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Player reportPremier League 2026

Josko Gvardiol

Man City
Defensive full-back FB
17.5 defensive actions/90 · low final-third share 27%
Capability Analysis
Ball-Winning58%vs 21 full-backs
"How actively does he win the ball back?"
Interceptions /901.1357%
Ball recoveries /903.4262%
Tackles /901.3929%
Duels won /901.8686%
Breaking Pressure
no action recorded in any high-press match yet
Wide Delivery10%vs 21 full-backs
"Does he create danger from wide areas -- crosses and cutbacks?"
Crosses /900.00%
Cross accuracy: 0.0%
Cutbacks /901.0419%
Ball-Carrying95%vs 21 full-backs
"Does he advance the ball himself when the pass isn't on?"
Progressive carries /908.3595%
Carry distance /90190.78m95%
full-backinverted full-backprogressioncrossing
618
minutes
8 apps
85%
pass completion
348 passes
24
progressive passes
3.5/90
20
final-3rd entries
2.9/90
5
box entries
0.73/90
120
defensive actions
17.5/90
25
tackles + interceptions
57% tackle win
8
dribbles
62% 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 (51% of his 348 passes)
85% completion · 348× in 8/8 matches
↓
PROGRESS
carry or combine up the flank
3.5 prog/90 · 24× in 7/8 matches
↓
DRIBBLE
beat his man up the line
62% won · 8× in 4/8 matches
↓
DELIVER
cross or cut-back into the box
6 key passes · 5× in 4/8 matches
↓
DEFEND
1v1 and cover on his side
120 def actions · lost 32% deep · 120× in 8/8 matches
Signature: receive wide/inverted → progress the flank → deliver into the box → recover to defend 1v1. Attack the space behind him in transition.
18

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 →
44
passes / match
17.5
def actions / 90
14–81
pass range (matches)
14
clearances
Pass range = his fewest and most passes in any single match this season (14 at the low end, 81 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.

06

How dangerous are his carries?

Real ball-carries

60 tracked carries (8.7/90, 18 progressive, 575m 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.

2%7%2%2%2%27%23%25%5%7%
progressivelateral/short% of his 60 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 7m, longest 35m
By zone — where the carry started → where it ended
4Outside → Inside
22Inside → Inside
28Outside → Outside
6Inside → Outside
First (20)Second (18)Third (17)Fourth (5)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).

14
tackle duels
8
won
6
beaten · 43%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 29%
OUTSIDE 71%
Tackle-duel location — 4 inside · 10 outside
Right Wing
0 · 0%
Right Half-Space
0 · 0%
Central
0 · 0%
Left Half-Space
4 · 29%
Left Wing
10 · 71%
Vision AI beaten in 6 of 14 tackle duels (43% loss rate) — a real defensive leak worth flagging.
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: 1.17 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 12%
OUTSIDE 88%
Dribble location — 1 inside · 7 outside
Right Wing
0 · 0%
Right Half-Space
0 · 0%
Central
1 · 12%
Left Half-Space
0 · 0%
Left Wing
7 · 88%
Vision AI 88% of his carries are wide — an overlapping full-back who hugs the touchline.
07

How does he build & move the ball?

How does he escape the first line?

11%
vertical passes
15×
4%
switches
6×
24%
carries
32×
60%
short circulation
81×
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 →RWRHSCLHSLWRW0RHS2100%2C138%123%354%715%2LHS971%13%340%3928%2728%27LW1831%11%16%1144%8049%90FROM
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 — 7 progressive passes (23% of his progression) at 0.085 xT each. He moves it inside.

His progression is inward: 80% of progressive passes move the ball toward the middle versus 0% going wider — he cuts in rather than holding width.

Only 5% 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 20 final-third entries, 3.1 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%1%1%2%1%4%16%24%25%19%5%
completedincomplete348 passes · any zone → any zone · own goal left, attacking →
348
passes
85%
completed
53
lost
Vision AIIn line with his 85% season completion rate.
09

How does he progress play?

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

24
progressive · 3.5/90
20
final-third entries · 2.9/90
5
box entries · 0.73/90
17
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.
08

How does he create chances?

6 key passes (0.87/90), 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:
17%33%33%17%
chance creation (6)assist (0)% of the selected group's key passes originating in each zone
10

Where does he become vulnerable?

56 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.

13
attacking third (cheap)
25
middle third
18
own third (dangerous)
Vision AI 23% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 3.23 danger-index/90 · 0.396 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
11

What is his passing profile?

348
passes attempted
38%
mostly forward
66%
mostly short
Direction
Forward
132 · 38%
Sideways
113 · 32%
Backward
103 · 30%
Length (completed)
Short (<15m)
194 · 66%
Medium
87 · 29%
Long (>30m)
14 · 5%
12

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.

0.640.320.300.290.260.23
own goal left, attacking →
Highest-value routes (xT)
0.64
Left Wing Mid third → Left Half-Space Att third
3 passes
0.32
Left Wing Mid third → Left Wing Mid third
5 passes
0.30
Left Wing Att third → Left Half-Space Att third
1 passes
0.29
Left Wing Def third → Central Mid third
3 passes
0.26
Left Half-Space Att third → Right Half-Space Att third
1 passes
0.23
Left Half-Space Att third → Central Att third
1 passes
04

Where Does He Receive?

The zones where Josko Gvardiol 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
30%
Primary
Left Wing, Middle third
19%
Secondary
Left Half-Space, Middle third
17%
Third
Left Wing, Defensive third
These are the zones where he collected the ball most.
05

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Josko Gvardiol 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:
15598387671815359911
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%1%1%2%1%4%16%24%25%19%5%
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.

6Key pass
4Cross
2Cutback
24Progressive
32Long ball
9Switch
By zone — where the pass started → where it landed
92Outside → Inside
83Inside → Inside
91Outside → Outside
29Inside → Outside
By direction
132Forward
103Backward
113Sideways
own goal left, attacking →
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 →
How does he progress the ball forward?
His most common route for progressing play: he plays inside from the left wing toward the left hs, advancing it forward in the middle third — 3 passes worth 0.64 xT.
Where do his chances come from?
Of 6 key passes, his busiest route is a delivery where he plays straight through the central in the final third — 3 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 defensive third: 27% of his 15 touches there are lost (4 times).
—0 touches · too few—2 touches · too few—4 touches · too few27%4/15 lost21%12/57 lost—0 touches · too few—1 touch · too few—3 touches · too few7%5/68 lost18%19/105 lost—0 touches · too few—1 touch · too few12%1/8 lost18%5/28 lost7%4/56 lostRWRHSCLHSLWDEFMIDATT
03

Crosses & Cutbacks

4 crosses (0.58/90, 2 completed) and 2 cutbacks (0.29/90, 2 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.

14

How & where does he defend?

120 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 →
14
tackles · 57% won
11
interceptions · 1.6/90
29
recoveries · 4.2/90
14
clearances · 2.0/90
3
blocks
42
avg action height
20
won high (att 3rd)
51
middle third
49
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 54 proactive ball-wins (7.9/90), tackle success 57%. He defends high, stepping out to intercept — suits a high line.
15

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Josko Gvardiol 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 ~2-4 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 4.5, 2m)
84%
3.3
4.3
0.84
Mid press (PPDA 5.5, 2m)
88%
2.2
4.4
0.79
Low press (PPDA 8.0, 4m)
84%
4.1
5.0
1.21
Team

Team context

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

16

Impact on the Team

Insufficient sample: Josko Gvardiol played nearly every Man City match in the loaded data, so there is no meaningful "without him" comparison yet. This section fills in as more matches (and the rest of the season) are scraped.

17

His Share of the Team

Of everything Man City produced this season, the categories where the biggest share ran through Josko Gvardiol specifically — his share of the team total, not a per-90 rate.

category
share
him / team
clearances
6%
78 / 1336
interceptions
5%
26 / 486
goals
5%
1 / 20
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

19

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 232 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.

Inverted full-back84%Overlapping full-back61%
Why Inverted full-back 84%: a weighted blend of build-up 89 (weight 35%) + retention 89 (weight 30%) + progression 58 (weight 25%) + press resistance 65 (weight 10%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
retention, build-up, carrying
Strong
passing directness, box threat, receiving zones, transition, defensive aggression
Average
final-third threat, press resistance, progression, creativity, line-breaking, through-balls, crossing, dribbling, ball-winning
Weak
territory (wide vs central)
Unknown
aerial ability, marking, off-ball running — not in event data
Retention
89
Build-up
89
Carrying
85
Passing directness
85
Box threat
79
Receiving zones
79
Transition ~proxy
78
Defensive aggression
72
Final-third threat
68
Press resistance ~proxy
65
Progression
58
Creativity
57
Line-breaking
55
Through-balls ~proxy
47
Crossing
45
Dribbling
41
Ball-winning
40
Territory (wide vs central)
4
20

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: 185 cm / 80 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.

Jarell Quansah Leverkusen · Bundesliga · 190 cm / 83 kg
78%
Driven by: build-up (21%), territory (wide vs central) (17%), retention (16%). Different mechanism — Gvardiol more via passing directness, through-balls.
Mathías Olivera Napoli · Serie A · 174 cm / 78 kg
78%
Driven by: build-up (22%), retention (13%), territory (wide vs central) (13%). Different mechanism — Gvardiol more via through-balls, passing directness; Olivera more via ball-winning.
Alessandro Bastoni Inter · Serie A · 190 cm / 75 kg
76%
Driven by: build-up (17%), territory (wide vs central) (12%), transition (11%). Different mechanism — Bastoni more via through-balls, line-breaking.
Jules Koundé Barcelona · La Liga · 181 cm / 84 kg
73%
Driven by: retention (18%), build-up (14%), carrying (12%). Different mechanism — Gvardiol more via passing directness; Koundé more via dribbling, press resistance.
Lucas Hernández PSG · Ligue 1 · 184 cm / 79 kg
73%
Driven by: build-up (27%), territory (wide vs central) (16%), retention (12%). Different mechanism — Gvardiol more via box threat, through-balls.
Gerard Martín Barcelona · La Liga · 186 cm / 82 kg
72%
Driven by: build-up (24%), retention (15%), territory (wide vs central) (14%). Different mechanism — Gvardiol more via box threat, through-balls.
21

Summary

Josko Gvardiol is an inverted full-back / overlapping full-back: 3.5 progressive passes and 5 box entries, delivering 6 key passes. Overlap-first full-back. [1v1 recovery pace and off-ball overlap timing need tracking.]

Based on 8 matches (618 minutes) — an early read, treat with caution until more minutes are logged. He profiles as an inverted full-back / overlapping full-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 inverted 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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