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Player reportSerie A 2025/26

Teun Koopmeiners

Juventus
Ball-winning 6 (destroyer) DM
11.7 defensive actions/90
defensive middeep-lying playmakerpress resistancescreening
1957
minutes
33 apps
1242
passes
88% completed
88%
pass completion
1242 passes
112
progressive passes
5.2/90
255
defensive actions
11.7/90
51
tackles + interceptions
36% tackle win
78
recoveries
3.6/90
110
line-breaking passes
5.1/90
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
drop between the centre-backs — mostly in the middle third (59% of his 1242 passes)
88% completion · 1242× in 32/32 matches
↓
PROGRESS CENTRAL
break a line through the middle
5.2 prog/90 · 110× in 27/32 matches
↓
SCREEN / WIN BALL
protect the back four
5.9 ball-wins/90 · 129× in 32/32 matches
↓
RECYCLE / PROGRESS
keep it ticking, feed the final third
6.6 f3-entries/90 · 144× in 28/32 matches
Signature: Receive → Progress Central → Screen / Win Ball → Recycle / 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: escape pressure — 10× (low confidence, shown as a number only, no tactical conclusion drawn) — omitted from the signature rather than presented as one.
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 →
39
passes / match
11.7
def actions / 90
4–116
pass range (matches)
40
clearances
Pass range = his fewest and most passes in any single match this season (4 at the low end, 116 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.

11

How dangerous are his carries?

Real ball-carries

282 tracked carries (13.0/90, 91 progressive, 2788m 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%2%4%6%3%0%1%10%12%7%2%6%16%18%7%4%1%
progressivelateral/short% of his 282 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 8m, longest 52m
By zone — where the carry started → where it ended
18Outside → Inside
160Inside → Inside
73Outside → Outside
31Inside → Outside
First (105)Second (92)Third (47)Fourth (38)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).

33
tackle duels
12
won
21
beaten · 64%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 48%
OUTSIDE 52%
Tackle-duel location — 16 inside · 17 outside
Right Wing
5 · 15%
Right Half-Space
7 · 21%
Central
5 · 15%
Left Half-Space
4 · 12%
Left Wing
12 · 36%
Vision AI beaten in 21 of 33 tackle duels (64% loss rate) — a real defensive leak worth flagging.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →

Dribbles (1v1s)

Can he escape pressure on the ball? His carries/dribbles in tight central areas, by channel. Season rate: 0.46 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 70%
OUTSIDE 30%
Dribble location — 7 inside · 3 outside
Right Wing
1 · 10%
Right Half-Space
4 · 40%
Central
3 · 30%
Left Half-Space
0 · 0%
Left Wing
2 · 20%
Vision AI 70% of his carries are central — he receives and turns in congested midfield zones rather than out wide.
03

How does he build & move the ball?

How does he escape the first line?

15%
vertical passes
85×
5%
switches
30×
34%
carries
195×
45%
short circulation
257×
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 →RWRHSCLHSLWRW9365%6020%1912%113%3RHS10350%5122%2320%216%62%2C20316%3227%5430%6116%3212%24LHS3782%76%2234%12725%9334%129LW3130%115%4837%11548%149FROM
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 middle third → the left half-space in the middle third — 15 progressive passes (13% of his progression) at 0.013 xT each. He moves it inside.

His progression is inward: 66% of progressive passes move the ball toward the middle versus 1% going wider — he cuts in rather than holding width.

Only 8% of his passes switch play, so his threat is same-side — contain the flank he occupies and the route closes.

Quality behind the volume: 44 line-breaking passes and 144 final-third entries, 20.1 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%2%4%6%4%2%2%5%7%7%3%3%11%16%19%6%3%
completedincomplete1242 passes · any zone → any zone · own goal left, attacking →
1242
passes
88%
completed
152
lost
Vision AIIn line with his 88% season completion rate.
02

How does he progress play?

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

112
progressive · 5.2/90
144
final-third entries · 6.6/90
14
box entries · 0.64/90
25
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?

17 key passes (0.78/90), 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%23%23%8%15%15%
chance creation (13)assist (0)% of the selected group's key passes originating in each zone
14

Can he finish?

28 shots · 1.52 xG · 0 goals (-1.52 vs xG). Mostly left-footed. Circle size = xG.

shots  28
on target  19
goals  0
xG  1.52
xG on target  1.63
xG / shot  0.054
Where he shoots from — click an area of the box
06

Where does he become vulnerable?

157 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.

68
attacking third (cheap)
52
middle third
37
own third (dangerous)
Vision AI 43% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 2.22 danger-index/90 · 0.307 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
07

What is his passing profile?

1242
passes attempted
48%
mostly forward
50%
mostly short
Direction
Forward
590 · 48%
Sideways
417 · 34%
Backward
235 · 19%
Length (completed)
Short (<15m)
549 · 50%
Medium
476 · 44%
Long (>30m)
65 · 6%
05

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.

0.820.750.690.650.540.46
own goal left, attacking →
Highest-value routes (xT)
0.82
Left Half-Space Mid third → Left Half-Space Mid third
9 passes
0.75
Left Half-Space Mid third → Left Wing Mid third
13 passes
0.69
Left Wing Mid third → Left Wing Mid third
10 passes
0.65
Left Wing Mid third → Left Half-Space Att third
4 passes
0.54
Left Wing Def third → Left Half-Space Mid third
5 passes
0.46
Left Wing Mid third → Left Wing Att third
5 passes
09

Where Does He Receive?

The zones where Teun Koopmeiners 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
19%
Primary
Left Half-Space, Middle third
19%
Secondary
Left Wing, Middle third
10%
Third
Left Half-Space, Defensive third
These are the zones where he collected the ball most.
10

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Teun Koopmeiners 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:
41142197236693619658693531142253715230
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%2%4%6%4%2%2%5%7%7%3%3%11%16%19%6%3%
own goal left, attacking →
08

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.

17Key pass
14Cross
8Cutback
112Progressive
110Long ball
49Switch
By zone — where the pass started → where it landed
197Outside → Inside
439Inside → Inside
209Outside → Outside
245Inside → Outside
By direction
590Forward
235Backward
417Sideways
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 plays straight through the left hs in the middle third — 9 passes worth 0.82 xT.
Where do his chances come from?
Of 17 key passes, his busiest route is a delivery where he plays inside from the left wing toward the central in the final third — 5 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: 39% of his 51 touches there are lost (20 times).
25%3/12 lost15%2/13 lost5%3/63 lost10%13/125 lost18%14/77 lost10%6/59 lost8%6/75 lost6%7/124 lost4%9/243 lost10%24/232 lost39%20/51 lost18%5/28 lost7%2/28 lost27%12/44 lost38%26/68 lostRWRHSCLHSLWDEFMIDATT
13

Crosses & Cutbacks

14 crosses (0.64/90, 6 completed) and 8 cutbacks (0.37/90, 1 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?

255 defensive actions across the season (11.7/90). 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 →
33
tackles · 36% won
18
interceptions · 0.8/90
78
recoveries · 3.6/90
40
clearances · 1.8/90
16
blocks
39
avg action height
33
won high (att 3rd)
113
middle third
109
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 129 proactive ball-wins (5.9/90), tackle success 36%. 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 Teun Koopmeiners 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 5.6, 11m)
82%
3.0
3.7
0.81
Mid press (PPDA 8.1, 11m)
87%
5.1
4.9
1.11
Low press (PPDA 12.5, 11m)
91%
7.2
6.4
2.01
Team

Team context

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

17

Impact on the Team

Juventus's output per match with Teun Koopmeiners (33 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 (33)
WITHOUT (5)
Δ
goals against /match
0.97
0.40
+0.57
points /match
1.70
2.60
-0.90
goals for /match
1.55
2.00
-0.45
xG for /match
1.65
1.55
+0.10
18

His Share of the Team

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

category
share
him / team
final-third entries
7%
178 / 2484
interceptions
6%
19 / 327
threat added by passing (xT)
6%
33.6 / 586.5
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 258 defensive mids 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.

Deep-lying playmaker82%Tempo controller80%Ball-winning 647%
Why Deep-lying playmaker 82%: a weighted blend of progression 93 (weight 30%) + build-up 71 (weight 30%) + retention 77 (weight 20%) + press resistance 67 (weight 20%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
line-breaking, progression, final-third threat, receiving zones
Strong
carrying, territory (wide vs central), retention, box threat, transition, build-up, passing directness
Average
press resistance, crossing, creativity, through-balls, dribbling, defensive aggression
Weak
ball-winning
Unknown
aerial ability, marking, off-ball running — not in event data
Line-breaking
94
Progression
93
Final-third threat
88
Receiving zones
85
Carrying
83
Territory (wide vs central)
83
Retention
77
Box threat
75
Transition ~proxy
71
Build-up
71
Passing directness
70
Press resistance ~proxy
67
Crossing
63
Creativity
60
Through-balls ~proxy
57
Dribbling
54
Defensive aggression
53
Ball-winning
26
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: 185 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 Serie A, Bundesliga, La Liga, Ligue 1 and Premier League, 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.

Pierre-Emile Højbjerg Marseille · Ligue 1 · 187 cm / 81 kg
85%
Driven by: final-third threat (12%), progression (10%), carrying (9%). Different mechanism — Koopmeiners more via territory (wide vs central), line-breaking; Højbjerg more via passing directness.
Himad Abdelli Marseille · Ligue 1 · 185 cm / 81 kg
78%
Driven by: carrying (15%), final-third threat (12%), box threat (12%). Different mechanism — Koopmeiners more via passing directness, line-breaking; Abdelli more via ball-winning, dribbling.
Leon Avdullahu Hoffenheim · Bundesliga · 185 cm / 79 kg
78%
Driven by: progression (16%), receiving zones (13%), line-breaking (12%). Different mechanism — Koopmeiners more via box threat, territory (wide vs central); Avdullahu more via ball-winning.
Leon Goretzka Aston Villa · Premier League · 189 cm / 82 kg
75%
Driven by: receiving zones (13%), final-third threat (12%), carrying (11%). Different mechanism — Koopmeiners more via territory (wide vs central), passing directness; Goretzka more via retention, dribbling.
Bryan Cristante Roma · 186 cm / 80 kg
73%
Driven by: progression (16%), transition (15%), final-third threat (14%). Different mechanism — Koopmeiners more via territory (wide vs central), retention; Cristante more via defensive aggression, ball-winning.
Elliot Anderson Man City · Premier League · 179 cm / 69 kg
72%
Driven by: progression (15%), final-third threat (14%), carrying (11%). Different mechanism — Koopmeiners more via retention; Anderson more via ball-winning, dribbling.
22

Summary

Teun Koopmeiners is a deep-lying playmaker / tempo controller: 88% completion, 110 line-breaks and 5.2 progressive passes /90, resisting pressure with 50% dribble success. A central controller. [Off-ball screening position and scanning need tracking data.]

Based on 33 matches (1957 minutes) this season — a reliable read. He profiles as a deep-lying playmaker / tempo controller — best used in a system built around that identity. His biggest room for growth is press resistance — even a modest improvement there would meaningfully lift his overall deep-lying playmaker 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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