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Player reportBundesliga 2025/26

Nico Elvedi

Leeds
Stopper centre-back CB
17.5 defensive actions/90 · 4.2 progressive/90 — defends first
centre-backball-playing centre-backbuild-upline-breaking
3144
minutes
33 apps
1823
passes
92% completed
92%
pass completion
1823 passes
148
progressive passes
4.2/90
106
line-breaking passes
3.0/90
611
defensive actions
17.5/90
84
tackles + interceptions
67% tackle win
273
clearances
7.8/90
Overview

The player

Who he is and how he compares with 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
in the first line of build-up — mostly in the middle third (49% of his 1823 passes)
92% completion · 1823× in 33/33 matches
↓
BREAK A LINE
vertical pass past the opponent midfield
4.2 prog/90 · 106× in 32/33 matches
↓
SWITCH PLAY
diagonal to the far side
cross-field balls · 36× in 20/33 matches
↓
PROGRESS
entries into the final third
2.6/90 · 91× in 29/33 matches
Signature: Receive → Break A Line → Switch Play → Progress — the only steps proven repeatable this season (4 of 5 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: carry out — 8× (low confidence, shown as a number only, no tactical conclusion drawn) — omitted from the signature rather than presented as one.
17

Where is he influential — vs where is he merely present?

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.

own goal left, attacking →
55
passes / match
17.5
def actions / 90
11–97
pass range (matches)
273
clearances
Pass range = his fewest and most passes in any single match this season (11 at the low end, 97 at the high) — a measure of match-to-match involvement, not pass distance.
In possession

In possession

What he does with the ball: build-up, progression, creation, carrying and finishing.

10

How dangerous are his carries?

Real ball-carries

591 tracked carries (16.9/90, 193 progressive, 6116m total) — the ball moving with his touches, a different signal from dribbles below (beating an opponent 1v1). even a player who rarely dribbles past a man can still carry the ball forward constantly in build-up; this is that.

9%14%14%5%0%3%19%20%7%1%1%3%3%2%0%
progressivelateral/short% of his 591 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 8m, longest 43m
By zone — where the carry started → where it ended
45Outside → Inside
456Inside → Inside
52Outside → Outside
38Inside → Outside
First (208)Second (193)Third (113)Fourth (77)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →

Beaten in the tackle

How often an attacker gets past him in a 1v1 defensive duel — the closest signal the data has to "dribbled past" (no attacker-beat-defender field exists directly, so this counts tackles he attempted and lost).

43
tackle duels
29
won
14
beaten · 33%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 63%
OUTSIDE 37%
Tackle-duel location — 27 inside · 16 outside
Right Wing
11 · 26%
Right Half-Space
8 · 19%
Central
8 · 19%
Left Half-Space
11 · 26%
Left Wing
5 · 12%
Vision AI beaten in 14 of 43 tackle duels (33% loss rate) — a solid 1v1 defensive record.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →

He attempted only 4 dribbles of his own all season — dribbling is not part of this role; his ball-carrying is covered above, his defending against the dribble below.

02

How does he build & move the ball?

How does he escape the first line?

10%
vertical passes
129×
2%
switches
30×
37%
carries
496×
50%
short circulation
668×
Answer: he escapes the press primarily through carrying — stepping out with the ball.

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.

own goal left, attacking →
Lane transition matrix — when he receives in a lane, where does it go?
TO →RWRHSCLHSLWRW21652%11224%5123%500%11%2RHS65743%28316%10434%2227%431%5C55010%5421%11735%19028%1546%35LHS1921%14%826%5026%4944%84LW612%12%116%1013%867%41FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: the right wing in the defensive third → the right half-space in the middle third — 8 progressive passes (10% of his progression) at 0.083 xT each. He moves it inside.

His progression is inward: 47% of progressive passes move the ball toward the middle versus 9% going wider — he cuts in rather than holding width.

Only 6% of his passes switch play, so his threat is same-side — contain the flank he occupies and the route closes.

Quality behind the volume: 16 line-breaking passes and 91 final-third entries, 19.3 total xT added.

Origin and destination are measured on the same event row — no receiver inference. Receiver identity is not recoverable from this data source.
All passes — origin zone share
Filter: from to
8%14%13%7%2%0%4%15%16%7%1%0%2%4%3%3%1%0%
completedincomplete1823 passes · any zone → any zone · own goal left, attacking →
1823
passes
92%
completed
147
lost
Vision AIIn line with his 92% season completion rate.
03

How does he progress play?

How much he drives the ball forward. Progressive = completed pass advancing ≥15 toward goal.

148
progressive · 4.2/90
91
final-third entries · 2.6/90
8
box entries · 0.23/90
19
progression index /90
Progression index: one composite number — progressive passes + progressive carries + 2% of total distance progressed + 8× positive xT added, all per 90. Weights VOLUME and THREAT together rather than counting progressive actions alone.
12

How does he create chances?

12 key passes (0.34/90), 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:
8%8%25%17%17%8%17%
chance creation (12)assist (0)% of the selected group's key passes originating in each zone
06

Where does he become vulnerable?

150 times he gave the ball away. For a defender the danger is where — a loss in his own third can turn into a chance against; higher up it costs little.

19
attacking third (cheap)
63
middle third
68
own third (dangerous)
Vision AI 13% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 2.14 danger-index/90 · 0.499 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
05

What is his passing profile?

1823
passes attempted
45%
mostly forward
48%
mostly short
Direction
Forward
829 · 45%
Sideways
699 · 38%
Backward
295 · 16%
Length (completed)
Short (<15m)
808 · 48%
Medium
804 · 48%
Long (>30m)
64 · 4%
07

Preferred Progression Routes — xT-weighted

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.

0.990.950.930.850.750.57
own goal left, attacking →
Highest-value routes (xT)
0.99
Right Half-Space Mid third → Right Wing Mid third
17 passes
0.95
Right Wing Def third → Right Wing Mid third
17 passes
0.93
Right Half-Space Mid third → Central Att third
4 passes · 1 to a shot
0.85
Right Wing Def third → Right Half-Space Mid third
9 passes
0.75
Right Half-Space Mid third → Left Half-Space Att third
3 passes
0.57
Right Half-Space Mid third → Right Half-Space Mid third
7 passes
08

Where Does He Receive?

The zones where Nico Elvedi 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).

123
1 = primary, 2 = secondary, 3 = third · own goal left, attacking →
His collection zones
20%
Primary
Right Half-Space, Middle third
17%
Secondary
Central, Middle third
16%
Third
Right Half-Space, Defensive third
These are the zones where he collected the ball most.
09

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Nico Elvedi 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:
32655062154652732971242015154257236126356
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.

8%14%13%7%2%0%4%15%16%7%1%0%2%4%3%3%1%0%
own goal left, attacking →
11

Every Pass This Season — completed vs incomplete

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

12Key pass
1Cross
3Cutback
148Progressive
106Long ball
36Switch
By zone — where the pass started → where it landed
121Outside → Inside
937Inside → Inside
156Outside → Outside
462Inside → Outside
By direction
829Forward
295Backward
699Sideways
own goal left, attacking →
04

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 →
How does he progress the ball forward?
His most common route for progressing play: he switches it out from the right hs to the right wing in the middle third — 17 passes worth 0.99 xT.
Where do his chances come from?
Of 12 key passes, his busiest route is a delivery where he switches it out from the central to the right hs in the final third — 2 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 central in the final third: 33% of his 21 touches there are lost (7 times).
18%28/155 lost5%15/300 lost2%6/264 lost9%7/82 lost31%12/39 lost12%10/82 lost5%17/366 lost8%24/302 lost6%7/114 lost12%4/33 lost0%0/17 lost21%6/29 lost33%7/21 lost23%3/13 lost—6 touches · too fewRWRHSCLHSLWDEFMIDATT
Out of possession

Out of possession

Where and how he defends and presses.

13

How & where does he defend?

611 defensive actions across the season (17.5/90). 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 →
43
tackles · 67% won
41
interceptions · 1.2/90
104
recoveries · 3.0/90
273
clearances · 7.8/90
9
blocks
25
avg action height
27
won high (att 3rd)
123
middle third
461
own third
Vision AI A deep-defending defender. He wins the ball mainly by clearing and blocking — a reactive, protect-the-box profile. 188 proactive ball-wins (5.4/90), tackle success 67%. He defends deep, protecting his box — a last-line stopper.
14

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Nico Elvedi still play out when the opponent presses high? His build-up quality split by press intensity — the key question for a ball-playing defender. Tiers of ~11-11 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 4.5, 11m)
89%
4.1
3.5
0.73
Mid press (PPDA 5.7, 11m)
93%
4.0
2.7
0.85
Low press (PPDA 8.1, 11m)
94%
4.6
2.9
1.01
Team

Team context

How much of the team runs through him, and what changes without him.

15

Impact on the Team

Leeds's output per match with Nico Elvedi (33 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. What his own defending should move — goals conceded and results — leads; attacking output (largely out of a defender's hands) is shown after, for context. A proper on-off model needs many more minutes.

WITH (33)
WITHOUT (1)
Δ
goals against /match
1.52
3.00
-1.48
points /match
1.15
0.00
+1.15
goals for /match
1.24
1.00
+0.24
xG for /match
1.25
0.00
+1.25
16

His Share of the Team

Of everything Leeds produced this season, the categories where the biggest share ran through Nico Elvedi specifically — his share of the team total, not a per-90 rate.

category
share
him / team
clearances
24%
300 / 1254
interceptions
12%
46 / 383
final-third entries
10%
146 / 1485
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

18

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 513 centre-backs 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.

Ball-playing centre-back67%Stopper centre-back46%
Why Ball-playing centre-back 67%: a weighted blend of retention 78 (weight 30%) + build-up 75 (weight 30%) + progression 39 (weight 25%) + press resistance 48 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
—
Strong
retention, carrying, build-up
Average
transition, crossing, passing directness, creativity, final-third threat, press resistance, ball-winning
Weak
progression, receiving zones, defensive aggression, dribbling, box threat, line-breaking, through-balls, territory (wide vs central)
Unknown
aerial ability, marking, off-ball running — not in event data
Retention
78
Carrying
77
Build-up
75
Transition ~proxy
65
Crossing
65
Passing directness
59
Creativity
51
Final-third threat
50
Press resistance ~proxy
48
Ball-winning
45
Progression
39
Receiving zones
37
Defensive aggression
35
Dribbling
25
Box threat
22
Line-breaking
20
Through-balls ~proxy
19
Territory (wide vs central)
17
19

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: 189 cm / 84 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.

Andrew Omobamidele Strasbourg · Ligue 1 · 188 cm / 78 kg
80%
Driven by: build-up (17%), dribbling (12%), territory (wide vs central) (10%). Different mechanism — Elvedi more via crossing, final-third threat; Omobamidele more via build-up, passing directness.
Carl Starfelt Celta Vigo · La Liga · 185 cm / 83 kg
79%
Driven by: build-up (18%), territory (wide vs central) (14%), retention (13%). Different mechanism — Elvedi more via final-third threat, crossing; Starfelt more via passing directness.
Victor Lindelöf Aston Villa · 187 cm / 82 kg
74%
Driven by: build-up (14%), dribbling (14%), defensive aggression (12%). Different mechanism — Elvedi more via ball-winning, passing directness.
Francesco Acerbi Inter · Serie A 25/26 · 192 cm / 88 kg
73%
Driven by: retention (19%), build-up (16%), territory (wide vs central) (15%). Different mechanism — Elvedi more via passing directness, transition; Acerbi more via receiving zones, line-breaking.
Carlos Domínguez Celta Vigo · La Liga 25/26 · 187 cm / 81 kg
73%
Driven by: build-up (17%), dribbling (17%), territory (wide vs central) (16%). Different mechanism — Elvedi more via carrying, crossing; Domínguez more via passing directness, receiving zones.
Ezri Konsa Arsenal · 183 cm / 76 kg
70%
Driven by: build-up (15%), retention (15%), line-breaking (13%). Different mechanism — Elvedi more via crossing, ball-winning; Konsa more via dribbling, receiving zones.
20

Summary

Nico Elvedi is a ball-playing centre-back: 92% pass completion, 106 line-breaking passes and 4.2 progressive passes /90. A build-and-progress centre-back whose value is in beating the first line with the pass, not in raw defensive volume. [Aerial duels, marking, line-height and 1v1 recovery need aerial-event + tracking data, absent here.]

Based on 33 matches (3144 minutes) this season — a reliable read. He profiles as a ball-playing centre-back — best used in a system built around that identity. His biggest room for growth is progression — even a modest improvement there would meaningfully lift his overall ball-playing centre-back 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.

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