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Team reportLigue 1 2026

Lille

A territorially-dominated side, aggressive high-press out of possession, with a moderate attack. Currently #3 of 18 on 15 points (4-3-1, 11:6). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

territorially-dominatedaggressive high-pressmoderate attack
W
W
D
W
D
W
L
W
D
W
W
L
W
D
D
15
points
#3 of 18 · 8 games
11:6
goals
+5 GD
4-3-1
record
W-D-L
1.88
points/game
#3 in the league
1.10
xG for/game
rank #15
1.52
xG against/game
rank #12
#15
press rank
of 18 · most aggressive
44%
field tilt
#14
Lille
League average
Expected goals for / game
1.101.41
Expected goals against / game
1.521.41
Field tilt
44%50%
Pass retention
84%83%
Overview

The team

Who they are and how the season went.

Who Are They? — Identity

The question
In one read, what kind of team is Lille and how good was the season?
Read. Lille currently sit #3 of 18 on 15 points (4W-3D-1L, 1.88 pts/game), scoring 11 and conceding 6 for a goal difference of +5. On the ball they are a territorially-dominated team (44% field tilt, #14 in the league); off it they defend with a aggressive high-press (#15 of 18 for press intensity). Across the 8 matches of event data, they create 1.10 xG/game (#15) and concede 1.52 (#12), a net of -0.42 xG/game — the underlying performance diverges from the actual goal difference.

Season Context — the league table

The question
Where did Lille actually finish, and against whom?

The authoritative final table (full season), centred on Lille.

#teamPWDLGFGAGDPts
1PSG8521169+717
2Rennes85121814+416
3Lille8431116+515
4Monaco8431117+415
5Lyon8422137+614
6Paris FC8422139+414

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Lille actually dominate for chances — and which periods hurt them?

Net xG (created minus conceded) in each 15-minute window, summed across the whole season's matches — above the line is time they dominate for chances, below is time it hurts them. Real on-clock shot timing.

dominant (net xG for)conceding (net xG against)
even0-15'16-30'31-45'46-60'61-75'76-90+'+0.34-1.38
Vision AI Model Insight
Lille tend to fade after a strong start — first-half net xG -0.22, second-half -3.13. Their strongest period is 16-30' (net +0.34 xG); their most dangerous period to face is 61-75' (net -1.38 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Lille against what their opponents created. A line pulling away upwards is a side creating more than it gives away; the gap at the end is the season’s balance (-3.4 xG). Hover a point for that match.

049138.812.1Angers (A) 2-0 · xG 0.87 to 1.94PSG (H) 2-2 · xG 0.85 to 1.33Toulouse (A) 1-0 · xG 1.09 to 3.22Troyes (H) 2-0 · xG 1.28 to 0.53Nice (A) 1-2 · xG 1.66 to 1.06Le Havre (H) 1-0 · xG 0.64 to 1.35Brest (H) 1-1 · xG 1.88 to 0.70Monaco (A) 1-1 · xG 0.52 to 2.01M1M2M3M4M5M6M7M8
LilleOpponents against Lille

Tactical DNA

The football question
In five genes, what is Lille's footballing identity?

Each gene is a 0–100 score — the team's league percentile across the metrics that define that phase of play. It distils the whole report into an identity fingerprint: the taller the gene, the more that trait defines them.

42
Build-Up
possession control from the back
28
Progression
moving the ball upfield with threat
30
Creation
manufacturing chances
19
Press
winning the ball high & hard
33
Solidity
resisting the opponent's threat
Genetic identity
Lille are defined most by their Build-Up DNA (42/100 · average at possession control from the back), and least by their Press DNA (19/100). Percentiles vs the 18 teams in the league.

The Playstyle Wheel

Fifteen style metrics across five domains — Possess, Disrupt, Finish, Press, Defend — each a percentile against the rest of the league. Metrics marked ~proxy use the closest available event-data signal where the standard definition needs data this feed doesn't carry (explicit pressure events, offside/keeper-sweep incidents).

Possess78Disrupt55Finish57Press72Defend68
Possess
Deep buildup
65%
Possession
85%
Field tilt
85%
Disrupt
Central progression ~proxy
50%
Dribble tendency
30%
Progressive passes
85%
Finish
Final-third patience
90%
Shot quality
30%
Open-play xG
50%
Press
Forward press ~proxy
75%
High regains
65%
Pressing efficiency ~proxy
75%
Defend
Def-mid press ~proxy
70%
High line ~proxy
70%
PAdj defensive actions
65%
Lille is defined most by Possess (78% in the league) and weakest on Disrupt (55%). Percentiles vs the 20 teams in the league this season.
In possession

In possession

How they keep the ball, build up, progress, create and finish, and where their attacks die.

Keeping the ball6 sections

Field Tilt — Territorial Control

The question
How much of the pitch does Lille actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Lille's matches, the standard proxy for territorial dominance. Plotted against points per game for every side in the league — the real question isn't just who controls territory, it's whether that control actually converts into results. Dashed lines mark the league average on each axis; Lille highlighted. Hover any dot for the team.

PSG: 74% tilt, 2.12 pts/gRennes: 50% tilt, 2.00 pts/gLille: 44% tilt, 1.88 pts/gMonaco: 52% tilt, 1.88 pts/gLyon: 49% tilt, 1.75 pts/gParis FC: 46% tilt, 1.75 pts/gLens: 55% tilt, 1.62 pts/gLorient: 40% tilt, 1.50 pts/gMarseille: 58% tilt, 1.50 pts/gNice: 53% tilt, 1.38 pts/gToulouse: 51% tilt, 1.25 pts/gAuxerre: 52% tilt, 1.25 pts/gBrest: 44% tilt, 1.12 pts/gAngers: 43% tilt, 1.00 pts/gStrasbourg: 42% tilt, 0.88 pts/gLe Mans: 41% tilt, 0.88 pts/gTroyes: 54% tilt, 0.62 pts/gLe Havre: 51% tilt, 0.25 pts/gLille40%52%63%74%0.20.91.52.1FIELD TILT %POINTS / GAME
Vision AI Model Insight
Lille post 44% field tilt, ranking #14 of 18 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 1.88 points/game sits above the league-average return — a real disconnect: their territorial control isn't showing up on the scoreboard the way it should.

Where the time goes — how long each phase lasts

The question
When Lille has the ball, how much of that time is spent building, progressing and creating?

The share of Lille's time on the ball spent in each phase of play, in the order the phases happen. A phase is where the ball is on the pitch (own third, middle third, final third); a transition or a set piece skips the build-up and is counted on its own.

Build-up: 30.2% of the time on the ball30%Progression: 48.3% of the time on the ball48%Chance creation: 19.1% of the time on the ball19%Attacking transition: 2.4% of the time on the ball48%PROGRESSION
PhaseShare of the time
Build-up30.2%
Progression48.3%
Chance creation19.1%
Attacking transition2.4%
Vision AI Model Insight
Progression is where Lille spends most of its time on the ball (48% of its time on the ball).

Passing Network

The question
Who actually plays with whom — the real on-pitch connections, not just average positions?

Every pass linked to its likely receiver (the next same-team touch), aggregated into player-pair combinations at each player's average position. Line width = how often the pair combines; colour = threat generated per pass (blue low → red high). Hover a line for the pair, or click a player to isolate their connections.

Romain Perraud ↔ Alexsandro Ribeiro: 128 passes, -0.2 combined xTNathan Ngoy ↔ Alexsandro Ribeiro: 115 passes, -0.2 combined xTBerke Özer ↔ Alexsandro Ribeiro: 110 passes, -0.1 combined xTBerke Özer ↔ Nathan Ngoy: 86 passes, -0.3 combined xTNathan Ngoy ↔ Tiago Santos: 75 passes, 0.0 combined xTNabil Bentaleb ↔ Alexsandro Ribeiro: 65 passes, -0.3 combined xTNabil Bentaleb ↔ Nathan Ngoy: 63 passes, -0.1 combined xTNabil Bentaleb ↔ Romain Perraud: 55 passes, 0.5 combined xTNabil Bentaleb ↔ Hákon Haraldsson: 43 passes, 1.4 combined xTBenjamin André ↔ Romain Perraud: 42 passes, 0.2 combined xTBenjamin André ↔ Nabil Bentaleb: 37 passes, 0.4 combined xTNabil Bentaleb ↔ Tiago Santos: 32 passes, 0.3 combined xTDilane Bakwa ↔ Ngal'ayel Mukau: 32 passes, 0.2 combined xTBenjamin André ↔ Nathan Ngoy: 29 passes, 0.0 combined xTNabil Bentaleb ↔ Ethan Mbappé: 29 passes, 0.9 combined xTCalvin Verdonk ↔ Alexsandro Ribeiro: 29 passes, 0.0 combined xTDilane Bakwa ↔ Tiago Santos: 29 passes, 0.2 combined xTTiago Santos ↔ Ngal'ayel Mukau: 29 passes, 0.2 combined xTNabil Bentaleb ↔ Ngal'ayel Mukau: 28 passes, 0.5 combined xTRomain Perraud ↔ Dilane Bakwa: 27 passes, 1.1 combined xTNathan Ngoy ↔ Ethan Mbappé: 27 passes, -0.0 combined xTHákon Haraldsson ↔ Alexsandro Ribeiro: 27 passes, 0.4 combined xTBenjamin André ↔ Hákon Haraldsson: 25 passes, 0.3 combined xTTiago Santos ↔ Ethan Mbappé: 25 passes, 0.9 combined xTNabil Bentaleb — isolate this player's connectionsBentalebRomain Perraud — isolate this player's connectionsPerraudHákon Haraldsson — isolate this player's connectionsHaraldssonNgal'ayel Mukau — isolate this player's connectionsMukauAlexsandro Ribeiro — isolate this player's connectionsRibeiroNathan Ngoy — isolate this player's connectionsNgoyEthan Mbappé — isolate this player's connectionsMbappéBerke Özer — isolate this player's connectionsÖzerOlivier Giroud — isolate this player's connectionsGiroudBenjamin André — isolate this player's connectionsAndréTiago Santos — isolate this player's connectionsSantosDilane Bakwa — isolate this player's connectionsBakwaMaurits Kjærgaard — isolate this player's connectionsKjærgaardCalvin Verdonk — isolate this player's connectionsVerdonkGaëtan Perrin — isolate this player's connectionsPerrinOsame Sahraoui — isolate this player's connectionsSahraoui
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Perraud ↔ Ribeiro
128p · -0.2xT
Ngoy ↔ Ribeiro
115p · -0.2xT
Özer ↔ Ribeiro
110p · -0.1xT
Özer ↔ Ngoy
86p · -0.3xT
Ngoy ↔ Santos
75p · 0.0xT
Bentaleb ↔ Ribeiro
65p · -0.3xT
Bentaleb ↔ Ngoy
63p · -0.1xT
Bentaleb ↔ Perraud
55p · 0.5xT
Bentaleb ↔ Haraldsson
43p · 1.4xT
André ↔ Perraud
42p · 0.2xT
Vision AI Model Insight
Busiest connection: Romain Perraud ↔ Alexsandro Ribeiro (128 passes). Most dangerous per pass: Romain Perraud ↔ Dilane Bakwa (0.04 xT/pass over 27 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Lille had the ball

Every touch across 72 matches. Brighter means more touches.

Which Zones Do They Attack Through?

The question
Across the whole pitch, where does Lille actually do its on-ball work?

Passes on one map, carries (the ball travelling with a player) on the other. Each is binned into the 15 pitch zones (three thirds × five vertical lanes) and shaded by its share of that kind of action; the arrows are the real actions.

Passes
the ball moved by a pass
3985
ACTIONS
4%5%13%6%4%8%9%11%10%10%4%3%3%3%6%PASSES
Carries
the ball moved with a player
992
ACTIONS
4%7%11%7%4%10%9%12%9%11%7%3%2%5%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (12.8% of all actions). 63% of actions run through the inside lanes (centre + both half-spaces) versus 37% down the two wings — an inside-dominant, half-space build. By third: 32% defensive, 49% middle, 18% attacking.

Attack Sides

Which channel they attacked through this season: the share of every action made in the opponent’s half, down the left, through the middle and down the right. Lille leaned on their left (41%). The bars under the pitch put the league’s share beside theirs.

41%Left side22%Middle37%Right sideATTACKING →
Lille
41%22%37%
League
38%22%40%

Final-Third Entries

Every completed pass or carry that took the ball from outside the final third into it, by the channel it arrived in. Lille made 308 this season (38.5 a match); 30% came into the right wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.

Left wing: 91 entries (30%)9130%LEFT WINGLeft half-space: 41 entries (13%)4113%LEFT HALF-SPACECentre: 40 entries (13%)4013%CENTRERight half-space: 44 entries (14%)4414%RIGHT HALF-SPACERight wing: 92 entries (30%)9230%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing9111.430%30%
Left half-space415.113%13%
Centre405.013%11%
Right half-space445.514%14%
Right wing9211.530%32%
Build-up2 sections

Build-Up — the pass map

The football question
How does Lille progress possession from defence into attack — and who runs it?

Build-up passes grouped into 5 real categories — not the old zone grid, not raw individual lines: CB (passer is a centre-back), Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top passer.

1282build-up passes attempted
83%completed
25%reach the middle third
2%go long into the final third

Pass types

534CB · 50%
52Long Wide · 5%
10Long Central · 1%
359Wide → FB · 34%
105Central · 10%

Sequence success — build-up

68build-up sequences this season
10%succeed — reach the next third or a shot
43%turned over with nothing to show
CB534 · 50%
right: 289 passes, most from Ngoy289left: 245 passes, most from Alexsandro245
Long Wide52 · 5%
left: 33 passes, most from Özer33right: 19 passes, most from Özer19
Long Central10 · 1%
right: 7 passes, most from Özer7left: 3 passes, most from Özer3
Wide → FB359 · 34%
left: 196 passes, most from Özer196right: 163 passes, most from Özer163
Central105 · 10%
left: 55 passes, most from Özer55right: 50 passes, most from Özer50
◆ Vision AI Insight
Lille build predominantly down the left, with Özer as the fulcrum (202 build-up passes). Only 27% of their build-up passes actually advance a third — the rest is lateral circulation, the hallmark of a possession-controlling side that circulates patiently in midfield before progressing. Their single most-repeated pattern is C def → LHS def (80×).

Pass Explorer

Every pass of Lille’s last 8 matches as an arrow, theirs first and the opponents’ with other team, each side attacking left to right (solid = completed, dashed grey = failed). Eight families per team — click any map to open it wide, then filter by channel or third, from one to another (or click a cell of the flow grids), by outcome, half, minute and passer. Channels: right wing, right half-space, centre, left half-space, left wing.

Progression4 sections

How They Progress — the mechanism

Not just how many progressive passes, but where they start, who plays them, and whether they actually penetrate. 328 progressive passes across 8 matches (41.0/game).

Origin lane

Right wing
28%
Right half-space
14%
Central
18%
Left half-space
10%
Left wing
30%
Progression is right-dominant: 42% right side · 18% central · 40% left.

Who generates it

Romain Perraud
44 · 13%
Berke Özer
36 · 11%
Nabil Bentaleb
34 · 10%
Dilane Bakwa
32 · 10%
Ethan Mbappé
30 · 9%
Top two — Romain Perraud & Berke Özer — account for 24% of all progression.
PROGRESSION
41.0 prog passes/game
mostly right
→
PENETRATION
28% reach final third
20% reach the box
→
THREAT
the other 72% is recycled
progress ≠ danger
What came of it. 28% of progressive passes reached the final third and 20% the box; the rest was recycled in front of the block. 24% of the progression ran through two players, mostly down the right side.

Which lanes actually create the threat

Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.

Per lane — volume vs threat
Right wingefficient
Right half-spacebalanced
Centralbalanced
Left half-spacesterile
Left wingbalanced

Progression — the pass map

The football question
Once Lille have the ball in midfield, how do they actually break into the final third — and who carries that job?

Progression passes grouped into 5 real categories: CB, Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top passer.

1949progression passes attempted
89%completed
13%break into the final third
13%go backward into the defensive third

Pass types

598CB · 35%
62Long Wide · 4%
4Long Central · 0%
816Wide → FB · 47%
247Central · 14%

Sequence success — progression

102progression sequences this season
25%succeed — reach the next third or a shot
38%turned over with nothing to show
CB598 · 35%
right: 304 passes, most from Ngoy304left: 294 passes, most from Alexsandro294
Long Wide62 · 4%
right: 34 passes, most from Bentaleb34left: 28 passes, most from Perraud28
Long Central4 · 0%
left: 3 passes, most from Haraldsson3
Wide → FB816 · 47%
left: 445 passes, most from Perraud445right: 371 passes, most from Santos371
Central247 · 14%
left: 136 passes, most from Bentaleb136right: 111 passes, most from Bentaleb111
◆ Vision AI Insight
Lille progress predominantly down the left, with Ngoy the busiest midfield outlet (220 progression passes). Only 13% of passes that start in midfield actually break the final-third line — the rest (74%) is recycled back into midfield or (13%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LHS mid → LW mid (104×) — press that lane and midfield progression stalls.

Decision Quality — not all completed passes are equal

A 90% pass completion can hide a sideways habit. Grading every pass by the threat it adds separates value creation from safe circulation.

Excellent (high xT gain)
13%
Progressive
1%
Neutral / sideways
50%
Safe / backward
37%
13% of passes are progressive-or-better; the remaining 87% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.

Carries Map — progressive ball-carries, squad-wide

The question
Where does Lille actually progress the ball with their feet, not a pass?

200 progressive carries this season across the whole squad (20% of 982 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 13m, longest 46m. Most active carrier: Ngoy (35). Filter to one player below.

First (71)Second (53)Third (47)Fourth (29)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Chance creation4 sections

Chance creation — how the shots come

The question
Where do Lille's chances actually come from?

Every shot sorted twice. First by the kind of attack: an attacking transition (the shot came within 15 seconds of winning the ball), a settled attack (open play after the team had the ball), or a set piece. Then by how it was set up: a cross, a cut-back, a long ball, a pass into the box, or no pass at all (the player created it himself). So a cut-back from an attacking transition is counted apart from a cut-back in a settled attack.

90shots
8.8xG
0.10xG per shot
3big chances (0.3+ xG)
11goals
#15key passes / game in the league
#7box entries / game in the league
Attacking transition: 19 shots (21%)21%19Settled attack: 56 shots (62%)62%56Set piece: 15 shots (17%)17%1590SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 21% of shots1952.110.11
Long ball100.140.14
Pass into the box / short pass1041.070.11
Own creation (carry, dribble, rebound)810.900.11
Settled attack 62% of shots5654.980.09
Cross800.610.08
Cut-back620.690.11
Long ball520.300.06
Pass into the box / short pass3012.950.10
Own creation (carry, dribble, rebound)700.430.06
Set piece 17% of shots1511.710.11
Corner1100.840.08
Free kick300.080.03
Penalty110.790.79

Every attempt to create — and what came of it

Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.

Who sets the shots up

PlayerSet-upsxG createdGoals
Hákon Haraldsson111.101
Ethan Mbappé50.620
Basar Önal20.590
Dilane Bakwa60.531
Tiago Santos50.510

Who takes them

PlayerShotsxGGoals
Olivier Giroud71.502
Ayase Ueda91.422
Ethan Mbappé111.232
Dilane Bakwa70.662
Hákon Haraldsson80.611
Vision AI Model Insight
The biggest source of Lille's chances, by xG, is settled attack (5.0 of 8.8 xG, 56 of 90 shots), mostly pass into the box / short pass. 19 of the 90 shots (21%) came within 15 seconds of winning the ball. 15 of the 90 shots came from set pieces; 11 goals from 8.8 xG (+2.2).

Chance Creation — the pass map

The football question
How does Lille consistently create dangerous chances — from which zones, and who creates them?

Key passes (the pass immediately before a shot) grouped into 5 real categories: CB, Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top creator.

Pass types

5CB · 7%
6Long Wide · 9%
8Long Central · 12%
27Wide → FB · 40%
21Central · 31%

Sequence success — final-third

49final-third sequences this season
22%succeed — produce a shot
31%turned over with nothing to show

Danger Funnel — which service carries threat

Every key pass pooled by where it was played FROM, then drawn with its arrow width set by total xT rather than by count. A zone that produces a lot of cheap balls shrinks; one that produces a few decisive ones dominates. Where this disagrees with the volume map, the volume map is the misleading one.

0 key passes shown● low threat● mid● high threatarrow width = total xT, not count
CB5 · 7%
right: 3 passes, most from Goffi3left: 2 passes, most from Alexsandro2
Long Wide6 · 9%
right: 6 passes, most from Bentaleb6
Long Central8 · 12%
left: 4 passes, most from Bakwa4right: 4 passes, most from Bakwa4
Wide → FB27 · 40%
right: 16 passes, most from Haraldsson16left: 11 passes, most from Kjærgaard11
Central21 · 31%
right: 14 passes, most from Haraldsson14left: 7 passes, most from Santos7

Who creates — volume × threat

12Haraldsson
8Bakwa
7Bentaleb
6Mbappé
5Kjærgaard
5André
5Santos
67key passes #15 of 18
13.2box entries/game #7 of 18
30.4final-3rd entries/game #14 of 18
1.10xG/game #15 of 18
11goals #11 of 18
+2.2finishing vs xG #6 of 18
◆ Vision AI Insight
Lille lean right — 40% of their key passes come from that flank and its half-space (27 of 67), most often from Mbappé (6). They funnel chances into the c of the final third, most often via RW att → C att (6 key passes, most often from Santos). Haraldsson is the primary source overall. They generate 1.10 xG a game and finish it clinical — they beat their xG, led by Olivier Giroud (2G), Ayase Ueda (2G), Dilane Bakwa (2G).

Crosses & Cutbacks — squad-wide

The question
How does Lille deliver into the box from wide areas, and what comes of it?

77 crosses: 28 found a team-mate (36%), 6 led to a shot (8%). 20 cut-backs: 10 found a team-mate (50%), 5 led to a shot (25%). A cross starts wide and is aimed into the box; a cut-back starts near the byline and is squared back. Grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball.

Crosses by Territory

The question
Which part of the final third does Lille actually cross from?

77 crosses this season (the same crosses as the map above), split into fifteen territories — five channels (both wings, both half-spaces and the centre) by three depths from the halfway line to the byline. 27% come from one territory, the byline right wing; 1 come from the half-spaces and 0 from the centre.

deep right wing: 5 crosses (6%)6%5deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 2 crosses (3%)3%2advanced right wing: 13 crosses (17%)17%13advanced right half-space: 0 crosses (0%)advanced centre: 0 crosses (0%)advanced left half-space: 0 crosses (0%)advanced left wing: 17 crosses (22%)22%17byline right wing: 21 crosses (27%)27%21byline right half-space: 0 crosses (0%)byline centre: 0 crosses (0%)byline left half-space: 1 crosses (1%)1%1byline left wing: 18 crosses (23%)23%18
TerritoryCrossesShareLed to a shot
byline · right wing2127%4
byline · left wing1823%1
advanced · left wing1722%0
advanced · right wing1317%1
deep · right wing56%0
deep · left wing23%0
byline · left half-space11%0
Finishing3 sections

Shot Map

90 shots for 8.8 xG (1.10/game, #15 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

Moderate attack. 11.2 shots/game at 0.098 xG/shot. Box entries 13/game (#7). Threat created 10.6 xT/game (#12).

Goal Sequences

The move behind each of Lille’s 11 goals this season, from the moment they got the ball to the finish. Pick a goal from the list, then step through it or press Play: numbered circles are passes and touches, dotted lines are carries (the ball travelling with a player), dashed grey is a pass that was lost, the star is the shot.

Each goal’s possession, rebuilt from the raw event feed — 11 goals traced.

How Do They Score?

The question
Where do the goals actually come from — open play, dead balls, which foot?

Every goal Lille scored across the loaded matches, broken down by how it was created and finished.

By situation

Open play
10 · 91%
Set pieces
0 · 0%
Penalties
1 · 9%

By finish

Right foot
3 · 27%
Left foot
7 · 64%
Header
1 · 9%
Vision AI Model Insight
11 goals scored. 91% come in open play; set pieces add 0%. Open play is clearly their main route to goal.
When they lose it1 section

Ball-Loss Map — where attacks die

Every turnover has a location and a cause. This is a rate, not a raw count — the share of pass attempts from each zone that end in a turnover, so a zone they simply play through more often doesn't automatically look riskier. Grey cells are real zones with too few attempts to trust a rate.

Loss rate by zone

42 of 148 pass attempts lost here (28%).28%42/148Ngoy24 of 217 pass attempts lost here (11%).11%24/217Özer92 of 525 pass attempts lost here (18%).18%92/525Özer18 of 225 pass attempts lost here (8%).8%18/225Alexsandro46 of 167 pass attempts lost here (28%).28%46/167Perraud39 of 329 pass attempts lost here (12%).12%39/329Santos40 of 357 pass attempts lost here (11%).11%40/357Bentaleb45 of 432 pass attempts lost here (10%).10%45/432Bentaleb42 of 417 pass attempts lost here (10%).10%42/417Bentaleb56 of 414 pass attempts lost here (14%).14%56/414Perraud39 of 168 pass attempts lost here (23%).23%39/168Mbappé32 of 116 pass attempts lost here (28%).28%32/116Santos24 of 103 pass attempts lost here (23%).23%24/103Giroud34 of 126 pass attempts lost here (27%).27%34/126Haraldsson52 of 241 pass attempts lost here (22%).22%52/241Perraudattacking →

How they lose it

Incomplete pass — attacking third
181
Failed forward pass
125
Failed take-on
88
Lost in the defensive third
222
Their weakest zone is the right wing in the defensive third: 28% of 148 pass attempts there are lost (42 times). Separately, 29% of all losses happen in the attacking third — a fair share happen deeper, which invites transitions.
Out of possession

Out of possession

How they press, where they win the ball back, and how they concede.

Pressing2 sections

Pressing — the full picture

The football question
How hard does Lille press, where, and does it actually work — beyond a single PPDA number?

A composite Pressing Index built from four event-derived dimensions, each ranked against the league. Not one metric — intensity, height, effectiveness and opponent disruption together. The pitch shows every defensive action (the only five events this data records); the white line is the average height that feeds the score. Toggle by action type below, hover any dot for the player.

21
Pressing Index
/100 · passive
Intensity15
PPDA, high-press share, high-zone actions
Height6
how high up the pitch they defend
Effectiveness39
high recoveries & high-regain share
Disruption19
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
19%
RHS
19%
C
23%
LHS
24%
LW
15%
By third (high / mid / low regain)
Def 52%
Mid 35%
Att 13%
Read
Ranked #15 of 18 for press intensity, this is a high press. Note the tension: 52% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (20% high-press share) means that when they do defend, it is often deep. Of recoveries, 54% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#15/18lower = more intense; rank is what matters
Defensive actions / game151#11/18
High-press share20%#16/18def actions won high up
Defensive-action height (0–100)36.2#17/18avg pitch height of actions
High recoveries / game21.9#13/18ball won in mid+att third
High-recovery share54%#9/18share of recoveries won high
Opponent completion allowed84%#11/18lower = more disruptive
Opponent progressive allowed10.0%#18/18of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.

How long they keep it — passes and seconds until the ball is won

The question
Once the opponent has the ball, how many passes and how many seconds pass before Lille win it back with a defensive action?

Counted over the 235 opposition possessions that Lille ended with a tackle, interception, recovery or challenge. Fewer passes and seconds means the ball is won quickly (a press); more means the opponent is allowed to play before Lille step in. Lille win it after 5.4 opponent passes in the first half-hour and after 4.2 after the hour mark (sooner).

PASSES THEY GET
5.1passes
median 3 · before Lille win it
TIME THEY KEEP IT
15sec
median 9s · 29.4 wins per game
How many passes the opponent got in before the ball was won
42%
25%
16%
17%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.2
17s
15–30′
4.7
15s
30–45+′
5.0
15s
45–60′
7.1
20s
60–75′
5.3
15s
75–90+′
3.6
9s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Lille does. This says how: wide or central, short or long, patient or direct. Bars are standard deviations from the league mean for passes played from that third; a solid bar marks a dimension where Lille are genuinely unusual, and a verdict is only written where something clears 0.85 sd — a side that is ordinary in a third is told so rather than given a label for average play.

Build-up (own third) 1,282 passes

nothing unusual in this zone

Width of use-0.7819.38
Wide-channel share-0.780.26
Side bias+0.180.82
Pass length-0.1622.14
Long-ball share-0.460.18
Forward gain per pass-0.2210.49
Backward-pass share+0.170.21
Deep-pass share-0.480.24
Completion+0.390.83
Seconds between passes-0.133.25
Side used

left 27% · central 49% · right 24%

Progression (middle third) 1,949 passes

nothing unusual in this zone

Width of use+0.0425.65
Wide-channel share-0.110.40
Side bias+0.562.29
Pass length-0.1816.97
Long-ball share-0.460.08
Forward gain per pass-0.682.57
Backward-pass share+0.520.36
Deep-pass share-0.480.14
Completion+0.550.88
Seconds between passes-0.443.00
Side used

left 38% · central 31% · right 31%

Final third 754 passes

safer, quicker

Width of use-0.3030.88
Wide-channel share-0.340.56
Side bias+0.684.33
Pass length-0.5614.59
Long-ball share-0.660.07
Forward gain per pass-0.080.94
Backward-pass share-0.420.36
Deep-pass share-0.690.06
Completion+0.940.77
Seconds between passes-0.862.75
Side used

left 46% · central 18% · right 36%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Lille's own league. The means behave as football should: width of use grows 21.0 → 25.6 → 31.6 going forward, pass length shrinks 22.7 → 17.2 → 15.5 m, and completion is hardest in the final third. Tempo is integer-resolution because the feed records whole seconds.

Transitions1 section

Transitions — attacking & defensive

The question
When Lille win or lose the ball, what actually happens in the seconds after?

Reconstructed from the full timestamped event stream: real possession spells (not zone-clustered), and shots that follow a regain within a fixed window. This phase of play needs ordered, per-event timestamps — which every match here carries.

Direct play share18%
#7 of 18 · reaches final third in ≤3 passes
Patient build-up share33%
#5 of 18 · spells of 6+ passes
Tempo (possession length)20.5s
#14 of 18 · shorter = faster tempo
Passes per possession5.1
#6 of 18
Counter-attack shots /game0.79
#16 of 18 · shot within 12s of a regain in own half
Press→shot /game2.67
#14 of 18 · shot within 8s of a high regain
Speed to final third after regain13.5s
#12 of 18 · lower = faster break

Sequence success — attacking transition

7attacking transition sequences this season
0%succeed — produce a shot
43%turned over with nothing to show

Sequence success — defensive transition

29defensive transition sequences this season
59%succeed — reach the next third or a shot
7%turned over with nothing to show
Vision AI Model Insight
Lille are balanced between tempo and patience: 18% of possessions reach the final third in 3 passes or fewer (#7 of 18), against 33% built patiently over 6+ passes (#5 of 18). Winning the ball back leads to a shot inside 12 seconds 0.79 times a game (#16), and a high regain converts to a shot within 8 seconds 2.67 times a game (#14 of 18) — not yet a major source of chances.
Defending the box2 sections

Vulnerability Map — how opponents hurt them

The report flipped: where do opponents create their threat against Lille? 424 opponent progressive passes and 125 shots faced (12.1 xG against) across the season.

Opponent threat by lane (attacking into Lille)

Right wing
34%
Right half-space
16%
Central
13%
Left half-space
10%
Left wing
27%
Where the danger came from. Opponents generated most of their threat through the right wing (34% of the danger conceded).

How Do They Concede?

The question
Where do the goals against Lille actually come from — open play, dead balls, and who supplies them?

Every goal Lille conceded across the loaded matches — the opponent's shots in Lille's own matches — plus every individual opponent key pass faced, each drawn as its own real arrow (not zone-clustered) with the % share of each zone behind it.

Where the goals go in

← opponent shot at own goal

Every opponent key pass against them (90 total)

2%6%3%3%3%18%24%9%11%20%Amine SbaïJordan LefortAmine SbaïBranco van den BoomenYassin BelkhdimAmine SbaïAmine SbaïAmine SbaïAmine SbaïAmine SbaïAmine SbaïUsman SimbakoliOusmane CamaraCarlens ArcusBranco van den BoomenJordan LefortAmine SbaïFabián RuizAchraf HakimiDésiré DouéMaghnes AklioucheVitinhaFabián RuizMaghnes AklioucheMaghnes AklioucheMika GodtsLucas MaronnierHugo PicardAntoine MilleHugo PicardDermane KarimAdrien MonfrayDro FernándezMika GodtsVitinhaCristian CásseresSantiago HidalgoIlyas AziziCristian CásseresRafik MessaliCristian CásseresCristian CásseresCristian CásseresThomas JørgensenThomas JørgensenChrist TapéNiklas SchmidtNiklas SchmidtJoris ChotardJoris ChotardHugo MagnettiLucas TousartJoseph NongeChrist TapéJonathan ClaussJonathan ClaussMohammed AmouraJonathan ClaussElye WahiMohammed AmouraNiels NkounkouGauthier HeinGauthier HeinLamine N'DiayeRassoul NdiayeRassoul NdiayeDjibril OuziadJosh MajaSimon EbonogLamine N'DiayeSota NakamuraSota NakamuraRassoul NdiayeAmir RichardsonRassoul NdiayeSimon EbonogRassoul NdiayeAleksandr GolovinDenis ZakariaAleksandr GolovinAleksandr GolovinVandersonEdan DiopJordan TezeAleksandr GolovinFlávio NazinhoLamine CamaraVandersonVandersonFlávio Nazinho← own goal

By situation

Open play
3 · 60%
Set pieces
2 · 40%
Penalties
0 · 0%
Vision AI Model Insight
5 goals conceded. 60% come in open play, and 40% from set pieces — a genuine defensive frailty at dead balls to fix on the training ground. 20% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right half-space of the attacking third (24% of key passes faced) — that is the zone to shut off.
Context

Shape and tactics

Set pieces, strengths and weaknesses, and who they resemble.

Premium
Tactical Phase Read
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
Subscribe →

Set-Piece Threat

How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.

Open play
10 g · 7.1 xG
Set pieces
0 g · 0.9 xG
Penalties
1 g
0% of goals come from set pieces (0 of 11), worth 0.9 xG from 14 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Lille's corners go?

24 corners taken this season, split by which flag they were taken from — arrows from the flag, dots at the delivery point, shaded by % of that side's corners landing in each zone (same treatment as the concede map below). No swing-direction (inswinger/outswinger) data is recorded here, only a start and end point per pass, which cannot show how the ball curved — so this shows what is genuinely knowable: where it lands, and short vs actually delivered. Tap or hover a dot for who took it and the match; filter to one match below and the shading recomputes for just that game.

Right side (9)

11%22%11%22%22%11%
Delivered into the box 100%Short 0%

Left side (15)

7%7%27%20%13%13%7%
Delivered into the box 93%Short 7%

Where opponents attack Lille from set pieces

22 shots from opponent corners against Lille, 2 conceded, split by the flag the corner came from — arrows from the flag, dots where the shot was taken (gold = goal), shaded by the % of that flag's shots in each zone. Tap or hover a shot for who took it, the minute and the match; filter to one match and the shading recomputes for just that game.

Right flag (11)

9%18%64%9%
Shot 11Goals 1

Left flag (11)

18%27%27%18%9%
Shot 11Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • none stand out
Weaknesses (bottom-third vs league)
  • shots /game — 11.25 (11th pct)
  • xG created /game — 1.10 (17th pct)
  • press intensity (PPDA) — 6.56 (17th pct)
  • field tilt % — 43.85 (22th pct)
  • progression /game — 41.00 (22th pct)

Style Archetype & Similar Teams

Team archetype: Direct / counter high-press. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.

Strasbourg
81%
Lorient
62%
Angers
48%
Lyon
39%
Nice
27%

Performance vs Opponent Styles

The question
Not just how Lille results against a high press or a low block — how does their own play actually change?

Every match split into three tiers by how hard that specific opponent pressed (opponent PPDA — lower means a more aggressive press), matching Lille's own passing behaviour to the result.

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)1.501.501.00
vs mid-block opponents (2m)1.500.003.00
vs low-block opponents (4m)1.250.751.75

Behaviour — how Lille actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents79%18%297.45.5
vs mid-block opponents82%13%379.78.5
vs low-block opponents87%9%4912.619.5
Vision AI Model Insight
Facing a high press, retention drops to 79% vs 87% against a low block (8pt lower under pressure), and directness (long-ball share) sits at 18% when pressed vs 9% against a low block — a real style switch: they go noticeably more direct when pressed rather than trying to play through it.

Scouting Summary — the team in brief

In brief. Lille are territorially-dominated with a aggressive high-press. Their attack creates 1.10 xG a game and they concede 1.52 a game. [Event-data based — no tracking, so off-ball structure and marking scheme need video.]
Squad

Players

Who drives the numbers.

Against Their Own Norm

For each of ten match numbers, the one match this season that departed furthest from Lille’s own average, the eight biggest swings first. Bar right of centre means more than usual, left means less. It shows how much the way they play moves from game to game, and which opponent moved it.

Lille
across 8 matches this season
Pass accuracyat Monaco · 1-1 · 2026-10-2575%avg 84%
Final-third entriesvs Brest · 1-1 · 2026-10-1766avg 38
PPDAvs PSG · 2-2 · 2026-08-2812.9avg 6.6
Progressive passesvs Brest · 1-1 · 2026-10-1765avg 41
Field tiltvs Brest · 1-1 · 2026-10-1782%avg 44%
Threat from passingat Nice · 1-2 · 2026-09-209.66avg 5.77
Defensive actionsat Nice · 1-2 · 2026-09-20119avg 151
Expected goalsvs Brest · 1-1 · 2026-10-171.88avg 1.10

On-Ball Value — who moved the game

Every pass, carry, take-on, shot and ball win is worth the change it made to the chance of scoring minus the chance of conceding in the next 10 seconds. This is Lille’s last 8 matches added up: where the value came from, who produced it, and the six biggest single moves. OBV only measures what a player does with the ball: it shows who added the most on-ball value, not who was the most important player (defending off the ball, positioning and pressing are not in it).

+11.8on-ball value, 8 matches
Where the value came from
Passes3985 actions+3.77
Carries982 actions-0.06
Dribbles144 actions+0.53
Shots90 actions+4.72
Ball wins472 actions+2.82
Most on-ball value (OBV)ActionsOBVper 100
Ethan Mbappé279+1.38+0.49
Nabil Bentaleb502+1.29+0.26
Olivier Giroud86+1.02+1.19
Berke Özer336+0.84+0.25
Nathan Ngoy647+0.84+0.13
Hákon Haraldsson347+0.69+0.20
Alexsandro599+0.65+0.11
Maurits Kjærgaard132+0.65+0.49
123456
Biggest single movesOBV
1  Olivier Giroud · shot+0.805
2  Basar Önal · pass+0.459
3  Ethan Mbappé · shot+0.334
4  Berke Özer · pass+0.272
5  Ayase Ueda · shot+0.268
6  Maurits Kjærgaard · shot+0.242

Set Pieces by Player

Who delivers Lille’s dead balls and who finishes them this season. 24 corners taken, most by Hákon Haraldsson (9); 14 shots from corners and free kicks, 0 goals. “Into the box” counts corners that landed inside the penalty area; free-kick takers are the players who shot from one, because this feed does not mark who delivers the others.

PlayerCorners takenInto the boxSet-piece shotsGoalsxGFree-kick shotsPenalties
Hákon Haraldsson99 (100%)1—0.06——
Nabil Bentaleb——4—0.103—
Ethan Mbappé43 (75%)1—0.03——
Dilane Bakwa66 (100%)——0.00——
Alexsandro——2—0.14——
Tanguy Nianzou——2—0.34——
Basar Önal31 (33%)——0.00——
Tiago Santos——1—0.09——
Ayase Ueda——1—0.07——
Benjamin André——1—0.06——
Olivier Giroud————0.00—1/1
Maxima Goffi——1—0.01——
Calvin Verdonk11 (100%)——0.00——
Romain Perraud11 (100%)——0.00——

Top Performers

Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 216 minutes). Coloured chips are that player's strongest capability blocks.

playerposminVision AI Scorecapability blocks
Berke ÖzerGK6627.0Shot-Stopping 70%
Romain PerraudFB6316.0Ball-Carrying 72%Wide Delivery 40%Ball-Winning 37%
Alexsandro RibeiroCB6625.7Ball-Carrying 70%Aerial & Box Defending 49%Ball-Winning 38%Progression 35%
Nabil BentalebCM6315.2Progression 71%Successful Dribble 48%Chance Creation 45%Ball-Carrying 43%
Nathan NgoyCB6635.2Ball-Carrying 82%Ball-Winning 42%Progression 42%Aerial & Box Defending 14%
Hákon HaraldssonCM5813.8Successful Dribble 46%Ball-Carrying 45%Progression 41%Chance Creation 20%
Tiago SantosFB4943.8Ball-Carrying 95%Ball-Winning 25%Wide Delivery 19%
Ngal'ayel MukauCM5152.4Progression 60%Successful Dribble 52%Ball-Carrying 40%Chance Creation 15%

Top Creators

Chance creation leaders — key passes /90 and box entries.

playerposminkey P /90box entriesxT
Hákon HaraldssonM5811.86185.5
Dilane BakwaM3462.08176.0
Ethan MbappéM4261.27114.7
Tiago SantosD4940.91106.0
Nabil BentalebM6311.00310.1
Romain PerraudD6310.2967.8
Olivier GiroudF4210.6430.8
Ngal'ayel MukauM5150.1744.0

Wide Delivery Leaders

Crosses and cutbacks — wingers and full-backs only (by real average position, not the raw D/M position code), ranked by combined volume.

playerposmincrosses (completed)cutbacks (completed)
Tiago SantosFB4946 (33%)7 (57%)
Romain PerraudFB6313 (67%)9 (22%)
Basar ÖnalW2131 (0%)1 (100%)

Defensive Volume Leaders

Who does the defensive work — tackles, interceptions, recoveries.

playerposmindef actionstacklesinterceptrecoveries
Alexsandro RibeiroD6621188715
Nathan NgoyD66310661026
Nabil BentalebM6311036642
Romain PerraudD6319313619
Ngal'ayel MukauM51590131026
Tiago SantosD4948610520
Benjamin AndréM3868516422
Hákon HaraldssonM581826428

Full Squad Data

Every player with 100+ minutes (20 players).

playerposappsmingoalsxGkey PprogdefxT
Nathan NgoyD766300.11141066.4
Berke ÖzerG766200.0036228.5
Alexsandro RibeiroD766200.21171186.8
Nabil BentalebM863100.373410310.1
Romain PerraudD863100.2244937.8
Hákon HaraldssonM858110.61218825.5
Ngal'ayel MukauM851500.1112904.0
Tiago SantosD649420.5530866.0
Ethan MbappéM742621.2630564.7
Olivier GiroudF742121.531450.8
Benjamin AndréM638600.157852.7
Dilane BakwaM634620.7832566.0
Tanguy NianzouD328300.613292.0
Ayase UedaF424121.412220.3
Basar ÖnalM421300.139331.7
Maurits KjærgaardM519500.656152.5
Maxima GoffiD319400.127422.8
Gaëtan PerrinM414600.102240.8
Calvin VerdonkD514100.0018292.4
Osame SahraouiM413100.232131.3

Player Role Architecture

The question
Who does what — and what tactical job does each key player actually perform?

The nine most-used players (450+ minutes), each with the role their event fingerprint points to — not just their listed position.

Nathan Ngoy
Stopper / marker · Defender
minutes663
goals · xG0 · 0.1
prog passes /901.9
key passes /900.14
def actions /9014.4
pass accuracy92%
Berke Özer
Goalkeeper · Goalkeeper
minutes662
goals · xG0 · 0.0
prog passes /904.9
key passes /900.00
def actions /903.0
pass accuracy68%
Alexsandro Ribeiro
Stopper / marker · Defender
minutes662
goals · xG0 · 0.2
prog passes /902.3
key passes /900.14
def actions /9016.0
pass accuracy91%
Romain Perraud
Ball-playing defender · Defender
minutes631
goals · xG0 · 0.2
prog passes /906.3
key passes /900.29
def actions /9013.3
pass accuracy83%
Nabil Bentaleb
Ball-winner / destroyer · Midfielder
minutes631
goals · xG0 · 0.3
prog passes /904.8
key passes /901.00
def actions /9014.7
pass accuracy85%
Hákon Haraldsson
Ball-winner / destroyer · Midfielder
minutes581
goals · xG1 · 0.6
prog passes /902.8
key passes /901.86
def actions /9012.7
pass accuracy82%
Ngal'ayel Mukau
Ball-winner / destroyer · Midfielder
minutes515
goals · xG0 · 0.1
prog passes /902.1
key passes /900.17
def actions /9015.7
pass accuracy85%
Tiago Santos
Ball-playing defender · Defender
minutes494
goals · xG2 · 0.5
prog passes /905.5
key passes /900.91
def actions /9015.7
pass accuracy82%
Ethan Mbappé
Deep-lying playmaker · Midfielder
minutes426
goals · xG2 · 1.2
prog passes /906.3
key passes /901.27
def actions /9011.8
pass accuracy77%

Recruitment Intelligence — profiles to sign

The question
If you were sporting director, which player profiles would move the needle most?

Each recruitment target is derived directly from the team's weakest areas vs the league — the gap, why it shows in the data, and the profile that closes it.

Need — bottom-third: shots /game (11th pct)
Sign a shot-taking forward to raise shot volume. The data flags this because shot volume is low (11.25, 11th percentile vs the league).
Need — bottom-third: xG created /game (17th pct)
Sign a higher-volume goalscorer or chance creator. The data flags this because the attack under-produces xG (1.10, 17th percentile vs the league).
Need — bottom-third: press intensity (PPDA) (17th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (6.56, 17th percentile vs the league).
Vision AI · building report