Vision AI ← BACK TO SEARCHSeason2025/262026 · this seasonAll seasons
Building the full report
Combining every season — this one is larger, give it a moment.
Team reportLigue 1 2026

Lens

A possession-dominant side, aggressive high-press out of possession, with a high-volume attack. Currently #7 of 18 on 13 points (4-1-3, 16:12). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

possession-dominantaggressive high-presshigh-volume attack
L
W
D
D
W
L
W
W
L
L
D
L
W
W
W
13
points
#7 of 18 · 8 games
16:12
goals
+4 GD
4-1-3
record
W-D-L
1.62
points/game
#7 in the league
1.65
xG for/game
rank #4
1.35
xG against/game
rank #7
#7
press rank
of 18 · most aggressive
55%
field tilt
#3
Lens
League average
Expected goals for / game
1.651.41
Expected goals against / game
1.351.41
Field tilt
55%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 Lens and how good was the season?
Read. Lens currently sit #7 of 18 on 13 points (4W-1D-3L, 1.62 pts/game), scoring 16 and conceding 12 for a goal difference of +4. On the ball they are a possession-dominant team (55% field tilt, #3 in the league); off it they defend with a aggressive high-press (#7 of 18 for press intensity). Across the 8 matches of event data, they create 1.65 xG/game (#4) and concede 1.35 (#7), a net of +0.30 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

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

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

#teamPWDLGFGAGDPts
4Monaco8431117+415
5Lyon8422137+614
6Paris FC8422139+414
7Lens84131612+413
8Marseille84041813+512
9Lorient833276+112
10Nice8323810-211

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Lens 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+'+1.11-0.78
Vision AI Model Insight
Lens tend to stay fairly even across both halves — first-half net xG +1.33, second-half +1.10. Their strongest period is 76-90+' (net +1.11 xG); their most dangerous period to face is 61-75' (net -0.78 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Lens 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 (+2.4 xG). Hover a point for that match.

05101413.210.8Auxerre (H) 5-2 · xG 3.49 to 1.82Strasbourg (A) 1-2 · xG 2.58 to 1.64Lorient (H) 0-1 · xG 1.11 to 0.86Le Mans (A) 2-2 · xG 1.24 to 2.87Monaco (A) 1-2 · xG 1.31 to 0.96Lyon (H) 2-1 · xG 1.47 to 1.11Troyes (A) 3-1 · xG 1.37 to 1.13Paris FC (H) 2-1 · xG 0.63 to 0.39M1M2M3M4M5M6M7M8
LensOpponents against Lens

Tactical DNA

The football question
In five genes, what is Lens'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.

67
Build-Up
possession control from the back
53
Progression
moving the ball upfield with threat
78
Creation
manufacturing chances
72
Press
winning the ball high & hard
61
Solidity
resisting the opponent's threat
Genetic identity
Lens are defined most by their Creation DNA (78/100 · strong at manufacturing chances), and least by their Progression DNA (53/100). 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).

Possess72Disrupt43Finish60Press75Defend78
Possess
Deep buildup
75%
Possession
60%
Field tilt
80%
Disrupt
Central progression ~proxy
0%
Dribble tendency
40%
Progressive passes
90%
Finish
Final-third patience
15%
Shot quality
75%
Open-play xG
90%
Press
Forward press ~proxy
65%
High regains
80%
Pressing efficiency ~proxy
80%
Defend
Def-mid press ~proxy
80%
High line ~proxy
80%
PAdj defensive actions
75%
Lens is defined most by Defend (78% in the league) and weakest on Disrupt (43%). 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 Lens actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Lens'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; Lens 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/gLens40%52%63%74%0.20.91.52.1FIELD TILT %POINTS / GAME
Vision AI Model Insight
Lens post 55% field tilt, ranking #3 of 18 in the league — a genuinely territory-dominant side, and their 1.62 points/game sits above the league-average return — territory is genuinely converting into results.

Where the time goes — how long each phase lasts

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

The share of Lens'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: 32.0% of the time on the ball32%Progression: 42.9% of the time on the ball43%Chance creation: 22.4% of the time on the ball22%Attacking transition: 2.7% of the time on the ball43%PROGRESSION
PhaseShare of the time
Build-up32.0%
Progression42.9%
Chance creation22.4%
Attacking transition2.7%
Vision AI Model Insight
Progression is where Lens spends most of its time on the ball (43% 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.

Florian Thauvin ↔ Ruben Aguilar: 93 passes, 2.4 combined xTRuben Aguilar ↔ Kyllian Antonio: 58 passes, -0.6 combined xTRobin Risser ↔ Kyllian Antonio: 56 passes, -0.4 combined xTMatthieu Udol ↔ Kyllian Antonio: 49 passes, -0.3 combined xTFlorian Thauvin ↔ Michal Skóras: 48 passes, 2.4 combined xTRuben Aguilar ↔ Yacine Titraoui: 40 passes, 0.1 combined xTMatthieu Udol ↔ Robin Risser: 35 passes, 0.7 combined xTFlorian Thauvin ↔ Yacine Titraoui: 34 passes, 1.0 combined xTRuben Aguilar ↔ Michaël Cuisance: 33 passes, 0.8 combined xTMichaël Cuisance ↔ Yacine Titraoui: 31 passes, 0.2 combined xTFlorian Thauvin ↔ Michaël Cuisance: 30 passes, 0.9 combined xTFlorian Thauvin ↔ Andrija Bulatovic: 30 passes, 1.6 combined xTMatthieu Udol ↔ Amadou Haidara: 28 passes, 0.5 combined xTYacine Titraoui ↔ Kyllian Antonio: 27 passes, 0.2 combined xTMichaël Cuisance ↔ Kyllian Antonio: 25 passes, 0.1 combined xTMichal Skóras ↔ Andrija Bulatovic: 25 passes, -0.0 combined xTRuben Aguilar ↔ Amadou Haidara: 21 passes, 0.1 combined xTMatthieu Udol ↔ Michal Skóras: 21 passes, 0.5 combined xTRuben Aguilar ↔ Robin Risser: 20 passes, 0.1 combined xTAndrija Bulatovic ↔ Kyllian Antonio: 20 passes, 0.0 combined xTThorgan Hazard ↔ Matthieu Udol: 19 passes, 0.3 combined xTRuben Aguilar ↔ Andrija Bulatovic: 19 passes, 0.3 combined xTMatthieu Udol ↔ Yacine Titraoui: 19 passes, 0.6 combined xTAmadou Haidara ↔ Kyllian Antonio: 19 passes, -0.3 combined xTFlorian Thauvin — isolate this player's connectionsThauvinAdrien Thomasson — isolate this player's connectionsThomassonRobin Risser — isolate this player's connectionsRisserMichal Skóras — isolate this player's connectionsSkórasRuben Aguilar — isolate this player's connectionsAguilarMatthieu Udol — isolate this player's connectionsUdolAmadou Haidara — isolate this player's connectionsHaidaraMichaël Cuisance — isolate this player's connectionsCuisanceAndrija Bulatovic — isolate this player's connectionsBulatovicKyllian Antonio — isolate this player's connectionsAntonioRayan Fofana — isolate this player's connectionsFofanaYacine Titraoui — isolate this player's connectionsTitraouiFranjo Ivanovic — isolate this player's connectionsIvanovicOdsonne Édouard — isolate this player's connectionsÉdouardThorgan Hazard — isolate this player's connectionsHazardAbdallah Sima — isolate this player's connectionsSima
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Thauvin ↔ Aguilar
93p · 2.4xT
Aguilar ↔ Antonio
58p · -0.6xT
Risser ↔ Antonio
56p · -0.4xT
Udol ↔ Antonio
49p · -0.3xT
Thauvin ↔ Skóras
48p · 2.4xT
Aguilar ↔ Titraoui
40p · 0.1xT
Udol ↔ Risser
35p · 0.7xT
Thauvin ↔ Titraoui
34p · 1.0xT
Aguilar ↔ Cuisance
33p · 0.8xT
Cuisance ↔ Titraoui
31p · 0.2xT
Vision AI Model Insight
Busiest connection: Florian Thauvin ↔ Ruben Aguilar (93 passes). Most dangerous per pass: Florian Thauvin ↔ Andrija Bulatovic (0.05 xT/pass over 30 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Lens 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 Lens 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
4338
ACTIONS
5%6%11%5%5%12%10%10%7%8%7%4%2%2%5%PASSES
Carries
the ball moved with a player
1033
ACTIONS
3%7%11%6%4%13%10%10%7%8%8%3%2%2%6%CARRIES
Vision AI Model Insight
Their single busiest zone is the right wing of the middle third (11.9% of all actions). 58% of actions run through the inside lanes (centre + both half-spaces) versus 42% down the two wings — an inside-dominant, half-space build. By third: 33% defensive, 47% middle, 20% 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. Lens leaned on their right (46%). The bars under the pitch put the league’s share beside theirs.

34%Left side20%Middle46%Right sideATTACKING →
Lens
34%20%46%
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. Lens made 319 this season (39.9 a match); 38% 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: 87 entries (27%)8727%LEFT WINGLeft half-space: 39 entries (12%)3912%LEFT HALF-SPACECentre: 30 entries (9%)309%CENTRERight half-space: 41 entries (13%)4113%RIGHT HALF-SPACERight wing: 122 entries (38%)12238%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing8710.927%30%
Left half-space394.912%13%
Centre303.89%11%
Right half-space415.113%14%
Right wing12215.238%32%
Build-up2 sections

Build-Up — the pass map

The football question
How does Lens 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.

1456build-up passes attempted
87%completed
27%reach the middle third
1%go long into the final third

Pass types

554CB · 44%
79Long Wide · 6%
3Long Central · 0%
507Wide → FB · 40%
128Central · 10%

Sequence success — build-up

78build-up sequences this season
18%succeed — reach the next third or a shot
35%turned over with nothing to show
CB554 · 44%
right: 299 passes, most from Ganiou299left: 255 passes, most from Antonio255
Long Wide79 · 6%
left: 51 passes, most from Risser51right: 28 passes, most from Risser28
Long Central3 · 0%
right: 2 passes, most from Titraoui2
Wide → FB507 · 40%
left: 260 passes, most from Risser260right: 247 passes, most from Risser247
Central128 · 10%
right: 75 passes, most from Risser75left: 53 passes, most from Risser53
◆ Vision AI Insight
Lens build predominantly down the right, with Risser as the fulcrum (300 build-up passes). Only 28% 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 → RHS def (87×).

Pass Explorer

Every pass of Lens’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. 344 progressive passes across 8 matches (43.0/game).

Origin lane

Right wing
37%
Right half-space
15%
Central
8%
Left half-space
10%
Left wing
30%
Progression is right-dominant: 51% right side · 8% central · 41% left.

Who generates it

Florian Thauvin
68 · 20%
Ruben Aguilar
43 · 12%
Matthieu Udol
41 · 12%
Michal Skóras
28 · 8%
Robin Risser
19 · 6%
Top two — Florian Thauvin & Ruben Aguilar — account for 32% of all progression.
PROGRESSION
43.0 prog passes/game
mostly right
→
PENETRATION
27% reach final third
26% reach the box
→
THREAT
the other 73% is recycled
progress ≠ danger
What came of it. 27% of progressive passes reached the final third and 26% the box; the rest was recycled in front of the block. 32% 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
Centralsterile
Left half-spacebalanced
Left wingefficient

Progression — the pass map

The football question
Once Lens 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.

2027progression passes attempted
87%completed
14%break into the final third
13%go backward into the defensive third

Pass types

543CB · 31%
82Long Wide · 5%
7Long Central · 0%
938Wide → FB · 53%
200Central · 11%

Sequence success — progression

116progression sequences this season
30%succeed — reach the next third or a shot
34%turned over with nothing to show
CB543 · 31%
right: 308 passes, most from Ganiou308left: 235 passes, most from Sagnan235
Long Wide82 · 5%
left: 41 passes, most from Thauvin41right: 41 passes, most from Titraoui41
Long Central7 · 0%
right: 7 passes, most from Bulatovic7
Wide → FB938 · 53%
right: 560 passes, most from Aguilar560left: 378 passes, most from Udol378
Central200 · 11%
left: 108 passes, most from Cuisance108right: 92 passes, most from Cuisance92
◆ Vision AI Insight
Lens progress predominantly down the right, with Aguilar the busiest midfield outlet (186 progression passes). Only 14% of passes that start in midfield actually break the final-third line — the rest (73%) 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 RHS mid → RW mid (114×) — 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
49%
Safe / backward
38%
14% of passes are progressive-or-better; the remaining 86% 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 Lens actually progress the ball with their feet, not a pass?

194 progressive carries this season across the whole squad (19% of 1017 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 15m, longest 67m. Most active carrier: Ganiou (36). Filter to one player below.

First (78)Second (42)Third (38)Fourth (36)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 Lens'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.

111shots
13.2xG
0.12xG per shot
10big chances (0.3+ xG)
15goals
#5key passes / game in the league
#2box entries / game in the league
Attacking transition: 23 shots (21%)21%23Settled attack: 55 shots (50%)50%55Set piece: 33 shots (30%)30%33111SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 21% of shots2323.350.15
Cross400.240.06
Cut-back210.280.14
Long ball100.120.12
Pass into the box / short pass1111.380.13
Own creation (carry, dribble, rebound)501.330.27
Settled attack 50% of shots5595.600.10
Cross1541.840.12
Cut-back400.510.13
Long ball300.150.05
Pass into the box / short pass2242.150.10
Own creation (carry, dribble, rebound)1110.960.09
Set piece 30% of shots3344.260.13
Corner2711.800.07
Free kick300.080.03
Penalty332.380.79

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
Florian Thauvin131.916
Michal Skóras70.951
Matthieu Udol80.520
Abdallah Sima40.521
Ismaëlo Ganiou10.470

Who takes them

PlayerShotsxGGoals
Florian Thauvin203.764
Matthieu Udol81.332
Odsonne Édouard81.321
Michaël Cuisance60.880
Abdallah Sima90.861
Vision AI Model Insight
The biggest source of Lens's chances, by xG, is settled attack (5.6 of 13.2 xG, 55 of 111 shots), mostly pass into the box / short pass. 23 of the 111 shots (21%) came within 15 seconds of winning the ball. 33 of the 111 shots came from set pieces; 15 goals from 13.2 xG (+1.8).

Chance Creation — the pass map

The football question
How does Lens 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

3CB · 4%
5Long Wide · 6%
11Long Central · 13%
26Wide → FB · 32%
37Central · 45%

Sequence success — final-third

94final-third sequences this season
23%succeed — produce a shot
34%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
CB3 · 4%
right: 3 passes, most from Antonio3
Long Wide5 · 6%
left: 3 passes, most from Udol3right: 2 passes, most from Thauvin2
Long Central11 · 13%
right: 7 passes, most from Thauvin7left: 4 passes, most from Thauvin4
Wide → FB26 · 32%
right: 17 passes, most from Aguilar17left: 9 passes, most from Udol9
Central37 · 45%
right: 24 passes, most from Thauvin24left: 13 passes, most from Thauvin13

Who creates — volume × threat

27Thauvin
9Udol
7Skóras
7Aguilar
5Cuisance
5Bulatovic
4Sima
82key passes #5 of 18
15.0box entries/game #2 of 18
31.6final-3rd entries/game #12 of 18
1.65xG/game #4 of 18
15goals #3 of 18
+1.8finishing vs xG #3 of 18
◆ Vision AI Insight
Lens lean left — 45% of their key passes come from that flank and its half-space (37 of 82), most often from Thauvin (19). They funnel chances into the c of the final third, most often via LW att → C att (15 key passes, most often from Thauvin). Thauvin is the primary source overall. They generate 1.65 xG a game and finish it clinical — they beat their xG, led by Florian Thauvin (4G), Matthieu Udol (2G), Franjo Ivanovic (2G).

Crosses & Cutbacks — squad-wide

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

130 crosses: 55 found a team-mate (42%), 23 led to a shot (18%). 31 cut-backs: 15 found a team-mate (48%), 6 led to a shot (19%). 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 Lens actually cross from?

130 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; 9 come from the half-spaces and 0 from the centre.

deep right wing: 7 crosses (5%)5%7deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 7 crosses (5%)5%7advanced right wing: 34 crosses (26%)26%34advanced right half-space: 7 crosses (5%)5%7advanced centre: 0 crosses (0%)advanced left half-space: 1 crosses (1%)1%1advanced left wing: 18 crosses (14%)14%18byline right wing: 35 crosses (27%)27%35byline right half-space: 0 crosses (0%)byline centre: 0 crosses (0%)byline left half-space: 1 crosses (1%)1%1byline left wing: 20 crosses (15%)15%20
TerritoryCrossesShareLed to a shot
byline · right wing3527%10
advanced · right wing3426%4
byline · left wing2015%4
advanced · left wing1814%3
deep · right wing75%0
deep · left wing75%1
advanced · right half-space75%1
advanced · left half-space11%0
byline · left half-space11%0
Finishing3 sections

Shot Map

111 shots for 13.2 xG (1.65/game, #4 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

High-volume attack. 13.9 shots/game at 0.119 xG/shot. Box entries 15/game (#2). Threat created 11.4 xT/game (#7).

Goal Sequences

The move behind each of Lens’s 16 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 — 16 goals traced.

How Do They Score?

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

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

By situation

Open play
11 · 73%
Set pieces
1 · 7%
Penalties
3 · 20%

By finish

Right foot
4 · 27%
Left foot
5 · 33%
Header
6 · 40%
Vision AI Model Insight
15 goals scored. 73% come in open play; set pieces add 7%. 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

39 of 228 pass attempts lost here (17%).17%39/228Antonio24 of 265 pass attempts lost here (9%).9%24/265Risser51 of 493 pass attempts lost here (10%).10%51/493Risser15 of 236 pass attempts lost here (6%).6%15/236Risser56 of 234 pass attempts lost here (24%).24%56/234Udol60 of 502 pass attempts lost here (12%).12%60/502Thauvin35 of 425 pass attempts lost here (8%).8%35/425Thauvin60 of 422 pass attempts lost here (14%).14%60/422Ganiou36 of 311 pass attempts lost here (12%).12%36/311Haidara66 of 367 pass attempts lost here (18%).18%66/367Udol80 of 288 pass attempts lost here (28%).28%80/288Thauvin51 of 161 pass attempts lost here (32%).32%51/161Thauvin29 of 78 pass attempts lost here (37%).37%29/78Thauvin33 of 106 pass attempts lost here (31%).31%33/106Udol64 of 222 pass attempts lost here (29%).29%64/222Thauvinattacking →

How they lose it

Incomplete pass — attacking third
257
Failed forward pass
164
Failed take-on
80
Lost in the defensive third
185
Their weakest zone is the central in the attacking third: 37% of 78 pass attempts there are lost (29 times). Separately, 37% 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 Lens 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.

76
Pressing Index
/100 · strong
Intensity72
PPDA, high-press share, high-zone actions
Height83
how high up the pitch they defend
Effectiveness86
high recoveries & high-regain share
Disruption58
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
20%
RHS
21%
C
20%
LHS
18%
LW
21%
By third (high / mid / low regain)
Def 41%
Mid 42%
Att 17%
Read
Ranked #7 of 18 for press intensity, this is a high press. 59% of defensive actions happen in the middle & attacking thirds, at an average height of 41. Of recoveries, 61% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#7/18lower = more intense; rank is what matters
Defensive actions / game150#12/18
High-press share25%#3/18def actions won high up
Defensive-action height (0–100)41.0#3/18avg pitch height of actions
High recoveries / game26.1#3/18ball won in mid+att third
High-recovery share61%#2/18share of recoveries won high
Opponent completion allowed83%#6/18lower = more disruptive
Opponent progressive allowed8.4%#9/18of 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 Lens win it back with a defensive action?

Counted over the 273 opposition possessions that Lens 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 Lens step in. Lens win it after 6.5 opponent passes in the first half-hour and after 4.3 after the hour mark (sooner).

PASSES THEY GET
5.3passes
median 3 · before Lens win it
TIME THEY KEEP IT
15sec
median 7s · 34.1 wins per game
How many passes the opponent got in before the ball was won
37%
30%
17%
16%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.1
18s
15–30′
7.0
23s
30–45+′
5.9
18s
45–60′
4.4
12s
60–75′
4.8
13s
75–90+′
4.1
11s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Lens 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 Lens 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) 1,456 passes

circulating, playing short, shorter passing

Width of use+0.4922.02
Wide-channel share+0.390.33
Side bias-0.23-0.70
Pass length-0.9519.28
Long-ball share-0.930.14
Forward gain per pass-0.987.20
Backward-pass share+0.610.23
Deep-pass share-0.960.19
Completion+0.940.87
Seconds between passes-0.543.00
Side used

left 27% · central 41% · right 32%

Progression (middle third) 2,027 passes

right-sided

Width of use+0.4726.57
Wide-channel share+0.590.45
Side bias-1.02-3.98
Pass length-0.2416.89
Long-ball share-0.350.09
Forward gain per pass-0.243.25
Backward-pass share+0.370.35
Deep-pass share-0.190.15
Completion+0.440.87
Seconds between passes-0.443.00
Side used

left 31% · central 27% · right 42%

Final third 855 passes

nothing unusual in this zone

Width of use+0.4532.73
Wide-channel share+0.310.61
Side bias-0.69-5.30
Pass length+0.0715.58
Long-ball share-0.360.08
Forward gain per pass-0.100.91
Backward-pass share+0.060.39
Deep-pass share-0.120.08
Completion+0.010.70
Seconds between passes-0.203.25
Side used

left 36% · central 13% · right 51%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Lens'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 Lens 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 share19%
#5 of 18 · reaches final third in ≤3 passes
Patient build-up share30%
#8 of 18 · spells of 6+ passes
Tempo (possession length)18.7s
#11 of 18 · shorter = faster tempo
Passes per possession4.9
#8 of 18
Counter-attack shots /game1.38
#1 of 18 · shot within 12s of a regain in own half
Press→shot /game3.48
#4 of 18 · shot within 8s of a high regain
Speed to final third after regain11.2s
#4 of 18 · lower = faster break

Sequence success — attacking transition

8attacking transition sequences this season
38%succeed — produce a shot
38%turned over with nothing to show

Sequence success — defensive transition

37defensive transition sequences this season
62%succeed — reach the next third or a shot
16%turned over with nothing to show
Vision AI Model Insight
Lens are a direct, fast-break side: 19% of possessions reach the final third in 3 passes or fewer (#5 of 18), against 30% built patiently over 6+ passes (#8 of 18). Winning the ball back leads to a shot inside 12 seconds 1.38 times a game (#1), and a high regain converts to a shot within 8 seconds 3.48 times a game (#4 of 18) — a modest but real source of chances.
Defending the box2 sections

Vulnerability Map — how opponents hurt them

The report flipped: where do opponents create their threat against Lens? 333 opponent progressive passes and 85 shots faced (10.8 xG against) across the season.

Opponent threat by lane (attacking into Lens)

Right wing
29%
Right half-space
13%
Central
20%
Left half-space
15%
Left wing
23%
Where the danger came from. Opponents generated most of their threat through the right wing (29% of the danger conceded).

How Do They Concede?

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

Every goal Lens conceded across the loaded matches — the opponent's shots in Lens'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 (62 total)

2%2%2%3%6%6%15%16%13%26%10%Noah CadiouMamadou KonéJean-Victor MakengoPanos KatserisArsène KouassiIbrahima BaldéJean-Victor MakengoJacobo OrtegaGiovanni ReynaGiovanni ReynaDiogo SousaGiovanni ReynaSebastian NanasiGessime YassinePape DiopSebastian NanasiSebastian NanasiSebastian NanasiNoa BoisséLucas CalodatAdil BourabaaAdil BourabaaRayan BambaLouis MafoutaAlexandre LaurayAlexandre LaurayFlávio NazinhoMatthis AblineParis BrunnerAleksandr GolovinParis BrunnerAleksandr GolovinAleksandr GolovinMathys DetourbetAdama CamaraLassine SinayokoAbner ViníciusTyler MortonLoïs OpendaZachary AthekameKeito NakamuraPavel SulcZachary AthekameTanner TessmannZachary AthekameZachary AthekameKaïl BoudacheDanny NamasoLamine SyRomain FaivreClément AkpaDanny NamasoRayan MandengueLasso CoulibalyAntoine MilleJunior DiazAntoine MilleRenaud RipartTimothé NkadaDermane KarimMerwan IfnaouiAntoine Mille← own goal

By situation

Open play
10 · 91%
Set pieces
0 · 0%
Penalties
1 · 9%
Vision AI Model Insight
11 goals conceded. 91% come in open play; set pieces account for only 0%, so dead-ball defending is not the main issue. 9% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the left half-space of the attacking third (26% 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
11 g · 8.9 xG
Set pieces
1 g · 1.9 xG
Penalties
3 g
7% of goals come from set pieces (1 of 15), worth 1.9 xG from 30 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Lens's corners go?

52 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 (28)

11%14%7%4%29%21%4%
Delivered into the box 89%Short 11%

Left side (24)

4%8%54%21%4%4%
Delivered into the box 96%Short 4%

Where opponents attack Lens from set pieces

8 shots from opponent corners against Lens, 0 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 (4)

25%25%50%
Shot 4Goals 0

Left flag (4)

25%50%25%
Shot 4Goals 0

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • field tilt % — 55.16 (83th pct)
  • box entries /game — 15.00 (83th pct)
  • xG created /game — 1.65 (78th pct)
  • shots /game — 13.88 (72th pct)
Weaknesses (bottom-third vs league)
  • none stand out

Style Archetype & Similar Teams

Team archetype: High-press possession side. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.

PSG
83%
Marseille
39%
Rennes
39%
Toulouse
38%
Le Havre
26%

Performance vs Opponent Styles

The question
Not just how Lens 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 Lens's own passing behaviour to the result.

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)1.502.000.50
vs mid-block opponents (2m)3.002.001.50
vs low-block opponents (4m)1.751.002.25

Behaviour — how Lens actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents83%10%3610.510.5
vs mid-block opponents85%11%4111.118.5
vs low-block opponents84%10%4812.015.5
Vision AI Model Insight
Facing a high press, retention drops to 83% vs 84% against a low block (1pt lower under pressure), and directness (long-ball share) sits at 10% when pressed vs 10% against a low block — their passing style barely changes regardless of how the opponent sets up, for better or worse.

Scouting Summary — the team in brief

In brief. Lens are possession-dominant with a aggressive high-press. Their attack creates 1.65 xG a game and they concede 1.35 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 Lens’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.

Lens
across 8 matches this season
Progressive passesvs Lorient · 0-1 · 2026-09-0560avg 43
Expected goalsvs Auxerre · 5-2 · 2026-08-223.49avg 1.65
Pass accuracyvs Auxerre · 5-2 · 2026-08-2287%avg 84%
Threat from passingvs Lorient · 0-1 · 2026-09-058.49avg 6.55
Final-third entriesvs Lorient · 0-1 · 2026-09-0562avg 40
Progressive carriesvs Lorient · 0-1 · 2026-09-0555avg 41
PPDAat Monaco · 1-2 · 2026-09-186.6avg 5.3
Field tiltvs Paris FC · 2-1 · 2026-10-2474%avg 55%

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 Lens’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).

+15.8on-ball value, 8 matches
Where the value came from
Passes4338 actions+5.79
Carries1017 actions-0.13
Dribbles127 actions-0.01
Shots111 actions+7.12
Ball wins510 actions+3.00
Most on-ball value (OBV)ActionsOBVper 100
Florian Thauvin655+4.57+0.70
Abdallah Sima148+1.40+0.94
Ruben Aguilar471+1.27+0.27
Ismaëlo Ganiou498+1.07+0.22
Odsonne Édouard69+1.00+1.45
Florian Sotoca131+0.99+0.76
Michal Skóras300+0.87+0.29
Matthieu Udol409+0.68+0.17
123456
Biggest single movesOBV
1  Florian Thauvin · shot+0.819
2  Florian Thauvin · shot+0.783
3  Florian Thauvin · shot+0.767
4  Florian Sotoca · shot+0.452
5  Florian Thauvin · pass+0.442
6  Ismaëlo Ganiou · pass+0.426

Set Pieces by Player

Who delivers Lens’s dead balls and who finishes them this season. 52 corners taken, most by Florian Thauvin (43); 30 shots from corners and free kicks, 1 goals, led by Matthieu Udol (1 goals, 0.42 xG). “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
Florian Thauvin4338 (88%)3—0.1013/3
Andrija Bulatovic76 (86%)3—0.081—
Abdallah Sima——3—0.26——
Ismaëlo Ganiou——3—0.30——
Matthieu Udol——310.42——
Thorgan Hazard——2—0.081—
Odsonne Édouard——2—0.12——
Jonathan Gradit——2—0.15——
Jean-Clair Todibo——2—0.09——
Ruben Aguilar——2—0.08——
Junior Kadile10 (0%)1—0.03——
Amadou Haidara——1—0.08——
Michal Skóras——1—0.03——
Florian Sotoca——1—0.04——

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
Florian ThauvinAM7408.2Box Threat 85%Ball-Carrying 70%Chance Creation 66%
Robin RisserGK7698.2Shot-Stopping 82%
Ismaëlo GaniouCB4607.5Ball-Carrying 72%Ball-Winning 68%Progression 64%Aerial & Box Defending 24%
Ruben AguilarCM5595.8Progression 84%Chance Creation 63%Ball-Carrying 33%Successful Dribble 18%
Matthieu UdolCM6024.6Progression 64%Chance Creation 62%Ball-Carrying 34%Successful Dribble 24%
Kyllian AntonioCB5134.3Ball-Winning 52%Progression 51%Ball-Carrying 14%Aerial & Box Defending 7%
Michaël CuisanceCM4963.2Ball-Carrying 51%Successful Dribble 50%Progression 34%Chance Creation 22%

Top Creators

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

playerposminkey P /90box entriesxT
Florian ThauvinM7403.284315.6
Ruben AguilarM5591.131610.0
Matthieu UdolM6021.3578.6
Michal SkórasM4021.5784.6
Andrija BulatovicM3101.4563.9
Florian SotocaM2820.9672.4
Abdallah SimaF3850.9451.3
Thorgan HazardF2281.1851.5

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Matthieu UdolM60210010728
Ismaëlo GaniouD4608911620
Ruben AguilarM5598917825
Michaël CuisanceM4968211734
Florian ThauvinM740783432
Yacine TitraouiM4027515626
Kyllian AntonioD5137513520
Michal SkórasM402674817

Full Squad Data

Every player with 100+ minutes (24 players).

playerposappsmingoalsxGkey PprogdefxT
Robin RisserG876900.0019196.7
Florian ThauvinM874043.827687815.6
Matthieu UdolM760221.39411008.6
Ruben AguilarM755910.67438910.0
Kyllian AntonioD651300.119754.4
Michaël CuisanceM749600.9513823.7
Ismaëlo GaniouD546010.8116895.8
Michal SkórasM740200.1728674.6
Yacine TitraouiM640200.0013754.7
Abdallah SimaF538510.946561.3
Amadou HaidaraM735100.207492.5
Andrija BulatovicM731000.3514463.9
Franjo IvanovicF629920.622411.0
Florian SotocaM528210.839332.4
Odsonne ÉdouardF627211.330160.7
Souleymane SagnanD326800.1012503.0
Thorgan HazardF622810.836281.5
Jean-Clair TodiboD420500.102421.7
Samson BaidooD317700.007391.7
Saud AbdulhamidM316910.1110252.1
Maik NawrockiD216000.106191.7
Jonathan GraditD315600.215351.7
Mezian MesloubM414500.125181.4
Junior KadileM310900.113170.7

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.

Robin Risser
Goalkeeper · Goalkeeper
minutes769
goals · xG0 · 0.0
prog passes /902.2
key passes /900.00
def actions /902.2
pass accuracy85%
Florian Thauvin
Creative forward · Forward
minutes740
goals · xG4 · 3.8
prog passes /908.3
key passes /903.28
def actions /909.5
pass accuracy67%
Matthieu Udol
Deep-lying playmaker · Midfielder
minutes602
goals · xG2 · 1.3
prog passes /906.1
key passes /901.35
def actions /9015.0
pass accuracy75%
Ruben Aguilar
Deep-lying playmaker · Midfielder
minutes559
goals · xG1 · 0.6
prog passes /906.9
key passes /901.13
def actions /9014.3
pass accuracy89%
Kyllian Antonio
Stopper / marker · Defender
minutes513
goals · xG0 · 0.1
prog passes /901.6
key passes /900.18
def actions /9013.2
pass accuracy89%
Michaël Cuisance
Ball-winner / destroyer · Midfielder
minutes496
goals · xG0 · 0.9
prog passes /902.4
key passes /900.91
def actions /9014.9
pass accuracy90%
Ismaëlo Ganiou
Stopper / marker · Defender
minutes460
goals · xG1 · 0.8
prog passes /903.1
key passes /900.20
def actions /9017.4
pass accuracy88%
Michal Skóras
Deep-lying playmaker · Midfielder
minutes402
goals · xG0 · 0.1
prog passes /906.3
key passes /901.57
def actions /9015.0
pass accuracy79%
Yacine Titraoui
Ball-winner / destroyer · Midfielder
minutes402
goals · xG0 · 0.0
prog passes /902.9
key passes /900.00
def actions /9016.8
pass accuracy89%

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 — below-average: progression /game (44th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (43.00, 44th percentile vs the league).
Need — below-average: pass retention % (50th pct)
Sign a secure ball-retaining midfielder. The data flags this because possession is turned over cheaply (83.89, 50th percentile vs the league).
Vision AI · building report