Thin sample this season. Sam Amo-Ameyaw has played 7 matches (276 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 →
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
Right Wing, Attacking third — mostly in the attacking third (43% of his 82 passes)
Signature: Receive → Carry / Beat Man → Create / 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: progress — 2× (low confidence, shown as a number only, no tactical conclusion drawn) — omitted from the signature rather than presented as one.
In possession
In possession
What he does with the ball: build-up, progression, creation, carrying and finishing.
47 tracked carries (15.3/90, 9 progressive, 556m 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.
progressivelateral/short% of his 47 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 9m, longest 37m
By zone — where the carry started → where it ended
First (24)Second (15)Third (8)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Dribbles (1v1s)
Sam Amo-Ameyaw's signature is the dribble. Does he carry outside (down the right wing) or inside (into the half-space / centre)? Every dribble classified by channel. Season rate: 6.85 dribbles attempted /90.
brighter band = more dribbles · own goal left, attacking →
INSIDE 33%
OUTSIDE 67%
Dribble location — 7 inside · 14 outside
Right Wing
14 · 67%
Right Half-Space
5 · 24%
Central
1 · 5%
Left Half-Space
1 · 5%
Left Wing
0 · 0%
Vision AI 67% of his dribbles are in the wide right lane — he attacks the full-back on the outside, then threatens to cut inside onto his left foot.
04
How does he create chances?
2 key passes (0.65/90), 0 of them assists — where his chance creation specifically comes from, 18 zones (6×3), showing his share of key passes originating there.
Chance creation — key pass origin zone share
Filter:
chance creation (2)assist (0)% of the selected group's key passes originating in each zone
Box deliveries — key passes reaching the final third, by flank
from the left (1)from the right (1)of 2 key passes landing in the final thirdattacking ↑ toward goal
08
Where does he become vulnerable?
36 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.
22
attacking third (cheap)
6
middle third
8
own third (dangerous)
Vision AI 61% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 3.08 danger-index/90 · 0.263 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
02
Where Does He Operate? — Every Zone
Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Sam Amo-Ameyaw 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.
Filter:
own goal left, attacking → · brighter + higher number = more touches
Passes only — completed vs incomplete, by zone
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.
own goal left, attacking →
07
Tactical patterns — how his football actually looks
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.
own goal left, attacking →
Where do his chances come from?
Of 2 key passes, his busiest route is a delivery where he plays straight through the central in the final third — 1 times. The receiver isn't identifiable in this data, only where the pass started and ended.
Where does he lose the ball most?
This is a RATE, not a raw count — the share of his touches in each zone that end in a turnover, so a zone he simply plays in more often doesn't automatically look riskier. His weakest zone is the right half-space in the final third: 56% of his 9 touches there are lost (5 times).
06
Does he carry inside or outside — his ball-carries across the pitch
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.
own goal left, attacking →
Across 47 ball-carries, his dominant tendency is that he drives along the touchline (45%). He carries from outside into the middle 14 times and out toward the touchline 1 — a genuine inside forward who cuts in with the ball.
05
What happens right after he carries the ball
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.
Shot
3 · 6%
Progressive / key pass
6 · 13%
Simple pass
21 · 45%
No clean link
17 · 36%
Of 47 carries, 6% flow straight into a shot of his own, 13% into a key or progressive pass — a genuine end product to the carry, not just ball retention. 36% have no clean link to a next touch of his own close to where the carry ended.
31 defensive actions across the season (10.1/90). Where he wins the ball, and how — the core question for a defender. Aerial duels are not recorded for this competition, so aerial dominance is not measured here.
click a card to isolate that action type · own goal left, attacking →
1
tackles · 0% won
3
interceptions · 1.0/90
13
recoveries · 4.2/90
0
clearances · 0.0/90
2
blocks
47
avg action height
9
won high (att 3rd)
11
middle third
11
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 17 proactive ball-wins (5.5/90), tackle success 0%. He defends high, stepping out to intercept — suits a high line.
Defensive work in the attacking half
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.
15
attacking-half actions · 4.89/90
09
Against Different Pressing Intensities
Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Sam Amo-Ameyaw keep producing when the game is tight and the press is high? Tiers of ~2-3 matches — directional evidence, not proof.
press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 3.7, 2m)
0.41
0.9
0.87
12%
Mid press (PPDA 5.0, 2m)
0.60
2.0
0.00
50%
Low press (PPDA 6.6, 3m)
0.74
0.0
0.70
44%
Team
Team context
How much of the team runs through him, and what changes without him.
Strasbourg's output per match with Sam Amo-Ameyaw (7 matches) versus without him (1 matches). Insufficient evidence — the without-sample is only 1 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.
WITH (7)
WITHOUT (1)
Δ
goals for /match
1.71
0.00
+1.71
xG for /match
1.27
0.00
+1.27
goals against /match
2.14
3.00
-0.86
points /match
1.00
0.00
+1.00
12
His Share of the Team
Of everything Strasbourg produced this season, the categories where the biggest share ran through Sam Amo-Ameyaw specifically — his share of the team total, not a per-90 rate.
category
share
him / team
goals
20%
2 / 10
successful take-ons
14%
35 / 242
box entries
8%
24 / 292
Recruitment
Style and verdict
Style profile, closest comparables, and the summary.
Not raw event counts — football style scores: weighted models scored 0–100 against the 180 wingers in the pool (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.
aerial ability, marking, off-ball running — not in event data
Carrying
90
Retention
80
Dribbling
75
Press resistance ~proxy
72
Build-up
69
Through-balls ~proxy
64
Territory (wide vs central)
60
Crossing
54
Transition ~proxy
52
Final-third threat
51
Defensive aggression
50
Ball-winning
48
Progression
47
Receiving zones
46
Line-breaking
44
Creativity
29
Box threat
26
Passing directness
8
14
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. A light physical-profile term (height / weight; this player: 174 cm / 64 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 Ligue 1, Bundesliga, La Liga, Premier League 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.
Ernest Poku Leverkusen · Bundesliga 25/26 · 173 cm / 63 kg
61%
Driven by: passing directness (30%), carrying (23%), retention (15%). Different mechanism — Amo-Ameyaw more via through-balls, ball-winning; Poku more via creativity, receiving zones.
Julio Díaz Sevilla · La Liga · 174 cm / 65 kg
60%
Driven by: passing directness (17%), retention (17%), box threat (15%). Different mechanism — Amo-Ameyaw more via carrying, through-balls; Díaz more via territory (wide vs central), ball-winning.
Mohammed Kudus Tottenham · Premier League · 177 cm / 70 kg
57%
Driven by: dribbling (24%), press resistance (23%), box threat (15%). Different mechanism — Amo-Ameyaw more via carrying, line-breaking; Kudus more via ball-winning, passing directness.
Jean-Mattéo Bahoya Leeds · Bundesliga · 180 cm / 75 kg
55%
Driven by: carrying (19%), press resistance (17%), dribbling (17%). Different mechanism — Amo-Ameyaw more via through-balls, crossing; Bahoya more via creativity, ball-winning.
Tyrique George Everton · Premier League · 181 cm / 75 kg
54%
Driven by: carrying (22%), retention (21%), press resistance (21%). Different mechanism — George more via creativity, passing directness.
Amad Diallo Man Utd · Premier League · 173 cm / 72 kg
52%
Driven by: retention (23%), build-up (22%), passing directness (18%). Different mechanism — Amo-Ameyaw more via through-balls, dribbling; Diallo more via creativity, receiving zones.
15
Summary
Sam Amo-Ameyaw is a wide, outside-first right carrier: 67% of dribbles in the wing lane, 62% of passes from wide — but 63% land inside. 0.7 progressive passes and 0.65 key passes /90 plus 2 goals from 0.54 xG. A carry-and-deliver threat.
Based on 7 matches (276 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a wide dribbler / isolator — 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 wide dribbler / isolator 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.