His repeatable signature. A step only appears if its reliability score (sample size × match coverage) reaches at least Medium confidence — pattern mining, not anecdotes.
19 key passes (1.35/90), 2 of them assists — where his chance creation specifically comes from, 18 zones (6×3), showing his share of key passes originating there.
Four arrows, one per movement class of his ball-carries: outside→inside (cutting in with the ball), inside→outside (carrying wide), outside→outside (down the touchline) and inside→inside (through the middle). Each count is measured from the carry's real start and end coordinates.
Every carry's end point matched against his own very next pass or shot in the same match, when one starts almost exactly there — the direct continuation of that touch, not a separate stat. “No clean link” means no pass or shot of his own started close enough to count (often the carry ended in a tackle or a loss); it isn't a claim about exactly what happened, only that nothing traceable followed.
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.
The zones where Emam Ashour gets on the ball — his top three ball-collection areas highlighted (gold = primary). Reception is proxied by where his on-ball actions begin (the event feed gives no explicit receiver).
Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Emam Ashour 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.
Same zone grid, restricted to passes so completed/incomplete and match filters actually mean something — a shot or a dribble has no "completed" in the pass sense.
217 tracked carries (15.4/90, 53 progressive, 2223m 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.
Does he carry to create or drift wide? Dribbles by channel. Season rate: 2.70 dribbles attempted /90.
11 crosses (0.78/90, 8 completed) and 10 cutbacks (0.71/90, 3 completed) — two separate wide-delivery patterns into the box, each its own map with a completed/failed filter. Neither is a tagged event on this data source, so both are inferred from pass geometry — the intended end point of a failed attempt is still real data (an interception doesn’t erase where the ball was aimed): a cross is a pass aimed into the box starting from a wide channel; a cutback starts almost on the byline but is squared back rather than driven forward, aimed centrally around the box. The completed-cross count was checked against this platform’s own real match-level cross totals and lands within about 1 cross of the true count.
How much he drives the ball forward. Progressive = completed pass advancing ≥15 toward goal.
55 shots · 1.97 xG · 5 goals (+3.03 vs xG). Mostly right-footed. Circle size = xG.
His progressive passes as zone→zone routes, weighted by expected threat (xT) added — arrow width and the number are the total xT generated on each route, not just how often he plays it. This is where he actually moves the needle.
112 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.
Every pass this season, plotted individually — green = completed, red = incomplete, gold = key pass. Filter by outcome or isolate one match below.
How he moves the ball — his 4 busiest progression routes, not where every pass starts and ends separately. Arrow width = how often, colour = xT gained, dashed = switch of play. The full breakdown is in the lane matrix below.
Primary route: the left half-space in the middle third → the left half-space in the final third — 5 progressive passes (8% of his progression) at 0.122 xT each. He keeps it in the same lane.
His progression is inward: 54% of progressive passes move the ball toward the middle versus 8% going wider — he cuts in rather than holding width.
9% of his passes are cross-field switches — he changes the point of attack often.
Quality behind the volume: 27 line-breaking passes and 69 final-third entries, 9.4 total xT added.
Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Emam Ashour keep producing when the game is tight and the press is high? Tiers of ~4-5 matches — directional evidence, not proof.
98 defensive actions across the season (7.0/90). Where he wins the ball, and how — the core question for a defender. Aerial duels are not in the event feed, so aerial dominance is not measured here.
Ball-wins in the attacking half only (own half vs. attacking half, a simple 2-way split, not the usual thirds) — the clearest single signal of how much he presses and recovers the ball high up the pitch.
Al Ahly FC's output per match with Emam Ashour (1 matches) versus without him (18 matches). Insufficient evidence — the without-sample is only 18 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.
Of everything Al Ahly FC produced this season, the categories where the biggest share ran through Emam Ashour specifically — his share of the team total, not a per-90 rate.
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.
Not raw event counts — football style scores: weighted models scored 0–100 against the 221 attacking mids in the league (min 450 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. Scope: pooled across the Premier League, La Liga and the Egyptian Premier League, 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.
Emam Ashour is an advanced playmaker (8) / half-space creator: 1.35 key passes /90, 4.5 progressive passes, 5 goals from 1.97 xG. A between-the-lines creator. [Off-ball movement into pockets needs tracking.]
Click any stat card to filter its map, hover a dot for the exact match, and use the dropdowns to slice passes zone-to-zone. Nothing here is static.