 Players
- Goal
- Evaluate whether users can quickly recognize the app’s value and navigate core features
- AI Integration
- Improve players’ skills and stay competitive with friends through rankings and comparisons
Our mid-fi tried to support FC players broadly, combining social competition, real-world content, and gameplay insights into one experience. But ... we realized the concept sat awkwardly between different ways of playing FC. Players pointed to several issues with the experience:
The feedback made us realize that we had designed for FC as a whole without clearly defining which game mode or player experience we were actually supporting. It wasn’t competitive enough for Ultimate Team, yet it didn’t reflect the deeper, long-term experience of Career Mode.
Same game, two very different player experiences
Career Mode gave us a clearer opportunity for contextual AI. Unlike the fast, match-driven experience of Ultimate Team, Career Mode save builds its own history through seasons of transfers, tactics, and player decisions. We saw an opportunity for AI to make sense of that history and surface stories and insights unique to each player’s journey.
Building on the FC visual language
We built the visual system around FC’s dark interface and bold typography, using green as a focused accent for key actions and AI-supported moments. And here’s what it all came together.
Solution
AI-powered second screen built around the career you’re building
Connecting Gameplay With The Players Around You
Essential social and real-world features that connect active friends, shared achievements, squad discussions, and game updates tied to player performance.
AI Integration
AI tactics based on your build up style (ATT / BAL / DEF) and an AI assistant for quick, contextual questions.
A Centralized View Of Your Season
Season progress comes together in one view, from league standings and upcoming matches to team performance, training, and career objectives.
AI Integration
Player insights from performance and starting XI recommendations with tailored formation and squad context.
Understanding The Players And Team You’re Building
Move between your squad, Youth Academy, and Starting XI while keeping player development and team decisions in one place.
Adding A Narrative To Each Season
Look back how your season was with achievements, team changes, and key moments that turn that gameplay history into a narrative of what you built and accomplished.
AI Integration
Transfer target recommendations based on squad needs and compares potential signings against your current players.
Transfer Decisions With Team Context
Scout and track transfer targets across leagues and clubs, then compare players against your current roster before making a decision.
Validation
Validated by Players & EA
We wrapped up the project by presenting our final concept at the 2026 UW HCDE Capstone Showcase and later to ~ 30 Electronic Arts employees.
At the showcase, we demoed the product to FC fans of different ages, former Xbox employees, and other attendees, giving us the chance to hear their questions and reactions firsthand. One participant who had been skeptical of our initial concept even told us how much they appreciated the direction we took after our pivot.
When we presented to the EA team, they also highlighted our thoughtful use of AI, appreciating that it was integrated only where it genuinely supported Career Mode managers.
Reflection
Looking Back & Looking Forward
We value a good pivot!
Early on, our team saw pivoting as a sign that we had gotten the design wrong. But during our final presentation, one of the EA employee said “We love a good pivot,” which completely changed my perspective. A good pivot isn’t about starting over, but it’s about learning from users, challenging your assumptions, and having the confidence to change course when the evidence points elsewhere. It became one of the biggest lessons I took away from this project. I also shared my journey in my linked in post.
Next Step
Talking with FC players during the showcase sparked a lot of ideas for where this project could go next. Many conversations centered around how AI could support experienced Career Mode players, not by taking over decisions, but by helping them discover new clubs, tactics, and ways to play that they might not have considered before. I’d also love to make AI conversations more collaborative, giving managers greater control over AI-generated lineups instead of treating recommendations as fixed answers.
