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Player reportLigue 1 2025/26

Nuno Mendes

PSG
Defensive full-back FB
12.3 defensive actions/90 · low final-third share 29%
full-backoverlapping full-backprogressioncrossing
1572
minutes
23 apps
87%
pass completion
1265 passes
119
progressive passes
6.8/90
131
final-3rd entries
7.5/90
23
box entries
1.32/90
214
defensive actions
12.3/90
41
tackles + interceptions
74% tackle win
64
dribbles
44% won
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
Left Wing, Middle third — wide or inverted — mostly in the middle third (52% of his 1265 passes)
87% completion · 1265× in 23/23 matches
↓
PROGRESS
carry or combine up the flank
6.8 prog/90 · 119× in 19/23 matches
↓
DRIBBLE
beat his man up the line
44% won · 64× in 22/23 matches
↓
DELIVER
cross or cut-back into the box
38 key passes · 23× in 14/23 matches
↓
DEFEND
1v1 and cover on his side
214 def actions · lost 19% deep · 214× in 23/23 matches
Signature: receive wide/inverted → progress the flank → deliver into the box → recover to defend 1v1. Attack the space behind him in transition.
19

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
12.3
def actions / 90
4–113
pass range (matches)
25
clearances
Pass range = his fewest and most passes in any single match this season (4 at the low end, 113 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.

08

How dangerous are his carries?

Real ball-carries

261 tracked carries (14.9/90, 75 progressive, 2583m 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.

0%0%0%0%1%2%1%4%2%2%18%27%23%15%3%
progressivelateral/short% of his 261 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 7m, longest 62m
By zone — where the carry started → where it ended
41Outside → Inside
99Inside → Inside
92Outside → Outside
29Inside → Outside
First (100)Second (90)Third (67)Fourth (4)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).

27
tackle duels
20
won
7
beaten · 26%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 37%
OUTSIDE 63%
Tackle-duel location — 10 inside · 17 outside
Right Wing
0 · 0%
Right Half-Space
1 · 4%
Central
5 · 19%
Left Half-Space
4 · 15%
Left Wing
17 · 63%
Vision AI beaten in 7 of 27 tackle duels (26% loss rate) — a solid 1v1 defensive record.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →

Dribbles (1v1s)

Does he carry outside (overlap) or inside (invert into midfield)? Every carry by channel. Season rate: 3.66 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 42%
OUTSIDE 58%
Dribble location — 27 inside · 37 outside
Right Wing
0 · 0%
Right Half-Space
0 · 0%
Central
4 · 6%
Left Half-Space
23 · 36%
Left Wing
37 · 58%
Vision AI 58% of his carries are wide — an overlapping full-back who hugs the touchline.
03

How does he build & move the ball?

How does he escape the first line?

15%
vertical passes
70×
9%
switches
42×
29%
carries
135×
46%
short circulation
213×
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 →RWRHSCLHSLWRW838%338%325%2RHS967%622%211%1C4120%822%932%1320%87%3LHS4242%77%2931%13322%9438%161LW6212%122%1410%6134%21052%324FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: the left wing in the final third → the left half-space in the final third — 20 progressive passes (15% of his progression) at 0.038 xT each. He moves it inside.

His progression is inward: 68% of progressive passes move the ball toward the middle versus 3% going wider — he cuts in rather than holding width.

8% of his passes are cross-field switches — he changes the point of attack often.

Quality behind the volume: 51 line-breaking passes and 131 final-third entries, 16.6 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
0%0%0%1%0%1%2%2%2%1%3%15%20%28%18%7%
completedincomplete1265 passes · any zone → any zone · own goal left, attacking →
1265
passes
87%
completed
162
lost
Vision AIIn line with his 87% season completion rate.
05

How does he progress play?

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

119
progressive · 6.8/90
131
final-third entries · 7.5/90
23
box entries · 1.32/90
31
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.
11

How does he create chances?

38 key passes (2.18/90), 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:
3%3%12%12%18%29%24%
chance creation (34)assist (0)% of the selected group's key passes originating in each zone
14

Can he finish?

34 shots · 3.55 xG · 4 goals (+0.45 vs xG). Mostly left-footed. Circle size = xG.

shots  34
on target  25
goals  4
xG  3.55
xG on target  4.81
xG / shot  0.104
Where he shoots from — click an area of the box
10

Where does he become vulnerable?

198 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.

87
attacking third (cheap)
73
middle third
38
own third (dangerous)
Vision AI 44% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 3.40 danger-index/90 · 0.300 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
12

What is his passing profile?

1265
passes attempted
40%
mostly forward
50%
mostly short
Direction
Forward
500 · 40%
Sideways
380 · 30%
Backward
385 · 30%
Length (completed)
Short (<15m)
555 · 50%
Medium
453 · 41%
Long (>30m)
95 · 9%
09

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.

1.891.030.920.710.690.69
own goal left, attacking →
Highest-value routes (xT)
1.89
Left Half-Space Mid third → Left Wing Att third
24 passes · 1 to a shot
1.03
Left Wing Mid third → Left Wing Att third
10 passes
0.92
Left Half-Space Mid third → Left Half-Space Att third
3 passes
0.71
Left Wing Att third → Central Att third
2 passes · 2 to a shot
0.69
Left Wing Mid third → Left Half-Space Att third
3 passes
0.69
Left Wing Mid third → Central Att third
2 passes · 1 to a shot
06

Where Does He Receive?

The zones where Nuno Mendes 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
27%
Primary
Left Wing, Middle third
22%
Secondary
Left Half-Space, Middle third
17%
Third
Left Wing, Attacking third
These are the zones where he collected the ball most.
07

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Nuno Mendes 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:
36204264364242108492526352522512
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.

0%0%0%1%0%1%2%2%2%1%3%15%20%28%18%7%
own goal left, attacking →
13

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.

38Key pass
18Cross
22Cutback
119Progressive
158Long ball
73Switch
By zone — where the pass started → where it landed
290Outside → Inside
289Inside → Inside
339Outside → Outside
185Inside → Outside
By direction
500Forward
385Backward
380Sideways
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 left hs to the left wing, advancing it forward in the middle third — 24 passes worth 1.89 xT.
Where do his chances come from?
Of 38 key passes, his busiest route is a delivery where he plays inside from the left hs toward the central in the final third — 12 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 wing in the final third: 36% of his 11 touches there are lost (4 times).
—0 touches · too few—1 touch · too few—7 touches · too few13%10/79 lost16%25/154 lost—1 touch · too few—7 touches · too few12%3/26 lost7%19/281 lost9%32/341 lost36%4/11 lost—3 touches · too few14%2/14 lost25%31/124 lost15%33/216 lostRWRHSCLHSLWDEFMIDATT
02

Crosses & Cutbacks

18 crosses (1.03/90, 8 completed) and 22 cutbacks (1.26/90, 11 completed) — two separate wide-delivery patterns into the box, each its own map with a completed/failed filter. Neither is a tagged event, 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.

Crosses — close-up on the final third
Cutbacks — close-up on the final third
completedfailed (dashed)close-up on the box — attacking ↑ toward goal
Out of possession

Out of possession

Where and how he defends and presses.

15

How & where does he defend?

214 defensive actions across the season (12.3/90). 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 →
27
tackles · 74% won
14
interceptions · 0.8/90
87
recoveries · 5.0/90
25
clearances · 1.4/90
20
blocks
37
avg action height
19
won high (att 3rd)
93
middle third
102
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 128 proactive ball-wins (7.3/90), tackle success 74%. He defends mostly around the middle third.
16

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Nuno Mendes 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 ~7-9 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 7.7, 7m)
86%
8.6
9.8
2.15
Mid press (PPDA 10.6, 7m)
87%
8.2
10.4
1.60
Low press (PPDA 16.4, 9m)
88%
4.4
7.6
1.49
Team

Team context

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

17

Impact on the Team

PSG's output per match with Nuno Mendes (3 matches) versus without him (5 matches). Insufficient evidence — the without-sample is only 5 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 (3)
WITHOUT (5)
Δ
goals against /match
0.67
1.40
-0.73
points /match
3.00
1.60
+1.40
goals for /match
2.00
2.00
+0.00
xG for /match
2.56
1.97
+0.59
18

His Share of the Team

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

category
share
him / team
expected assists (xA)
6%
2.2 / 35.1
successful take-ons
6%
28 / 468
box entries
5%
48 / 970
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

20

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 231 full-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.

Overlapping full-back88%Inverted full-back83%
Why Overlapping full-back 88%: a weighted blend of crossing 84 (weight 30%) + final-third threat 98 (weight 25%) + transition 71 (weight 25%) + dribbling 87 (weight 20%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
box threat, final-third threat, receiving zones, carrying, creativity, line-breaking, through-balls, progression, dribbling, retention
Strong
crossing, press resistance, transition
Average
build-up, defensive aggression, ball-winning
Weak
passing directness, territory (wide vs central)
Unknown
aerial ability, marking, off-ball running — not in event data
Box threat
100
Final-third threat
98
Receiving zones
97
Carrying
96
Creativity
93
Line-breaking
92
Through-balls ~proxy
92
Progression
90
Dribbling
87
Retention
86
Crossing
84
Press resistance ~proxy
81
Transition ~proxy
71
Build-up
64
Defensive aggression
51
Ball-winning
46
Passing directness
20
Territory (wide vs central)
12
21

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: 180 cm / 70 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.

Alphonso Davies Bayern · Bundesliga · 185 cm / 77 kg
93%
Driven by: creativity (15%), press resistance (9%), carrying (9%). Different mechanism — Mendes more via box threat.
Marcos Llorente Atletico · La Liga · 183 cm / 74 kg
92%
Driven by: box threat (12%), final-third threat (11%), crossing (10%). Different mechanism — Mendes more via creativity, line-breaking; Llorente more via passing directness.
Achraf Hakimi PSG · 181 cm / 73 kg
91%
Driven by: box threat (12%), final-third threat (11%), receiving zones (10%). Different mechanism — Mendes more via dribbling, press resistance; Hakimi more via territory (wide vs central).
Andrei Ratiu Rayo Vallecano · La Liga · 183 cm / 75 kg
91%
Driven by: box threat (14%), creativity (11%), carrying (10%). Different mechanism — Mendes more via retention, build-up; Ratiu more via territory (wide vs central), ball-winning.
João Cancelo Barcelona · La Liga · 182 cm / 74 kg
90%
Driven by: box threat (12%), crossing (11%), carrying (10%). Different mechanism — Mendes more via receiving zones, creativity; Cancelo more via territory (wide vs central), defensive aggression.
Ridle Baku RBL · Bundesliga · 176 cm / 72 kg
89%
Driven by: creativity (14%), box threat (11%), receiving zones (11%). Different mechanism — Mendes more via dribbling, press resistance; Baku more via territory (wide vs central).
22

Summary

Nuno Mendes is an overlapping full-back / inverted full-back: 6.8 progressive passes and 23 box entries, delivering 38 key passes. Overlap-first full-back. [1v1 recovery pace and off-ball overlap timing need tracking.]

Based on 23 matches (1572 minutes) this season — a reliable read. He profiles as an overlapping full-back / inverted full-back — best used in a system built around that identity. His biggest room for growth is transition — even a modest improvement there would meaningfully lift his overall overlapping full-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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