Thin sample this season. Emam Ashour has played 1 match (31 min) so far, so sections that need a bigger sample to say anything reliable are not shown here — they are missing on purpose, not broken. See all seasons combined →
Part 1
Overview
The headline read on him, and how he compares to his peers.
01
What Patterns Define Him?
His repeatable signature. A step only appears if its reliability score (sample size × match coverage) reaches at least Medium confidence — pattern mining, not anecdotes.
RECEIVE
Left Wing, Middle third — between the lines — mostly in the middle third (67% of his 15 passes)
60% completion · 15× in 1/1 matches
↓
TURN / BEAT MAN
face forward in the pocket
100% won · 1× in 1/1 matches
↓
FINISH
arrive and shoot from central zones
0 goals · 0.03 xG · 1× in 1/1 matches
Signature: Receive → Turn / Beat Man → Finish — the only steps proven repeatable this season (3 of 4 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: create — 0× (insufficient confidence, hidden — not enough evidence yet) — omitted from the signature rather than presented as one.
Part 2
Team Context
How much of the team's output runs through him, and what changes when he isn't on the pitch.
02
Impact on the Team
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.
WITH (1)
WITHOUT (18)
Δ
goals for /match
1.00
2.00
-1.00
xG for /match
1.29
0.00
+1.29
goals against /match
1.00
0.67
+0.33
points /match
1.00
0.50
+0.50
03
His Share of the Team
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.
category
share
him / team
shots
14%
55 / 390
successful take-ons
12%
16 / 138
expected assists (xA)
8%
2.6 / 31.4
Part 3
Recruitment
Style profile, closest comparables, and the summary verdict.
04
Playing-Style Profile
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.
Advanced playmaker (8)85%Half-space creator85%
Why Advanced playmaker (8) 85%: a weighted blend of creativity 86 (weight 35%) + progression 89 (weight 25%) + final-third threat 87 (weight 25%) + box threat 72 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
aerial ability, marking, off-ball running — not in event data
Carrying
97
Transition ~proxy
95
Retention
92
Ball-winning
90
Progression
89
Passing directness
88
Final-third threat
87
Dribbling
86
Creativity
86
Line-breaking
85
Receiving zones
84
Press resistance ~proxy
82
Through-balls ~proxy
78
Build-up
77
Box threat
72
Crossing
66
Defensive aggression
60
Territory (wide vs central)
17
05
Similar Players — in style space
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.
Azzedine Ounahi Girona · La Liga
96%
Driven by: transition (13%), carrying (10%), press resistance (9%). Different mechanism — Ashour more via ball-winning.
Arda Güler Real Madrid · La Liga
93%
Driven by: retention (9%), transition (9%), creativity (9%). Different mechanism — Ashour more via carrying; Güler more via crossing.
Marcus Tavernier Bournemouth · Premier League
89%
Driven by: transition (16%), creativity (10%), ball-winning (10%). Different mechanism — Ashour more via retention, line-breaking; Tavernier more via territory (wide vs central).
Matheus Cunha Man Utd · Premier League
89%
Driven by: transition (17%), carrying (11%), ball-winning (11%). Different mechanism — Ashour more via line-breaking, through-balls; Cunha more via territory (wide vs central).
Florian Wirtz Liverpool · Premier League
88%
Driven by: retention (10%), press resistance (9%), receiving zones (9%). Different mechanism — Ashour more via carrying, transition; Wirtz more via territory (wide vs central), crossing.
Xavi Simons RBL · Premier League
85%
Driven by: transition (11%), ball-winning (11%), creativity (10%). Different mechanism — Ashour more via box threat, dribbling; Simons more via territory (wide vs central).
06
Summary
Emam Ashour is an advanced playmaker (8) / half-space creator: 0.00 key passes /90, 5.8 progressive passes, 0 goals from 0.03 xG. A between-the-lines creator. [Off-ball movement into pockets needs tracking.]
Based on 1 matches (31 minutes) — an early read, treat with caution until more minutes are logged. He profiles as an advanced playmaker (8) / half-space creator — best used in a system built around that identity.
His biggest room for growth is box threat — even a modest improvement there would meaningfully lift his overall advanced playmaker (8) profile.
✨ This report is interactive
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.