Mobile app dashboard showing a section titled 'Between contracts' with last update 3 days ago, a location 'Lyon, France' with a high match label, details of a basketball club looking for a guard, and career tools options like Deal room, Vault, Agent hub, and Market value.

Professional athletes playing abroad can’t afford to trust the wrong people.

WEVOLV · UX Design

What athletes need shifts based on their situation, not their career stage. The system is designed around that. Working before she opens the app, surfacing what's relevant to her specific moment and earning trust before asking for anything.

Duration
Design 2 Weeks

Methods
Qualitative interviews, Quantitative survey (n=23), Secondary research & competitive analysis

Tools
Notion, Miro, Figma

The phase athletes spend the most time in isn’t supported by any existing platform.

Every platform skips the evaluate phase.

Who the user is —Professional athletes managing contracts, clubs and connections in countries where they have no established network and no local context.

What athletes do before connecting —Two to four weeks of passive observation. Monitoring social media, asking around, piecing together second-hand intel. They're evaluating, but doing it alone.

The gap —Evaluate sits between awareness and engagement and doesn't exist in any product designed for athletes.

What the research revealed instead —Career stage doesn't predict what athletes need. Situation does. An athlete between contracts has completely different needs than a veteran settling into a new country, even if they're the same age, the same level, the same sport. The design had to account for four distinct situations. Each one produces different behavior from the system.

A diagram titled 'Four-phase behavior model' outlining how athletes make connection decisions in four steps: Observe, Evaluate, Engage, Maintain. The Observe step involves passive scanning, and the Evaluate step highlights identifying gaps without support. The diagram also shows the flow from Observe directly to Engage with a note that there is no Evaluate phase in between.

“The 4-phase model is the single most useful frame to come out of this engagement. We’ve been designing around activation and connection volume. Your research reframes the entire product as a decision platform. That’s the right frame.”

— Client feedback, WEVOLV
Woman running up outdoor stadium stairs with blue seating

The research found something underneath the composure. That’s what I built for.

Gabby is a veteran. Seven seasons abroad. UK, Netherlands, Luxembourg, Belgium, Finland and Sweden. She knows how this works.

She's between contracts right now, training regularly, coaching to stay connected. From the outside, she looks like exactly what she is: a professional in strategic patience mode, staying ready until the right opportunity surfaces.

But the research found something underneath that composure. Gabby wasn't sure her visibility was actually reaching the right people. Not panic, just quiet, persistent uncertainty about whether the system was working for her or whether she was just waiting in the dark.

That's what this flow was designed for. Not the composed exterior. The uncertainty underneath it.

The system does the labor. She stays ready.

These screens follow Gabby through one specific moment: between contracts.

Every design decision responds to what she needs right now, not what athletes need in general.

Mobile app screen displaying a dashboard with sections about contracts between companies, including a compare location for Lyon, France, with options for actions related to contracts and career tools.

Dashboard

Three athletes named visibility control unprompted. Not as a preference but something they needed to feel safe.

Mobile app dashboard with a black and white background image of hands holding a basketball, titled 'What do you need today?', offering options to keep your people close or get in front of the right people, with a purple continue button and active status indicators.

Onboarding

Athletes don't extend trust to a system before seeing it demonstrate accuracy. The onboarding earns it before asking for anything.

Screenshot of a mobile app interface showing a 'Connect' tab with pending matches and messages related to a pro tennis team network in Lyon, including profile suggestions, recent activity, and connection requests.

Connect

Interviews showed 2-4 weeks of passive observation before any contact. The card leads with the match reason so the system does that work, not her.

Screenshot of a mobile app interface showing a 'Connect' tab with sections for 'Who's been paying attention' and 'Activity Log'. The interface displays notifications about profile views, active connections, and message activity.

Visibility

Both veteran interviews surfaced the same quiet uncertainty. Was her visibility actually reaching the right people? Specific signals answer that. Reassurance copy doesn't.

Mobile screen displaying a profile of a basketball club in Lyon, France, with an aerial photo of the city and sections about players and user comments.

What players know

Athletes rely on informal peer networks for local intel. The research found being everyone's resource was its own kind of labor. The peer cards surface that knowledge without putting it on any one athlete to carry.

The research made the case against verified badges.

Here’s what the data supported instead.

Insight 78% of athletes named peer reviews as their primary trust signal. Background checks registered at 4.3%. Verified badges don't build trust, peers do.

Design A composite of three signals: peer reviews, connection depth and track record. Visible on the profile before she decides whether to engage.

Three states designed for different moments:

  • Early Three labeled bars show the system's work while trust is still being established

  • Established Condenses to three dots with a summary line, less scaffolding, same signals

  • Low signal Shows honestly what's known and what isn't. Bars appear at Low or “None yet"

Impact An incomplete signal is more trustworthy than a fabricated one. The same principle that governs onboarding governs this, graduated autonomy applied to transparency.

Screenshots of a mobile app profile page for a person named Marcelle Davis, showing trust signals and activity details in three different signal strength states: early, established, and low signal. The interface includes icons at the bottom for dashboard, feed, connect, discover, and explore.

Career-level decisions deserve a deliberate commit moment. Auto-save isn’t enough.

Save button Career-level decisions warrant a deliberate commit moment. One Save button throughout the status sheet. Not auto-save.

Still True check-in Pre-populated confirms, not blank fields. Re-entering context she already shared signals the platform doesn't know her. Confirming builds trust before asking anything new.

Screenshot of a mobile app displaying user status settings and detailed status update about contracts, including training, overseas opportunities, and coaching, with options to edit situation and save changes.

Gabby shows up. The system already knows.

Five agents handle the logic, each with a defined job, defined inputs, defined outputs. The situation inference agent fires first and alone. The same system reads the situation differently every time depending on where the athlete actually is right now.

One rule governs all conflicts. What she says she's navigating overrides what the system infers. If there's a conflict, her declaration wins.

A system that updates her situation without asking isn't a partner. It's a manager.

A color-coded infographic showing four different situations with advice and indicators for athletes, illustrating how their perceptions and decisions change before and during app usage across various scenarios.

Four athlete situations. Four different system responses. Each map shows what the system knows before the app opens, what it surfaces inside the app and what the athlete decides. Same logic layer, different output every time based on situation, not career stage.

Diagram of a multi-agent system architecture titled 'WeWolv Connect Agentic Architecture'. It shows five specialized agents with descriptions and their interactions, including signal sources, fires first alone, routes and arbitrates, parallel specialists, and what the athlete sees. The system includes various data sources, trust graph, situation tags, ambient layers, surface layers, and an autonomous trigger, with color-coded sections for different agent functions.
Flowchart titled WELOW Agentic Flow illustrating stages before app opens, during the app, and athlete decision-making, with sections on invisible and visible athlete states, processes like profile mapping, peer reviews, connection depth, and system responses, using purple, yellow, and green colors.

How context moves through the system before Gabby opens the app.

A close-up black and white photo of an athletic man with sweat on his face, gazing into the distance, wearing sports attire, with one hand raised near his face.

The findings that mattered most were the ones that broke the hypothesis.

Every decision in this system traces back to how athletes actually build trust, not how a platform assumes they do. The research set the bar. If a decision didn't trace back to how athletes actually behave, it didn't belong in the design.

The research behind these decisions is documented in the WEVOLV research case study.