His repeatable signature. A step only appears if its reliability score (sample size × match coverage) reaches at least Medium confidence — pattern mining, not anecdotes.
Signature: Link → Finish — the only steps proven repeatable this season (2 of 4 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: receive / move — 2× (low confidence, shown as a number only, no tactical conclusion drawn); convert — 0× (insufficient confidence, hidden — not enough evidence yet) — 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.
11 tracked carries (2.7/90, 5 progressive, 113m 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 11 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 7m, longest 22m
By zone — where the carry started → where it ended
First (11)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Dribbles (1v1s)
Does he drop to link or stay central? Touches by channel. Season rate: 1.78 dribbles attempted /90.
brighter band = more dribbles · own goal left, attacking →
INSIDE 88%
OUTSIDE 12%
Dribble location — 7 inside · 1 outside
Right Wing
0 · 0%
Right Half-Space
2 · 25%
Central
3 · 38%
Left Half-Space
2 · 25%
Left Wing
1 · 12%
Vision AI His touches are central and high — a penalty-box striker.
03
How does he create chances?
4 key passes (0.98/90), 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 (4)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 (4)from the right (0)of 4 key passes landing in the final thirdattacking ↑ toward goal
04
Where does he become vulnerable?
26 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.
18
attacking third (cheap)
7
middle third
1
own third (dangerous)
Vision AI 69% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 1.23 danger-index/90 · 0.193 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
02
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 4 key passes, his busiest route is a delivery where he switches it out from the central to the right hs, advancing it forward in the middle 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 left half-space in the final third: 43% of his 14 touches there are lost (6 times).
23 defensive actions across the season (5.6/90). 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 →
2
tackles · 50% won
0
interceptions · 0.0/90
5
recoveries · 1.2/90
0
clearances · 0.0/90
2
blocks
57
avg action height
6
won high (att 3rd)
13
middle third
4
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 7 proactive ball-wins (1.7/90), tackle success 50%. 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.
13
attacking-half actions · 3.17/90
06
Against Different Pressing Intensities
Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Elye Wahi keep producing when the game is tight and the press is high? Tiers of ~3-4 matches — directional evidence, not proof.
press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 4.8, 3m)
0.28
1.6
0.00
50%
Mid press (PPDA 7.9, 3m)
0.84
1.4
2.81
0%
Low press (PPDA 10.0, 4m)
0.31
1.4
0.95
0%
Team
Team context
How much of the team runs through him, and what changes without him.
Nice's output per match with Elye Wahi (10 matches) versus without him (24 matches). A proper on-off model needs many more minutes.
WITH (10)
WITHOUT (24)
Δ
goals for /match
2.50
1.50
+1.00
xG for /match
1.44
0.07
+1.37
goals against /match
2.00
1.88
+0.12
points /match
1.90
1.04
+0.86
09
His Share of the Team
Of everything Nice produced this season, the categories where the biggest share ran through Elye Wahi specifically — his share of the team total, not a per-90 rate.
category
share
him / team
expected goals (xG)
12%
6.3 / 51.9
shots
9%
42 / 484
zone-14 entries
5%
13 / 237
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 299 strikers 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.
Why Target man 43%: a weighted blend of box threat 42 (weight 50%) + final-third threat 51 (weight 30%) + retention 46 (weight 20%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
aerial ability, marking, off-ball running — not in event data
Defensive aggression
57
Carrying
56
Crossing
56
Final-third threat
51
Build-up
47
Territory (wide vs central)
47
Retention
46
Progression
46
Box threat
42
Receiving zones
41
Through-balls ~proxy
41
Line-breaking
38
Transition ~proxy
36
Press resistance ~proxy
35
Creativity
32
Dribbling
28
Passing directness
22
Ball-winning
20
11
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: 184 cm / 74 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.
Roberto Fernández Espanyol · La Liga · 186 cm / 78 kg
71%
Driven by: passing directness (18%), dribbling (12%), ball-winning (12%). Different mechanism — Wahi more via final-third threat, carrying.
Hugo Duro Valencia · La Liga · 177 cm / 70 kg
69%
Driven by: dribbling (16%), transition (15%), passing directness (14%). Different mechanism — Wahi more via carrying, final-third threat.
Kevin Carlos Cagliari · Serie A · 186 cm / 98 kg
68%
Driven by: ball-winning (21%), creativity (17%), press resistance (12%). Different mechanism — Wahi more via receiving zones, carrying; Carlos more via through-balls.
Andrea Pinamonti Lazio · Serie A · 188 cm / 72 kg
68%
Driven by: ball-winning (19%), transition (15%), dribbling (14%). Different mechanism — Wahi more via carrying, final-third threat; Pinamonti more via build-up.
Nikola Stulic Lecce · Serie A · 188 cm / 80 kg
66%
Driven by: passing directness (15%), dribbling (13%), transition (13%). Different mechanism — Wahi more via carrying, progression; Stulic more via ball-winning.
Rasmus Højlund Napoli · Serie A · 191 cm / 86 kg
66%
Driven by: ball-winning (40%), passing directness (19%), dribbling (9%). Different mechanism — Wahi more via territory (wide vs central), through-balls; Højlund more via creativity.
12
Summary
Elye Wahi is a target man: 0 goals from 0.89 xG (-0.89 vs expected), 7 shots, 2 box entries. Under-performing his chances. [Off-ball runs, aerials and hold-up under contact need tracking/aerial data.]
Based on 10 matches (369 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a target man — 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 target man 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.