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.
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.
#
team
P
W
D
L
GF
GA
GD
Pts
4
Monaco
8
4
3
1
11
7
+4
15
5
Lyon
8
4
2
2
13
7
+6
14
6
Paris FC
8
4
2
2
13
9
+4
14
7
Lens
8
4
1
3
16
12
+4
13
8
Marseille
8
4
0
4
18
13
+5
12
9
Lorient
8
3
3
2
7
6
+1
12
10
Nice
8
3
2
3
8
10
-2
11
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)
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.
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).
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.
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.
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.
Phase
Share of the time
Build-up
32.0%
Progression
42.9%
Chance creation
22.4%
Attacking transition
2.7%
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.
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
Carries
the ball moved with a player
1033
ACTIONS
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.
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.
Channel
Entries
Per match
Share
League share
Left wing
87
10.9
27%
30%
Left half-space
39
4.9
12%
13%
Centre
30
3.8
9%
11%
Right half-space
41
5.1
13%
14%
Right wing
122
15.2
38%
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%
Long Wide79 · 6%
Long Central3 · 0%
Wide → FB507 · 40%
Central128 · 10%
◆ 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.
From channel
To channel
From third
To third
Outcome
Minutes
Channel to channel · click a cell
Third to third · click a cell
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%
Long Wide82 · 5%
Long Central7 · 0%
Wide → FB938 · 53%
Central200 · 11%
◆ 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.
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
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition21% of shots
23
2
3.35
0.15
Cross
4
0
0.24
0.06
Cut-back
2
1
0.28
0.14
Long ball
1
0
0.12
0.12
Pass into the box / short pass
11
1
1.38
0.13
Own creation (carry, dribble, rebound)
5
0
1.33
0.27
Settled attack50% of shots
55
9
5.60
0.10
Cross
15
4
1.84
0.12
Cut-back
4
0
0.51
0.13
Long ball
3
0
0.15
0.05
Pass into the box / short pass
22
4
2.15
0.10
Own creation (carry, dribble, rebound)
11
1
0.96
0.09
Set piece30% of shots
33
4
4.26
0.13
Corner
27
1
1.80
0.07
Free kick
3
0
0.08
0.03
Penalty
3
3
2.38
0.79
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
Player
Set-ups
xG created
Goals
Florian Thauvin
13
1.91
6
Michal Skóras
7
0.95
1
Matthieu Udol
8
0.52
0
Abdallah Sima
4
0.52
1
Ismaëlo Ganiou
1
0.47
0
Who takes them
Player
Shots
xG
Goals
Florian Thauvin
20
3.76
4
Matthieu Udol
8
1.33
2
Odsonne Édouard
8
1.32
1
Michaël Cuisance
6
0.88
0
Abdallah Sima
9
0.86
1
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%
Long Wide5 · 6%
Long Central11 · 13%
Wide → FB26 · 32%
Central37 · 45%
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.
Territory
Crosses
Share
Led to a shot
byline · right wing
35
27%
10
advanced · right wing
34
26%
4
byline · left wing
20
15%
4
advanced · left wing
18
14%
3
deep · right wing
7
5%
0
deep · left wing
7
5%
1
advanced · right half-space
7
5%
1
advanced · left half-space
1
1%
0
byline · left half-space
1
1%
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
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.
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
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#7/18
lower = more intense; rank is what matters
Defensive actions / game
150
#12/18
High-press share
25%
#3/18
def actions won high up
Defensive-action height (0–100)
41.0
#3/18
avg pitch height of actions
High recoveries / game
26.1
#3/18
ball won in mid+att third
High-recovery share
61%
#2/18
share of recoveries won high
Opponent completion allowed
83%
#6/18
lower = more disruptive
Opponent progressive allowed
8.4%
#9/18
of 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
Every opponent key pass against them (62 total)
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.
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.
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)
Delivered into the box 89%Short 11%
Left side (24)
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)
Shot 4Goals 0
Left flag (4)
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 type
goals for/g
goals against/g
points/g
vs high-pressing opponents (2m)
1.50
2.00
0.50
vs mid-block opponents (2m)
3.00
2.00
1.50
vs low-block opponents (4m)
1.75
1.00
2.25
Behaviour — how Lens actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
83%
10%
36
10.5
10.5
vs mid-block opponents
85%
11%
41
11.1
18.5
vs low-block opponents
84%
10%
48
12.0
15.5
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.]
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.
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)
Actions
OBV
per 100
Florian Thauvin
655
+4.57
+0.70
Abdallah Sima
148
+1.40
+0.94
Ruben Aguilar
471
+1.27
+0.27
Ismaëlo Ganiou
498
+1.07
+0.22
Odsonne Édouard
69
+1.00
+1.45
Florian Sotoca
131
+0.99
+0.76
Michal Skóras
300
+0.87
+0.29
Matthieu Udol
409
+0.68
+0.17
Biggest single moves
OBV
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.
Player
Corners taken
Into the box
Set-piece shots
Goals
xG
Free-kick shots
Penalties
Florian Thauvin
43
38 (88%)
3
—
0.10
1
3/3
Andrija Bulatovic
7
6 (86%)
3
—
0.08
1
—
Abdallah Sima
—
—
3
—
0.26
—
—
Ismaëlo Ganiou
—
—
3
—
0.30
—
—
Matthieu Udol
—
—
3
1
0.42
—
—
Thorgan Hazard
—
—
2
—
0.08
1
—
Odsonne Édouard
—
—
2
—
0.12
—
—
Jonathan Gradit
—
—
2
—
0.15
—
—
Jean-Clair Todibo
—
—
2
—
0.09
—
—
Ruben Aguilar
—
—
2
—
0.08
—
—
Junior Kadile
1
0 (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.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Florian Thauvin
M
740
3.28
43
15.6
Ruben Aguilar
M
559
1.13
16
10.0
Matthieu Udol
M
602
1.35
7
8.6
Michal Skóras
M
402
1.57
8
4.6
Andrija Bulatovic
M
310
1.45
6
3.9
Florian Sotoca
M
282
0.96
7
2.4
Abdallah Sima
F
385
0.94
5
1.3
Thorgan Hazard
F
228
1.18
5
1.5
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Matthieu Udol
M
602
100
10
7
28
Ismaëlo Ganiou
D
460
89
11
6
20
Ruben Aguilar
M
559
89
17
8
25
Michaël Cuisance
M
496
82
11
7
34
Florian Thauvin
M
740
78
3
4
32
Yacine Titraoui
M
402
75
15
6
26
Kyllian Antonio
D
513
75
13
5
20
Michal Skóras
M
402
67
4
8
17
Full Squad Data
Every player with 100+ minutes (24 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Robin Risser
G
8
769
0
0.0
0
19
19
6.7
Florian Thauvin
M
8
740
4
3.8
27
68
78
15.6
Matthieu Udol
M
7
602
2
1.3
9
41
100
8.6
Ruben Aguilar
M
7
559
1
0.6
7
43
89
10.0
Kyllian Antonio
D
6
513
0
0.1
1
9
75
4.4
Michaël Cuisance
M
7
496
0
0.9
5
13
82
3.7
Ismaëlo Ganiou
D
5
460
1
0.8
1
16
89
5.8
Michal Skóras
M
7
402
0
0.1
7
28
67
4.6
Yacine Titraoui
M
6
402
0
0.0
0
13
75
4.7
Abdallah Sima
F
5
385
1
0.9
4
6
56
1.3
Amadou Haidara
M
7
351
0
0.2
0
7
49
2.5
Andrija Bulatovic
M
7
310
0
0.3
5
14
46
3.9
Franjo Ivanovic
F
6
299
2
0.6
2
2
41
1.0
Florian Sotoca
M
5
282
1
0.8
3
9
33
2.4
Odsonne Édouard
F
6
272
1
1.3
3
0
16
0.7
Souleymane Sagnan
D
3
268
0
0.1
0
12
50
3.0
Thorgan Hazard
F
6
228
1
0.8
3
6
28
1.5
Jean-Clair Todibo
D
4
205
0
0.1
0
2
42
1.7
Samson Baidoo
D
3
177
0
0.0
0
7
39
1.7
Saud Abdulhamid
M
3
169
1
0.1
1
10
25
2.1
Maik Nawrocki
D
2
160
0
0.1
0
6
19
1.7
Jonathan Gradit
D
3
156
0
0.2
1
5
35
1.7
Mezian Mesloub
M
4
145
0
0.1
2
5
18
1.4
Junior Kadile
M
3
109
0
0.1
1
3
17
0.7
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).