Case study · OP.GG Player Intelligence

Turning match history into player intelligence.

We designed and built an interactive League of Legends dashboard that connects one 100-match snapshot to trends, filters, relationships, sessions, and source-linked match detail.

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OP.GG Player Intelligence overview for Doublelift with ranked summary, recent games, global filters, and trend controls

Project type

Web applicationProduct concept

Industry

Gaming analyticsEsports

Capabilities

Product strategyUX/UI designData visualizationFront-end development

The challenge

The data was available. The story was buried.

A player profile can hold rank, champion history, individual games, sessions, teammates, opponents, and dozens of performance signals. The challenge was not adding another statistic. It was helping someone understand what those records mean together.

We set out to make the first five seconds useful, then keep deeper evidence close for anyone who wanted to investigate a trend, teammate, champion, session, or match.

Win rate trajectory across the selected 100-match set with source availability, recent form, and connected analysis panels — **Connected trend analysis**
The selected match set drives the headline metrics, trend canvas, recent form, champion performance, sessions, relationships, and match history together.

What we built

One analytical system from overview to evidence.

The interface begins with the player, then gives every filter and deep-dive a clear relationship to the same imported match set. The result feels dense because the subject is dense, but each layer has a defined job.

✓A source-labeled overview for rank, LP, record, role, champion mix, and recent form ✓Seven global filter dimensions that recalculate the connected analytical views ✓Six metric views that mark unavailable source fields instead of estimating them ✓Reusable deep dives for matches, champions, teammates, sessions, and driver insights

Interaction design

Every conclusion stays close to the supporting evidence.

Compact controls keep the overview fast to scan. When someone wants more context, the same visual system opens a focused evidence workspace without losing the selected player or match set.

Focused Jinx versus Jhin match analysis with performance summary, both team rosters, item build, runes, and source coverage — **Match analysis**
A reusable deep-dive brings performance, both team rosters, item evidence, runes, and source coverage into one focused workspace.

Recently played with and teammate chemistry panels comparing shared games, record, win rate, and KDA — **Player relationships**
Together and against views separate shared performance from opponent history, so frequent names become useful analytical context.

Mobile OP.GG Player Intelligence overview with player identity, rank summary, range controls, and recent games

Responsive system

Dense information, without a squeezed desktop.

The compact desktop navigation becomes a full-width mobile menu. Player identity, range controls, filters, tables, and deep dives reflow into a purposeful single-column reading path.

Horizontal rails remain only where comparison needs them, while the page itself stays contained and every primary control remains reachable.

Data integrity

Show what the source supports. Leave the rest unavailable.

The concept uses the newest 100 visible Ranked Solo match cards captured from OP.GG on August 26, 2026. Result, champion, KDA, CS, duration, items, rosters, opponents, and source labels remain connected to those imported games.

Per-match LP movement, damage, gold, and timeline events were not present in the source cards. The interface labels those fields as unavailable instead of replacing them with zeroes or invented values.

The goal was not more data. It was a faster path to a useful conclusion.

Project lead

Brendan Collins

Brendan led the product strategy, information architecture, UX/UI design, data presentation, and front-end build for the player-intelligence concept.

The key judgment was deciding which facts could be shown directly, which patterns could be derived from the selected match set, and which values had to remain unavailable.