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Player reportLa Liga 2025/26

Axel Witsel

Nice
Ball-winning 6 (destroyer) DM
14.1 defensive actions/90
defensive midtempo controllerpress resistancescreening
2723
minutes
32 apps
1468
passes
91% completed
91%
pass completion
1468 passes
72
progressive passes
2.4/90
427
defensive actions
14.1/90
67
tackles + interceptions
68% tackle win
167
recoveries
5.5/90
64
line-breaking passes
2.1/90
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 (60% of his 1468 passes)
91% completion · 1468× in 32/32 matches
↓
ESCAPE PRESSURE
turn out of a tight central area
62% won · 16× in 13/32 matches
↓
PROGRESS CENTRAL
break a line through the middle
2.4 prog/90 · 64× in 24/32 matches
↓
SCREEN / WIN BALL
protect the back four
7.7 ball-wins/90 · 234× in 32/32 matches
↓
RECYCLE / PROGRESS
keep it ticking, feed the final third
4.1 f3-entries/90 · 125× in 30/32 matches
Signature: drop to receive → escape the press on the turn → progress centrally or recycle → screen the counter. Block the central lane and press his first touch to force him backwards.
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 →
46
passes / match
14.1
def actions / 90
16–76
pass range (matches)
58
clearances
Pass range = his fewest and most passes in any single match this season (16 at the low end, 76 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

349 tracked carries (11.5/90, 63 progressive, 3145m 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%3%7%5%3%0%1%11%20%10%5%8%10%11%3%0%
progressivelateral/short% of his 349 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 7m, longest 32m
By zone — where the carry started → where it ended
16Outside → Inside
268Inside → Inside
28Outside → Outside
37Inside → Outside
First (104)Second (101)Third (87)Fourth (57)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).

37
tackle duels
25
won
12
beaten · 32%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 59%
OUTSIDE 41%
Tackle-duel location — 22 inside · 15 outside
Right Wing
4 · 11%
Right Half-Space
5 · 14%
Central
8 · 22%
Left Half-Space
9 · 24%
Left Wing
11 · 30%
Vision AI beaten in 12 of 37 tackle duels (32% loss rate) — a solid 1v1 defensive record.
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: 0.66 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 75%
OUTSIDE 25%
Dribble location — 12 inside · 4 outside
Right Wing
1 · 6%
Right Half-Space
6 · 38%
Central
4 · 25%
Left Half-Space
2 · 12%
Left Wing
3 · 19%
Vision AI 75% of his carries are central — he receives and turns in congested midfield zones rather than out wide.
02

How does he build & move the ball?

How does he escape the first line?

7%
vertical passes
50×
2%
switches
18×
29%
carries
215×
62%
short circulation
466×
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 →RWRHSCLHSLWRW7869%5424%196%5RHS26638%10130%7927%733%82%5C4619%4125%11626%12227%12612%56LHS3731%35%2023%8435%12937%137LW1601%18%1234%5557%92FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: the left half-space in the middle third → the left half-space in the middle third — 5 progressive passes (8% of his progression) at 0.007 xT each. He keeps it in the same lane.

His progression is inward: 52% of progressive passes move the ball toward the middle versus 8% 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: 24 line-breaking passes and 125 final-third entries, 5.1 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%4%5%7%4%0%2%10%15%12%6%0%1%7%10%11%4%0%
completedincomplete1468 passes · any zone → any zone · own goal left, attacking →
1468
passes
91%
completed
130
lost
Vision AIIn line with his 91% season completion rate.
03

How does he progress play?

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

72
progressive · 2.4/90
125
final-third entries · 4.1/90
10
box entries · 0.33/90
13
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?

14 key passes (0.46/90), 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:
7%7%7%21%29%14%7%7%
chance creation (14)assist (0)% of the selected group's key passes originating in each zone
13

Can he finish?

20 shots · 1.65 xG · 1 goals (-0.65 vs xG). Mostly right-footed. Circle size = xG.

shots  20
on target  9
goals  1
xG  1.65
xG on target  1.27
xG / shot  0.083
Where he shoots from — click an area of the box
05

Where does he become vulnerable?

136 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.

25
attacking third (cheap)
80
middle third
31
own third (dangerous)
Vision AI 18% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 1.76 danger-index/90 · 0.392 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
06

What is his passing profile?

1468
passes attempted
40%
mostly forward
57%
mostly short
Direction
Forward
592 · 40%
Sideways
512 · 35%
Backward
364 · 25%
Length (completed)
Short (<15m)
768 · 57%
Medium
525 · 39%
Long (>30m)
45 · 3%
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.

0.410.410.400.310.280.21
own goal left, attacking →
Highest-value routes (xT)
0.41
Right Half-Space Mid third → Right Wing Att third
5 passes
0.41
Left Half-Space Mid third → Left Half-Space Mid third
5 passes
0.40
Left Half-Space Att third → Right Half-Space Att third
2 passes
0.31
Central Mid third → Left Wing Att third
3 passes
0.28
Left Half-Space Mid third → Left Wing Mid third
5 passes · 1 to a shot
0.21
Central Mid third → Left Half-Space Mid third
3 passes
09

Where Does He Receive?

The zones where Axel Witsel 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
Central, Middle third
18%
Secondary
Left Half-Space, Middle third
13%
Third
Right Half-Space, Middle 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 Axel Witsel 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:
1011114916558730157221173861966479104569
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%4%5%7%4%0%2%10%15%12%6%0%1%7%10%11%4%0%
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.

14Key pass
3Cutback
72Progressive
64Long ball
36Switch
By zone — where the pass started → where it landed
91Outside → Inside
757Inside → Inside
147Outside → Outside
343Inside → Outside
By direction
592Forward
364Backward
512Sideways
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, advancing it forward in the middle third — 5 passes worth 0.41 xT.
Where do his chances come from?
Of 14 key passes, his busiest route is a delivery where he plays inside from the right hs toward the central 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 right wing in the defensive third: 19% of his 27 touches there are lost (5 times).
19%5/27 lost7%4/60 lost3%5/147 lost11%9/84 lost12%6/48 lost14%6/42 lost11%21/183 lost6%18/284 lost7%19/270 lost12%13/106 lost5%1/21 lost9%5/53 lost12%7/60 lost11%6/53 lost17%5/30 lostRWRHSCLHSLWDEFMIDATT
Out of possession

Out of possession

Where and how he defends and presses.

14

How & where does he defend?

427 defensive actions across the season (14.1/90). 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 →
37
tackles · 68% won
30
interceptions · 1.0/90
167
recoveries · 5.5/90
58
clearances · 1.9/90
32
blocks
37
avg action height
40
won high (att 3rd)
187
middle third
200
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 234 proactive ball-wins (7.7/90), tackle success 68%. He defends mostly around the middle third.
15

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Axel Witsel 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 ~10-12 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 5.1, 10m)
90%
2.2
1.5
0.60
Mid press (PPDA 6.5, 10m)
90%
2.3
2.6
0.79
Low press (PPDA 9.2, 12m)
93%
2.7
2.1
0.94
Team

Team context

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

16

Impact on the Team

Nice's output per match with Axel Witsel (32 matches) versus without him (6 matches). 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 (32)
WITHOUT (6)
Δ
goals against /match
1.41
1.67
-0.26
points /match
1.03
1.33
-0.30
goals for /match
1.03
1.00
+0.03
xG for /match
1.28
0.05
+1.24
17

His Share of the Team

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

category
share
him / team
ball recoveries
11%
195 / 1784
interceptions
11%
38 / 349
zone-14 entries
9%
30 / 346
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 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.

Tempo controller77%Deep-lying playmaker68%Ball-winning 641%
Why Tempo controller 77%: a weighted blend of retention 89 (weight 35%) + build-up 74 (weight 30%) + press resistance 65 (weight 20%) + progression 35 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
retention
Strong
build-up, passing directness
Average
receiving zones, transition, press resistance, carrying, box threat, crossing, creativity, final-third threat, defensive aggression
Weak
ball-winning, dribbling, progression, territory (wide vs central), line-breaking, through-balls
Unknown
aerial ability, marking, off-ball running — not in event data
Retention
89
Build-up
74
Passing directness
73
Receiving zones
67
Transition ~proxy
66
Press resistance ~proxy
65
Carrying
52
Box threat
50
Crossing
49
Creativity
47
Final-third threat
43
Defensive aggression
41
Ball-winning
37
Dribbling
36
Progression
35
Territory (wide vs central)
33
Line-breaking
31
Through-balls ~proxy
20
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: 186 cm / 82 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.

Denis Zakaria Monaco · 191 cm / 76 kg
76%
Driven by: retention (26%), through-balls (11%), build-up (10%). Different mechanism — Witsel more via crossing, receiving zones; Zakaria more via carrying, dribbling.
Nicolas Seiwald RBL · Bundesliga · 180 cm / 80 kg
73%
Driven by: retention (28%), build-up (19%), press resistance (11%). Different mechanism — Witsel more via crossing, territory (wide vs central); Seiwald more via through-balls, ball-winning.
Roméo Lavia Chelsea · Premier League · 181 cm / 76 kg
70%
Driven by: retention (26%), through-balls (13%), build-up (13%). Different mechanism — Witsel more via territory (wide vs central), transition; Lavia more via dribbling, creativity.
Harry Winks Cagliari · Serie A · 178 cm / 65 kg
66%
Driven by: retention (23%), build-up (19%), through-balls (14%). Different mechanism — Witsel more via receiving zones, territory (wide vs central); Winks more via ball-winning.
Sofyan Amrabat Real Betis · La Liga 25/26 · 185 cm / 77 kg
63%
Driven by: build-up (22%), retention (21%), transition (13%). Different mechanism — Witsel more via receiving zones, box threat; Amrabat more via progression, line-breaking.
Alberto Grassi Cremonese · Serie A 25/26 · 183 cm / 75 kg
61%
Driven by: retention (12%), build-up (12%), defensive aggression (11%). Different mechanism — Witsel more via defensive aggression, territory (wide vs central); Grassi more via dribbling.
21

Summary

Axel Witsel is a tempo controller / deep-lying playmaker: 91% completion, 64 line-breaks and 2.4 progressive passes /90, resisting pressure with 62% dribble success. A central controller. [Off-ball screening position and scanning need tracking data.]

Based on 32 matches (2723 minutes) this season — a reliable read. He profiles as a tempo controller / deep-lying playmaker — 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 tempo controller 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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