Dreamteam — Esports Analytics for 1.2M+ Players

Role: Sr. UX Designer Timeline: Oct 2018 – Dec 2019 (~15 months) · Industry: Esports · gaming analytics Scope: Coaching platform, navigation & IA, skill tree, premium flows, research

Dreamteam was the largest esports recruitment platform — 1.2M+ users, partnerships across Fnatic, NAVI, Faceit and ESL. On top of recruitment sat an analytics platform that had to turn complex in-game data into actionable insight for three audiences: players, teams and coaches.

Esports tooling drowned players in numbers — K/D, ADR, win rates across titles — without telling anyone what to do with them.

Players treated analytics as a post-match scoreboard: looked once, felt judged, left.

Coaches gave sharp feedback that lived in Discord and docs, disconnected from the gameplay it referred to — so most of it was never acted on.

One data model was stretched across three audiences, so nobody's view felt built for them.

Live interviews with players, teams and coaches across CS:GO and Apex, plus task tests: show a real post-match breakdown, ask "what would you change next game?"

The surprise: the highest-ranked players used the stats least — they already knew their next move. Mid-tier players, the bulk of the base, wanted direction the product never gave them.

Scattered stats → a visible path → your next move.

Skill Tree over a stat wall. A visual progression system for tracking and developing skills across titles, with advanced metrics moved to a secondary view. Players came back to work on a named skill rather than glance at a score.

Coaching that gets applied. An end-to-end loop where players receive, track and apply coach feedback in one place, tied to the gameplay it referenced.

Premium discovery without resentment. Upgrade flows and locked states that taught rather than blocked, so players felt the value before the paywall.

18% → 41% weekly return to the analytics surface

1 in 5 → 68% of coach notes acted on

+44% premium conversion, driven by high-intent players

1.2M+ users on the platform

North-star: players who improved their rank — not players who viewed stats.

Treat the recommendation logic as a core experience constraint from day one, not a layer added after the visuals. Recommendation quality is the product.