Stat Lab · Opta-style event data · 2010/11 → present

Stats out of context lie.Put them back in.

PITCHBOOK.IO lets you build custom efficiency metrics — like xG per 10 final-third entries or duels won per 100 minutes out of possession — and rank any player against their positional peers across Europe's top-5 leagues.

Example metric
xA per 10 Final-Third Touches · CFs · Ligue 1 · 2021/22
Subject: O. Dembélé → 96th percentile vs positional peers
Football-headed detective in a deerstalker hat inspecting two stat sheets with a magnifying glass
What it does

Three steps from a raw stat to real context.

01

Pick a numerator and a denominator

Goals, xG, xA, big chances, dribbles, duels won. Divide by minutes, touches, final-third entries, or time out of possession — whichever makes the stat fair.

02

Lock the subject's season

Search any player across Europe's top-5 leagues from 2010/11 to today and pick the exact season you want to analyse.

03

Rank against positional peers

Compare to the top-5 leagues' best, the best in the subject's own league, or a hand-picked player — with live percentile tiers.

Dataset integrity

Opta-style event data, top-5 leagues, 15+ seasons.

Premier League, La Liga, Serie A, Bundesliga, Ligue 1 — every season from 2010/11 to the current campaign. Advanced event metrics (xG, xA, progressive carries, final-third entries) start from 2017/18 in line with the underlying provider coverage.

Player-seasons
44,982
Distinct players
12,039
Leagues
Top 5
Coverage
2010/11 → 2025/26
More stats coming soon

Additional numerators and denominators — including richer goalkeeper, set-piece, defensive and pressing metrics — are being added on a rolling basis as the dataset expands.

Stop arguing with a single number.

Open the Stat Lab and build the metric that actually answers the question.

Launch Stat Lab
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