Mateo Kovacic

His repeatable signature. A step only appears if its reliability score (sample size × match coverage) reaches at least Medium confidence — pattern mining, not anecdotes.

Red fill = raw touch territory. Gold rings = zones where his influence (xT added, progression, line-breaks, key passes) outweighs how often he's actually there — one combined map instead of two separate maps to compare by eye. Red with no ring: present but not dangerous. A ring on faint red: rare touches, outsized impact.

23 tracked carries (20.1/90, 1 progressive, 205m total) — the ball moving with his touches, a different signal from dribbles below (beating an opponent 1v1). this counts every touch-carry, not just his dribble attempts below — a fuller picture of how much of his ball-carrying is control-and-move rather than beating a man.

Only 5 dribbles attempted this season — too little volume to map a location pattern.

3 key passes (2.62/90), 0 of them assists — where his chance creation specifically comes from, 18 zones (6×3), showing his share of key passes originating there.

The zones where Mateo Kovacic gets on the ball — his top three ball-collection areas highlighted (gold = primary). Reception is proxied by where his on-ball actions begin (no explicit receiver is recorded).

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Mateo Kovacic actually gets on the ball. Hover any zone for its breakdown by action type, its share of all touches, and the exact coordinate range it covers.

Every pass this season, plotted individually — green = completed, grey (dashed) = incomplete, gold = key pass. Filter by outcome or isolate one match below.

Three clustered sequence diagrams from his own event data — his three busiest routes: the way he progresses, the pattern behind his chances, and where a turnover turns dangerous.

Man City's output per match with Mateo Kovacic (3 matches) versus without him (5 matches). Insufficient evidence — the without-sample is only 5 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.

Of everything Man City produced this season, the categories where the biggest share ran through Mateo Kovacic specifically — his share of the team total, not a per-90 rate.

Not raw event counts — football style scores: weighted models scored 0–100 against the 433 central mids in the pool (min 180 min). This is what separates players who post similar numbers but play differently. Proxy dimensions are inferred from on-ball data; true off-ball running / under-pressure context is not measured.

Closest comparables measured on the style scores above, within the same position family — so it separates how players are alike, not just how much they touch the ball. Each line explains the shared strength and the divergent mechanism. A light physical-profile term (height / weight; this player: 177 cm / 78 kg) is included at a quarter of one style axis's weight — enough to break ties between stylistic twins, not to override style. Scope: pooled across the Premier League, Bundesliga, La Liga, Ligue 1 and Serie A, percentiled within each player's own league before comparing — a match from another league is marked with its league name.

Style, not quality: a high match here means two players tend to produce the ball in similar ways — it is not a ranking, a scouting recommendation, or a claim that they are equally good.

Mateo Kovacic is a deep-lying playmaker / tempo controller: 6.1 progressive passes, 2.62 key passes /90, 0 box entries, 0 goals from 0.00 xG. A box-to-box contributor across every phase.