MetaMask Predictions

Intuitive, lively, and scalable prediction markets.

Predictions product context

Context

Evolving Predictions beyond the MVP

Six months after launching Predictions, we had enough behavioral data and user feedback to understand where the experience was working and where it needed to evolve.

We learned that sports, crypto, and politics drove most engagement. Our existing navigation struggled to accommodate the growing breadth of markets, while a newer card-based approach was showing promise. At the same time, the core experience needed to become more competitive, and users were asking for more sophisticated ways to trade.

This created three priorities:

  • Strengthen the core experience so markets were easier to scan, understand, and trade
  • Build a system that could scale across sports, crypto, politics, and new market types
  • Expand how users could trade through combinations and advanced order types

I worked with a small cross-functional team to define and deliver the next iteration of Predictions.

Core Predictions

Creating a scalable foundation for every prediction market

  1. 1

    Discover

    Scan markets across sports, crypto, politics, and new types.

  2. 2

    Evaluate

    Understand a market at a glance, then in detail.

  3. 3

    Order

    Place a straightforward trade or a more advanced one.

  4. 4

    Confirm

    Leave with a clear record of the position entered.

Prediction markets were fundamentally different from MetaMask’s traditional financial experiences. Users expected them to feel more immediate, lively, and approachable.

Rather than treating each improvement independently, I focused on establishing a consistent interaction model across discovery evaluation order confirmation.

Cards

Making markets clear at a glance

Cards are the primary way users discover and evaluate markets, so I redesigned them around the information needed to make a decision quickly.

The system supports both standard prediction markets and versus formats for sports, while maintaining a consistent hierarchy around outcomes and odds. We also streamlined odds into ¢ values to more closely connect price with the value of a position.

Motion

Using motion to make markets feel alive

I explored slot-reel-inspired motion for changing odds, reinforcing the dynamic nature of prediction markets.

Animating every market simultaneously quickly became visually overwhelming, so I constrained the behavior to cards entering the user’s focus. Motion became a contextual signal rather than decoration.

Chiefs vs Bills

KC
21

LIVE Q3

0
BUF
NFL $2.7M Vol. +9 more

LIVESet 5

M. Navone

  1. 5
  2. 6
  3. 6
  4. 3
  5. 67
AD

F. Cobolli

  1. 7
  2. 3
  3. 3
  4. 6
  5. 79
40
Wimbledon ATP $X Vol +2 more

When will Bitcoin hit $150K

Before January 2027

Before September 2026

BTC $34.8M Vol. +4 more

Will Ethereum hit $10K in 2026?

Yes

No

ETH $18.2M Vol. +6 more
For sports specifically, I tried experimenting with different layouts and vibes. I decided to lean on the versus format for scoring as that performed well historically and we could reserve other options for future growth experimentation.

Market details

Extending an established information architecture

Rather than creating a completely new detail-page pattern, I adapted the information architecture I had established for Token Details to Predictions.

This created greater consistency across MetaMask while allowing prediction-specific information and actions to live within a familiar structure.

Prediction market detail screens for football, baseball, and golf

Order experience

Scaling a simple interaction model to advanced trading

I extended our quick bottom-sheet pattern to support both straightforward trades and more advanced behaviors such as limit orders.

The goal was to introduce additional capability without making the default betting experience feel heavier.

Market and limit order bet slips

Confirmation

Providing confidence when a position is placed

Unlike many transactions elsewhere in MetaMask, research indicated that users wanted stronger confirmation after placing a prediction.

Instead of relying solely on a transient toast, we introduced a dedicated confirmation state that clearly communicated the position they had entered.

Trade submitted confirmation and auto-sell target

Combinations

Supporting parlays

Expanding from individual predictions to multi-market bets

Sports represented an important part of Predictions usage, but the product lacked a behavior common to sports betting: combining multiple outcomes into a single position.

Rather than simply recreating a traditional sportsbook parlay flow, we explored how combinations could fit naturally into MetaMask’s existing interaction model.

Prebuilt combinations

Reducing the effort required to get started

Across two rounds of research, we found that users responded well to prebuilt combinations.

Instead of asking users to construct every combination from scratch, we provided starting points that could be reviewed and modified before placing a trade.

Prebuilt combination cards across Predictions home and Combos

Building combinations

Moving from an order form to a cart mental model

My initial explorations relied heavily on bottom sheets for constructing combinations. Through design critique and iteration, the cart metaphor emerged as a clearer model.

Users could progressively add outcomes while continuing to browse markets, with add-to-cart motion providing immediate feedback and reinforcing the more playful character of Predictions.

Combination builder with bottom sheet and cart

UXR version used a bottom sheet and colored buttons to convey selection. I ultimately decided that this was confusing as we're already using color to indicate active.

Revised mock after UXR leans on an outline treatment to indicate selection and works harmoniously with the new cart button.

Order experience

Keeping the interaction model familiar

Although combinations introduced significantly more complexity underneath, placing one should not feel like learning an entirely new product.

I reused the core order experience established for individual markets, allowing the system to accommodate a new trading behavior while preserving familiarity.

Combination slip and buy sheet

Solution

Predictions V2

The new Predictions experience addressed the core challenges we uncovered in V1. We created a scalable information architecture that supports every market category, outcome combination, and advanced order type, paired with a more inviting visual language that surfaces the information users need to make a prediction.

Impact

These updates establish a more expressive and scalable Predictions experience across core markets and combinations. The latest iteration is still rolling out, so we’re continuing to measure its impact on engagement and trading behavior.

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