RotoWire Smart Money
Translating sharp bettor signal into a product casual bettors trust — from OddsJam API to three shipped iterations.
PRODUCT DESIGN -- Lead Designer - AI Prototyping
Scope
Full Product iOS
Deliverables
Web Desktop + Mobile
Approach
PM → Designer → V1 → Insight → V1.1 → V1.2
Project Overview - Why this Product?
We found a Gap between two companies owned by the same parent serving overlapping audiences but failing at bridging the gap between expert Fantasy Sport bettors and new Fantasy sport users entering the sportsbook betting world.
RotoWire had the editorial-driven Picks & Props tool — trusted, familiar, but expert-led -- simultaneously a sister company OddsJam had a successful Sharp Money tool -- expert-led betting. RotoWire gained access to Oddjams data feed that spoke to sharps but had no place on the platform yet to display it nor integrate it. The middle ground — bettors moving from fantasy into real-money wagering — had nothing built for them.
Challenge
Our users needed a place to bet with confidence. We had the data they needed so we built a feature where they can bet with conviction.
"When I check betting lines, I want to know where smart money is moving so I can act — not just guess."
The user already knew how to find bets. What they lacked was a reason to trust one over another. The whole product is in service of closing that gap: from curiosity to conviction in under ten seconds through the establishment of a trust loop.
Score → Trust → Subscribe
The flywheel was straightforward: surface a high-confidence bet, the user wins, they trusts the platform, they upgrade subscription, then become a recurring bettor. The loop only works if the score is both accurate and perceived as accurate. Every design decision — how labels read, how bars scale, how the drawer explains — was in service of that second half.
Methods
Programs
Figma
Claude
ChatGPT
Starting Point
We had a footprint to work from. Two tools we had to understand and why neither was the answer on its own.
Before any design began we sat down to dissect, review, and fully understand our users insights in order to come up with a strategy and roadmap.
User Journey
01
Discover
Lands from RotoWire nav or organic search. Sees live feed sorted by score.
02
Read the Signal
Score ring + three bars give a fast read in under five seconds.
03
Trust the Score
Opens the drawer. This is where trust is built — or the user leaves
04
Decide
Bankroll context and risk modeling turn signal into a personal decision
05
Bet
One tap. Best line. Best book. No searching, no friction.
Discovery Process
Existing Oddsjam Designs
Rapid Prototype - Inspo RW Picks tool - Claude
What we studied
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The signal is real.
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OddsJam's Sharp Money tool is genuinely useful — stake distribution by price point, crossed market detection, edge percentage. Sharps use it because every number is visible and explained.
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The framing is exclusionary.
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Terms like "liquidity at -149" and "crossed market" assume exchange literacy most sports bettors don't have. The UI rewards the already-informed.
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The design challenge.
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Keep the data fidelity. Strip the jargon. Add RotoWire's editorial voice as a trust layer. Make the score actionable in under ten seconds — without hiding what's behind it.
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What we distilled
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The Card Pattern
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RotoWire's Picks tool had already established player photo + prop title + circular score gauge + CTA as trusted UI. Users recognized it.
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The Score Ring
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The circular gauge already meant "confidence rating" to RotoWire's audience. Reusing it for the Smart Score meant users arrived with a pre-built interpretation frame.
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The grid layout
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Two-column card grid from Picks collapsed gracefully to mobile. No new layout system needed — just new data inside proven structure.
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What we learned from Rapid Prototyping iterations
Although the information in the first iteration was accurate, the framing was wrong. Showing raw exchange data without a "here's what this means for you" layer created anxiety and confusion, not conviction. The fix wasn't removing data — it was moving it and creating supporting visualizations for it. The score ring needed to lead. The CTA needed to be unambiguous. Editorial voice needed to translate the confidence.
Design Iterations
V1 - We Had One Clear Job -- create a feed that captures interest, and earns trust.
The design had to simplify complex data, highlight the items that would inform the user what the bet was and more importantly earn the trust and confidence at first glance. We distilled the data points to three main pieces of information and relied on visualization to provide clear and quick information digestion.
Accept voice as a genuine first-class input — not a feature layer
Tool 01 - Journaling/Entry
V1 Dark Mode
V1 Light Mode
Breaking down the card anatomy
01
Score Ring
The hierarchy decision: make the score the hero, everything else supporting context. Score runs 60–100, color-coded from green through amber to red. The verbal label — GREAT / GOOD / OKAY / BAD — was added after testing showed users weren't calibrated to the number range alone. The label does the last mile of interpretation wor
02
Data Bars
Staked, Edge, and Win Probability in priority order. Bar length communicates relative strength — the exact number matters less than the visual read. Three bars is the ceiling; more would have diluted the scan speed that makes the feed useful.
03
Context Header
Player photo, prop title, matchup, league, time. The photo was inherited from Picks — it makes the card feel editorial rather than algorithmic, which matters for a platform whose credibility is built on expert voice.
Bet Drawer Detail
Bet Drawer - Mobile
Drawer is where trust is earned
01
Stake Distribution
How much sharp bettors put down on exchanges at each price point. Horizontal bars by line (-160, -150, -145...). The translation: OddsJam's raw exchange data made readable as a price-ladder visualization. Signals where the real money went in, and at what price.
02
Edge Breakdown
"We found a better payout than what sharp bettors accepted." +11.9% edge means you're getting a materially better deal than the exchange average. Shows Smart Money avg vs best sportsbook line side-by-side — makes the case in two numbers.
03
Probability
59.8% chance to win $117 on a $135 bet. Probability translated into a concrete dollar scenario. The framing matters: "59.8% chance" is abstract; "$117 on a $135 bet" is emotionally real. Users think in outcomes, not statistics.
"The drawer is where trust is earned. The feed is where interest is captured. Both solve different jobs, our initial mistake was trying to treat them as one screen."
V1.1 - We Got Smarter
The design response wasn't optional. A high-confidence score on a 20% win-probability bet looks wrong to a casual user. Without UI scaffolding — explanation copy, re-labeled sections, visible reasoning — the score felt broken, not sophisticated.
Recency dominates. The age of the sharp action was the single strongest predictor of value — more than stake size, more than edge percentage. A bet 20 minutes old carried dramatically different signal than one four hours old. bet_time earned 40 of 100 points.
New Filters Added
Improved League Taxonomy
Saved Filters - Preferred View
Players' News + Bet Risk + Multiple Lines
What Changed? V1 - V1.1
RISK WARNING
Polymarket Banner: "If this player doesn't play, you could lose"
Responsible gambling signal — and a trust-builder. Acknowledging risk reads as honest, not cautionary.
CTA STRUCTURE
Primary CTA + "Other Books" secondary list
Multi-book grouping — best line primary, alternatives below for user choice. Same bet, one card.
NEWS SECTION
Latest News rows with dates, expandable article preview
The merger of editorial and algorithmic that the product was always supposed to be. RotoWire's core competency finally inside the bet decision.
Update "Chance"
UX Copy: Win Probability
Language precision signals product maturity. More importantly, it aligns with how the filter is labeled — consistency across the surface matters.
What the work taught us
The principles that emerged across three iterations — not obvious at the start, earned through decisions that were later revisited.
Principles Emerged
Score legibility is confidence
Early scores spanned 30–100. Users couldn't calibrate — a 72 felt arbitrary against a 58. The fix was structural: floor at 60, distribution curve so most scores land 80–100, verbal labels to anchor the range. The number didn't change. The perception of the system did. How a score feels is part of the product — not just its accuracy.
Filters should reduce noise, not add options
The temptation when you have a rich API is to surface everything. Each filter in V1.1 was defended only if it made the feed more signal-dense, not because it was interesting to expose. "Chance" became "Win Probability" because the label shapes how users understand what they're controlling. Filter taxonomy is UX writing.
Borrow trust before building it
The fastest path to user trust on a new product is inheriting it from something they already trust. RotoWire's card pattern, score ring, and editorial voice were all borrowed. Smart Money grafted new signal onto a proven visual grammar. The constraint of working within a design system was actually its most valuable asset.
Risk disclosure can be a retention mechanic
The Estimator's "Place 8 more bets to cut your risk in half" reframes a warning as a goal. The progress bar makes the user feel behind on a target — not cautioned away from the product. The best product mechanics align platform interest with user interest without feeling manipulative. They feel like coaching.
Next Explorations
Player Page Fusion
The bet card as an entry point into the full RotoWire ecosystem — player profile, news, fantasy projections, historical performance. The product earns context that no sportsbook has.
Injury News Layer
Real-time injury reports and lineup changes that materially impact the Smart Score. RotoWire's editorial lead time becomes a genuine betting edge.
Historical Win Rate
Score-band accuracy over time. Users who see that 90+ scores win 67% of the time trust the system more than any interface copy could achieve. Transparency as retention strategy.
1-Click Placement
Sportsbook API deep-link opens the bet pre-filled. Remove the last friction point between insight and action. The product becomes the whole decision flow, not just the analysis.