Ask a grounded football analyst any question, or open a full player or team report — position-aware, sample-checked, built directly from event data across the Premier League, La Liga and Egyptian Premier League.
An AI analyst you can talk to, and a team-intelligence engine underneath it — every answer traces back to real event data, never a guess.
A grounded football analyst you can talk to — retrieves real numbers from the event database first, then explains what they mean tactically. Never invents a stat.
Weighted spatial maps, pressing behaviour, ball-loss zones and league-contextual style archetypes — the mechanism behind the results.
Find comparable players and teams by playing style, not raw counts — position-relative, with the archetype and the "why" behind every match.
The same intelligence engine runs across every competition. Premier League, La Liga and the Egyptian Premier League are fully loaded now; Serie A, Bundesliga, Ligue 1 and the Saudi Pro League are next.
How the analysis actually works — methodology, mistakes we caught, and what changed.
Raw-metric clustering let Federico Valverde and Frenkie de Jong land in the same bucket. That's not a fluke — it's what happens when you cluster event counts instead of playing style.
2026-07William Saliba, Virgil van Dijk and Gabriel Magalhães were all classified as full-backs by our own model. The bug wasn't in the players — it was in assuming a centre-back sits dead-centre.
2026-07Early versions gave every player the same fifteen sections — a centre-back's report included a shot map built on four attempts all season. The fix was to make the report decide what it should contain.
2026-07A different product from the AI Analyst above: pairs the chat analyst with match video and full event data for a single player, in one combined read. Not the data-only reports available today — a deeper product, still being built.