Turning sports data
into decisions,
not just displays.

The problem common to all sports data products

Sports data platforms tend to confuse comprehensiveness with usefulness. Dense tables with many columns, raw statistics without interpretation, and layouts that require horizontal scrolling on mobile are the default, because they were designed from the database outward, not from the user's decision inward.

Lineups.com serves bettors, fantasy players, and analysts. Each has different goals when they arrive at a page. A bettor wants to quickly identify value. A fantasy player wants to compare specific players for a lineup decision. An analyst wants full data depth. The challenge is designing experiences that serve all three without creating three separate products.

Projections widget redesign

The existing projections layout presented data correctly but without guidance. Salary and projection, the two primary decision signals for DFS users, were buried among many other columns in a dense table. On mobile, horizontal scrolling disconnected columns from their context, making comparison impossible without holding numbers in memory.

The redesign introduced a card-based layout that surfaces salary and projection as hero values for each player, with secondary stats collapsed but accessible. Position filter chips replaced the full position dropdown, reducing the selection cost for the most common filter action. The result is a page that is easier to scan on mobile without removing depth for power users who want it.

Team rankings & comparison

The team rankings page had an identified gap: the PM noted the comparison tool was missing on desktop, despite being the most useful feature for users trying to evaluate matchups. On mobile, the dense rankings table required horizontal scrolling through many columns, making comparison essentially impossible.

The proposed solution was a hybrid experience designed differently by device and intent. On mobile: a selection-first flow where users pick 2-5 teams, then see a full-width comparison chart. On desktop: the full rankings table retained with a sticky comparison toolbar at the top, users select teams from the table rows and the comparison builds inline.

The key design decision was treating the comparison as an always-available mode rather than a separate page. Users can enter and exit comparison without losing their place in the full table. This reduces the cognitive cost of using the feature enough that users who previously couldn't be bothered to navigate to a comparison tool will use it naturally within the rankings experience.

Standings redesign

Standings should be quick to scan. The existing table required users to decode row by row, checking columns for record, splits, streak, and games back, then holding those values in memory to compare teams. The redesign made key signals scannable at a glance: form momentum visualised inline, recent result sequences shown as compact icons, and expanded cards available for users who want deeper context without the expanded state being the default view.

Community predictions, product concept

The community predictions concept was proposed as a product layer that converts Lineups from a data destination into an engagement platform. The core mechanic is simple: one daily pick per league, yes/no vote format, with immediate community results after voting. But the strategic value is significant: each vote is structured behavioural data, which topics drive engagement, which teams and players command interest, whether community sentiment diverges from market probability.

The MVP was designed to start with free daily picks to build user behaviour before any market routing. The longer-term vision is prediction markets as a native Lineups layer, powered by sports context and editorial data signals, rather than sending users to an external service like Polymarket. The distinction matters: keeping prediction activity within Lineups creates dwell time, session depth, and a dataset that can improve every other product decision.

Betting calculators suite

For Gaming Today, a six-calculator suite was designed: Odds Converter, Moneyline, Parlay, No-Vig, Kelly Criterion, and Martingale. Each works as a standalone utility while fitting into a broader product framework for education, engagement, and conversion. Two modes were designed, Minimal (core calculation only) and Full (visualisations, contextual offers, history, explanations), allowing users to choose depth based on intent while keeping the default experience accessible for beginners.

The commercial logic: calculators create return visits (users come back before each bet), contextual operator offers appear at the moment of maximum purchase intent, and the tools establish the site as genuinely useful rather than purely promotional.

Outcome

Qualitative assessment of the work.

The sports product work applied one framework to data-driven products: lead with the decision the user needs to make, not with the data available to support it. This distinction, decision-led rather than data-led, framed each of the redesigns.

The comparison-first redesign of team rankings and the progressive disclosure model in projections aimed to reduce the cognitive load required to reach a comparison outcome, the specific task that DFS and betting users arrive to complete. The NHL line combinations redesign preserved the mental model that hockey fans bring to the page, aiming to reduce reorientation time on mobile by maintaining the familiar spatial grouping of lines and pairs.

The Community Predictions concept set out a strategic opportunity: converting passive data consumers into active participants, and using that participation as a first-party data signal for editorial prioritisation and product personalisation. If implemented, it represents the transition from Lineups as a data tool to Lineups as an engagement platform, a fundamentally different product value proposition.