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Reimagining
Fantasy Life's
Core Tools

A fast-paced redesign of three high-traffic pages — Draft Champion, Start/Sit, and Rankings — grounded in user research, JTBD methodology, and a shift from data-dumping to decision support.

PRODUCT DESIGN -- CONTRACT

Scope

3 Core Product Pages

Deliverables

Desktop and mobile web

Approach

Research → JTBD → Design

Project Overview

Fantasy Life brought me in to reimagine three of their most-visited pages. The brief wasn't a blank canvas — it was a constraint: work with what exists, understand why it falls short, and redesign with precision.

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The engagement began with a review package: existing screen designs across all three tools alongside transcribed user interviews covering challenges, pain points, journey maps, and direct user suggestions. My first task was synthesis — reading across all of that material to identify not just what users were complaining about, but what they were actually trying to accomplish.

From that synthesis I developed a JTBD agenda for each tool, then categorized every potential improvement into two buckets: new feature opportunities where a gap existed, and optimization opportunities where the existing UI simply needed to work better. That framework became the backbone of every design decision that followed.

The contract was fast-paced by nature. That meant ruthless prioritization — identifying which changes would move the needle most for both users and the business, and executing them with enough fidelity that the development team could take them directly into production planning.

Challenge

Transform high-traffic but underperforming tools from utilitarian data displays into genuinely decision-supportive experiences — without disrupting the patterns that existing users already rely on.

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Pages Redesigned:

  •  Draft Champion (pre-draft setup + live draft dashboard) · Start/Sit Tool · Weekly Rankings

Methods

Programs

Google_Forms_2020_Logo.png

Google Forms

Figma

My Role

Product Designer incorporating PM strategies — responsible for research synthesis, JTBD framing, interaction design, visual design, and post-design analysis.

Starting Point 

Existing Designs

Before any design began, these were the designs handed to me. Functional, High-traffic pages but carrying the weight of years of feature accretion with unclear unifying decision-support philosophy.

Research and JTBD

The user interviews revealed a consistent gap between what each tool offered and what users were actually trying to accomplish when they arrived.​

  • Research Inputs

    • User interview transcripts covering challenges, pain points, journey maps, and direct suggestions across all three tool experiences.

Rather than taking user complaints at face value ("I want more data"), I mapped each interview to the underlying job — the progress a user was trying to make in their independent journey. This reframing shifted the design conversation from feature requests to outcome design.

I then categorized every identified gap as either a new feature opportunity (something absent that users needed) or an optimization opportunity (something present but working against the user). This two-bucket model kept the work scoped and prioritized.

  • Analysis Method

    • Cross-interview synthesis → JTBD statement formation → gap categorization (new feature vs. UI optimization) → design agenda per tool.

Draft Champion

When it's draft season, help me feel confident I'm making the best pick available — without drowning me in settings before I even start.

  • Pre-draft settings form is overwhelming and front-loaded — cognitive overload before the fun begins

  • During the draft, the three-panel layout (Rankings / Queue / Roster) is cramped and hard to parse at a glance

  • No player comparison tool — users have to mentally hold multiple profiles simultaneously

  • Draft Assistant cards lack enough context to feel decisive — "add to queue" vs "draft now" is unclear

  • Mobile experience is a compressed desktop — not built for drafting on the go

Start / Sit Tool

Help me make my weekly lineup decision fast — I want a clear recommendation I can trust, not just raw numbers I have to interpret myself.

  • The existing card UI locks almost all meaningful data behind a paywall — the tool communicates no value before conversion

  • No clear recommendation output — users see data but don't get a verdict

  • Cards don't support more than two players cleanly — but real lineup decisions often involve 3–4 options

  • Matchup context is buried — the single most decisive factor isn't surfaced

  • Mobile layout stacks player cards vertically but removes the head-to-head comparison framing

Rankings

Let me quickly find where the experts rank a specific player in my format — and understand when experts disagree so I can make my own call.

  • Paywall locks immediately disrupt the core experience — users can't assess the product's quality before committing

  • Filter controls are scattered and verbose — scoring system, week, team, and position require too much effort to configure

  • Ranker identity is hidden in dropdowns — users trust people, not labels

  • Expert disagreement (high-value signal) is not visualized — consensus and outlier positions aren't scannable

  • Mobile collapses to a compressed desktop table — scrolling both axes on a phone is painful

Design Process and Iterations

Every design decision traced back to a specific JTBD gap. The explorations weren't stylistic — they were structural.

What changes when you design for outcomes instead of features?

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I ran parallel exploration tracks for all three tools simultaneously, testing different structural hypotheses before committing to high-fidelity execution. Desktop and mobile were designed in tandem from the start — not as an afterthought.

Two primary questions drove every screen: Does this surface the decision, or just the data? And does this earn the upgrade prompt, or interrupt the user's job?

Rankings

Tool 01  - Desktop & Mobile

01

Replace dropdown ranker selector with avatar-based picker

Users trust individual experts they follow, not abstract labels. Making ranker selection a visual, face-first interaction increases perceived trust and personalizes the output. It also surfaces the human expertise that's a core part of Fantasy Life's brand.

02

Surface Consensus and UR Score as primary sort signals

Two column-order explorations (Op1: UR Score first / Op2: Consensus first) tested which signal users reached for first. The goal in both was to remove the cognitive burden of mentally aggregating six ranker columns — let the system do that work and surface the headline number.

03

Redesign mobile as an expanded-row format, not a compressed table

On mobile, each player card expands to show individual ranker scores beneath the player name row — eliminating horizontal scrolling and making it usable one-handed. The ranker scores appear as labeled values below, not as a table column requiring pinch-zoom.

04

Consolidate header navigation and reduce paywall aggression

Stats & Info consolidation cleaned up the top nav. League Sync was repositioned as a contextual enhancement, not a gate — users see value first, then get the upgrade prompt when it's relevant to their action rather than before they've done anything.

Existing 

Proposed Design Op2

Proposed Design Op1

OPTIMIZATION WIN

From dropdown to face-first ranker selection

The avatar selector transforms an abstract setting into a personal curation moment. Users pick the experts they trust — and the data responds. This is the same mental model as following someone on social, applied to analytical tools.

NEW FEATURE

Consensus as a first-class signal

Previously, consensus was one column among many. In the redesign it becomes the primary sort axis — the system surfaces its own synthesis. For users who don't want to dig into individual rankers, this alone answers their question.

Start / Sit Tool

Tool 02 - Desktop & Mobile

01

Lead with a verdict, not a data card

The existing design presents players as equivalent cards and forces users to compare them mentally. The redesign introduces ranked verdict labels — "1 Best", "2 Start", "3 Start", "4 Sit" — so the output of the tool is a decision, not a display. The job is done for the user.

02

Cinematic hero header to establish player identity

A full-bleed player comparison banner with photography, rank numbers, and position context creates immediate orientation. This isn't decorative — it anchors the head-to-head frame and makes the tool feel like it was designed for this specific comparison, not generic.

03

Expose data before the upgrade prompt

The existing tool shows locks before showing any data — communicating no value before asking for conversion. The redesign shows charts, matchup quality indicators, and projection context to all users. Premium content is clearly differentiated, but the user understands what they're unlocking because they can see its shape.

04

Support 4-player comparison as the default, not the exception

Real lineup decisions rarely involve only two players. The desktop redesign expands to support 4-player comparison in a consistent grid, with the ranked verdict surfaced per player. Mobile stacks ranked cards vertically, each leading with the verdict label so the answer is visible without scrolling into the data.

Existing 

Proposed Design Op1

Proposed Design Op2

CORE REFRAME

The tool's output is a decision, not a data display

This was the central design thesis for Start/Sit. Everything — the verdict labels, the hero header, the data hierarchy — exists to make one thing happen faster: the user knows who to start before they finish scrolling.

CONVERSION STRATEGY

Earn the upgrade, don't demand it

By showing data structure before locking it, users understand what premium unlocks. The upgrade prompt lands after demonstrated value, not before. This is a fundamentally different relationship between the paywall and the product.

Draft Champion

01

Streamline the pre-draft settings into a focused, scannable form

Tool 03 - Desktop & Mobile

The existing settings page overwhelms users before the draft even begins. The redesign reduces visual noise, groups related controls more tightly, and separates the "start immediately" path from the "configure everything" path — letting eager users get into the draft faster.

02

Introduce player comparison as a new modal feature

The highest-value new feature identified from user interviews: the ability to compare two players side-by-side during a live draft. A "Compare" action on any player card triggers a modal showing both players with historical performance, tier breaks, expert agreement, and projected stats — the exact data needed to break a draft-time tie.

03

Elevate the Draft Assistant as the primary draft-time view

In the existing design, the Draft Assistant is a secondary tab. In the redesign it becomes the lead experience — the panel users live in during the draft. Rankings, Queue, and Roster become supporting panels, accessible but subordinate to the active decision at hand.

04

Mobile: build for one-handed draft interaction

On mobile, the draft experience was rebuilt around a single scrollable column with Rankings at the top and Roster/Draft Assistant below. Player insight callouts appear inline with each ranking card. The compare modal works as a bottom sheet — thumb-reachable, dismissible, fast.

Existing 

Proposed Design Op1

Proposed Design Op2

NEW FEATURE

Player Comparison Modal

The most direct response to user interview data. During a draft, users are constantly weighing two players against each other — the Compare feature brings that mental model into the product as a first-class interaction. Triggers from any player card with a single tap/click.

STRATEGIC INSIGHT

Draft Champion as a platform, not just a simulator

The redesigned Draft Champion positions itself as the authoritative draft companion — not a standalone mock draft tool. Integrating Expert Rankings, AI-powered suggestions, and comparison tools in one surface creates stickiness that extends well beyond draft season.

Final Designs

The final deliverables for Rankings and Draft Champion — the two tools taken through to production-ready fidelity. Both desktop and mobile, across light and dark themes, representing the new visual and interaction language for Fantasy Life's tool suite.

What I'd push further with more runway — and where the real ceiling for these products lives.

The paywall problem isn't fully solved. The redesigns reduce friction and show value before asking for conversion — but the underlying model of locking expert rankings entirely behind a subscription creates an adversarial relationship with new users. A freemium model where one ranker's data is always free, with premium unlocking the full suite, would likely outperform even the best paywall-adjacent UX.
 

The three tools need to talk to each other. Right now they share a brand and a nav bar. A user who syncs their league in Rankings has to re-sync in Start/Sit. A player researched in Draft Champion doesn't surface in any other tool. A shared data layer — powered by League Sync as the connective tissue — would transform three good tools into one great product.
 

Draft Champion has platform potential. The mock draft simulator is the entry point. But the draft grade, the roster that results from it, and the expert insights that informed each pick are all data points that could power a season-long companion. Post-draft analysis, weekly lineup recommendations tied to your draft roster, and trade evaluations built on your draft-day rankings are all within reach of the existing data model.
 

Mobile needs its own design system, not a responsive desktop. The mobile redesigns in this engagement are significantly better than what existed — but the deeper fix is treating the mobile experience as its own product surface with its own interaction model, not a layout-adapted version of the desktop.

  • What went well

    • The JTBD-first approach consistently produced design decisions that were defensible and traceable. When you know the outcome a user is trying to achieve, "should we add this?" becomes a straightforward question to answer.

  • What I'd do different

    • I'd push for a shared design system component library across all three tools earlier in the process. Designing them in parallel revealed shared patterns that weren't formalized — ranker avatars, tier bands, matchup quality indicators. Systematizing those would accelerate future work.

  • The bigger opportunity

    • Fantasy Life's competitive moat is Matthew Berry's brand and a roster of credible expert rankers. The product should make that human expertise feel more present, more personal, and more directly connected to each user's specific situation. AI is the accelerant for that. The foundation is here.

Which new metrics to track that align with Fantasy Life's North Star

Good design without measurable outcomes is just aesthetics. These are the metrics that would reveal whether the redesigns achieved their intended business and user value — and how we'd know if they didn't.

User Value Metrics

Rankings Ranker Selector Engagement

What % of Rankings users interact with the avatar-based ranker selector? This signals whether the new UI makes ranker personalization feel accessible.

Target: 3x increase vs. dropdown interaction rate

Player Compare Modal Usage

New feature — baseline is zero. Track activation rate per draft session and compare draft outcomes (grade) for users who use Compare vs. those who don't.

Target: >40% of sessions trigger at least one comparison

Time-to-Decision (Start/Sit)

How quickly does a user reach a lineup decision after opening the tool? The verdict-first design should measurably reduce this. Baseline against existing session length.

Target: >30% reduction in avg. session length

Draft Assistant Engagement Rate

What % of Draft Champion users interact with the Draft Assistant panel at least once per session? Elevating it as the primary view should drive this up significantly.

Target: 2x current engagement rate

Business Value Metrics

Free-to-Paid Conversion Rate

The most direct business signal. Value-first paywall design across all three tools should improve conversion by demonstrating product value before asking for it.

Target: >15% lift in conversion rate from tool pages

Draft Champion Return Rate

What % of users who complete one mock draft return for a second within 7 days? A more engaging draft experience should increase this substantially.

Target: >25% increase in 7-day return rate

League Sync Activation Rate

League Sync is Fantasy Life's highest-value retention mechanic. Repositioning it as contextual value (not a gate) should increase voluntary activation during natural tool usage.

Target: >30% increase in League Sync activations 

Session Depth Across Tool Suite

Do users now move between tools in a single session? Cross-tool navigation (e.g. Rankings → Start/Sit) signals the suite is working as a cohesive product rather than three isolated destinations.

Target: >20% of sessions touch 2+ tools

Where AI Makes
These Tools Smarter

The current redesign establishes a strong structural and visual foundation. The next evolution is AI-native — not AI as a feature badge, but AI embedded in the moments where users are most uncertain and the system has the data to close the gap.

01

Rankings — Personalized Expert Weighting

An AI model learns which rankers have historically been most accurate for a user's specific league format and scoring system, then automatically surfaces a personalized consensus score that weights those experts higher. Over a season, the rankings page becomes uniquely calibrated to each user — not just a static average of expert opinions.

OPTIMIZATION

02

Start/Sit — Natural Language Lineup Advisor

Users describe their dilemma in plain text — "Should I start Keenan Allen or play it safe with Tyler Boyd this week?" — and the tool returns a ranked recommendation with contextual reasoning that incorporates matchup data, recent performance trends, and scoring format. This transforms the tool from a comparison display into a genuine weekly advisor.

NEW FEATURE

03

Draft Champion — Post-Draft Grade Explainer

The existing draft already generates a grade at completion. An AI layer that explains the grade in natural language — what you did well, where you reached, which picks are high-upside vs. high-risk — would transform the grade from a number into a learning moment. Shareable by nature. Built-in social distribution.

OPTIMIZATION

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