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

Angers

A territorially-dominated side, aggressive high-press out of possession, with a moderate attack. Currently #14 of 18 on 8 points (2-2-4, 9:15). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

territorially-dominatedaggressive high-pressmoderate attack
D
L
D
L
L
D
D
L
W
L
D
W
L
L
D
8
points
#14 of 18 · 8 games
9:15
goals
-6 GD
2-2-4
record
W-D-L
1.00
points/game
#14 in the league
1.31
xG for/game
rank #11
1.67
xG against/game
rank #14
#12
press rank
of 18 · most aggressive
43%
field tilt
#15
Angers
League average
Expected goals for / game
1.311.41
Expected goals against / game
1.671.41
Field tilt
43%50%
Pass retention
82%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 Angers and how good was the season?
Read. Angers currently sit #14 of 18 on 8 points (2W-2D-4L, 1.00 pts/game), scoring 9 and conceding 15 for a goal difference of -6. On the ball they are a territorially-dominated team (43% field tilt, #15 in the league); off it they defend with a aggressive high-press (#12 of 18 for press intensity). Across the 8 matches of event data, they create 1.31 xG/game (#11) and concede 1.67 (#14), a net of -0.36 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

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

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

#teamPWDLGFGAGDPts
11Toulouse82421211+110
12Auxerre83141218-610
13Brest82331412+29
14Angers8224915-68
15Le Mans81431116-57
16Strasbourg82151218-67
17Troyes8125516-115

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Angers 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+'+0.89-1.77
Vision AI Model Insight
Angers tend to come alive after the break — first-half net xG -2.92, second-half +0.01. Their strongest period is 61-75' (net +0.89 xG); their most dangerous period to face is 46-60' (net -1.77 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Angers 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 (-2.9 xG). Hover a point for that match.

05101410.413.4Lille (H) 0-2 · xG 1.94 to 0.87Auxerre (A) 3-1 · xG 1.21 to 2.08Rennes (H) 1-2 · xG 1.87 to 1.52Le Havre (A) 0-0 · xG 0.65 to 1.66Troyes (H) 2-0 · xG 1.45 to 1.28Brest (A) 1-5 · xG 1.16 to 2.75Marseille (H) 2-5 · xG 1.71 to 2.51Lorient (H) 0-0 · xG 0.45 to 0.68M1M2M3M4M5M6M7M8
AngersOpponents against Angers

Tactical DNA

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

22
Build-Up
possession control from the back
22
Progression
moving the ball upfield with threat
37
Creation
manufacturing chances
25
Press
winning the ball high & hard
22
Solidity
resisting the opponent's threat
Genetic identity
Angers are defined most by their Creation DNA (37/100 · limited at manufacturing chances), and least by their Build-Up DNA (22/100). 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).

Possess15Disrupt25Finish23Press5Defend7
Possess
Deep buildup
35%
Possession
10%
Field tilt
0%
Disrupt
Central progression ~proxy
20%
Dribble tendency
50%
Progressive passes
5%
Finish
Final-third patience
40%
Shot quality
25%
Open-play xG
5%
Press
Forward press ~proxy
0%
High regains
5%
Pressing efficiency ~proxy
10%
Defend
Def-mid press ~proxy
10%
High line ~proxy
10%
PAdj defensive actions
0%
Angers is defined most by Disrupt (25% in the league) and weakest on Press (5%). 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 Angers actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Angers'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; Angers 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/gAngers40%52%63%74%0.20.91.52.1FIELD TILT %POINTS / GAME
Vision AI Model Insight
Angers post 43% field tilt, ranking #15 of 18 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 1.00 points/game sits below the league-average return — territory is genuinely converting into results.

Where the time goes — how long each phase lasts

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

The share of Angers'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: 30.5% of the time on the ball31%Progression: 47.7% of the time on the ball48%Chance creation: 19.2% of the time on the ball19%Attacking transition: 2.5% of the time on the ball48%PROGRESSION
PhaseShare of the time
Build-up30.5%
Progression47.7%
Chance creation19.2%
Attacking transition2.5%
Vision AI Model Insight
Progression is where Angers 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.

Anthony Lopes ↔ Jordan Lefort: 125 passes, 0.0 combined xTAnthony Lopes ↔ Ousmane Camara: 111 passes, 0.3 combined xTJordan Lefort ↔ Ousmane Camara: 106 passes, -0.2 combined xTBranco van den Boomen ↔ Jordan Lefort: 98 passes, 0.3 combined xTCarlens Arcus ↔ Ousmane Camara: 87 passes, -0.3 combined xTBranco van den Boomen ↔ Ousmane Camara: 79 passes, 0.8 combined xTBranco van den Boomen ↔ Joseph Kalulu: 77 passes, 0.2 combined xTJordan Lefort ↔ Joseph Kalulu: 77 passes, 0.1 combined xTBranco van den Boomen ↔ Carlens Arcus: 73 passes, 1.8 combined xTCarlens Arcus ↔ Jim Allevinah: 64 passes, 1.2 combined xTAmine Sbaï ↔ Joseph Kalulu: 64 passes, 2.3 combined xTBranco van den Boomen ↔ Yassin Belkhdim: 55 passes, -0.3 combined xTBranco van den Boomen ↔ Amine Sbaï: 50 passes, 1.1 combined xTCarlens Arcus ↔ Lilian Raolisoa: 48 passes, -0.2 combined xTBranco van den Boomen ↔ Jim Allevinah: 45 passes, 1.8 combined xTCarlens Arcus ↔ Yassin Belkhdim: 44 passes, 0.1 combined xTYassin Belkhdim ↔ Ousmane Camara: 40 passes, -0.3 combined xTBranco van den Boomen ↔ Lilian Raolisoa: 34 passes, 0.5 combined xTJordan Lefort ↔ Yassin Belkhdim: 34 passes, -0.3 combined xTAnthony Lopes ↔ Branco van den Boomen: 30 passes, -0.5 combined xTAnthony Lopes ↔ Carlens Arcus: 30 passes, -0.2 combined xTJordan Lefort ↔ Amine Sbaï: 28 passes, 0.1 combined xTYassin Belkhdim ↔ Joseph Kalulu: 25 passes, -0.2 combined xTOusmane Camara ↔ Lilian Raolisoa: 25 passes, -0.1 combined xTAnthony Lopes — isolate this player's connectionsLopesBranco van den Boomen — isolate this player's connectionsBoomenJim Allevinah — isolate this player's connectionsAllevinahYassin Belkhdim — isolate this player's connectionsBelkhdimHimad Abdelli — isolate this player's connectionsAbdelliAmine Sbaï — isolate this player's connectionsSbaïAmine El Ouazzani — isolate this player's connectionsOuazzaniJoseph Kalulu — isolate this player's connectionsKaluluEstéban Lepaul — isolate this player's connectionsLepaulLilian Raolisoa — isolate this player's connectionsRaolisoaOusmane Camara — isolate this player's connectionsCamaraCarlens Arcus — isolate this player's connectionsArcusJordan Lefort — isolate this player's connectionsLefortProsper Peter — isolate this player's connectionsPeterHarouna Djibirin — isolate this player's connectionsDjibirinBané Diatta — isolate this player's connectionsDiatta
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Lopes ↔ Lefort
125p · 0.0xT
Lopes ↔ Camara
111p · 0.3xT
Lefort ↔ Camara
106p · -0.2xT
Boomen ↔ Lefort
98p · 0.3xT
Arcus ↔ Camara
87p · -0.3xT
Boomen ↔ Camara
79p · 0.8xT
Boomen ↔ Kalulu
77p · 0.2xT
Lefort ↔ Kalulu
77p · 0.1xT
Boomen ↔ Arcus
73p · 1.8xT
Arcus ↔ Allevinah
64p · 1.2xT
Vision AI Model Insight
Busiest connection: Anthony Lopes ↔ Jordan Lefort (125 passes). Most dangerous per pass: Branco van den Boomen ↔ Jim Allevinah (0.04 xT/pass over 45 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Angers 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 Angers 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
3841
ACTIONS
6%5%12%6%4%10%10%9%9%9%7%2%1%2%7%PASSES
Carries
the ball moved with a player
985
ACTIONS
3%6%10%7%5%11%9%10%10%11%6%1%1%2%6%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (11.6% of all actions). 57% of actions run through the inside lanes (centre + both half-spaces) versus 43% down the two wings — an inside-dominant, half-space build. By third: 33% defensive, 48% middle, 19% 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. Angers leaned on their left (41%). The bars under the pitch put the league’s share beside theirs.

41%Left side19%Middle40%Right sideATTACKING →
Angers
41%19%40%
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. Angers made 323 this season (40.4 a match); 40% came into the left 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: 128 entries (40%)12840%LEFT WINGLeft half-space: 37 entries (11%)3711%LEFT HALF-SPACECentre: 19 entries (6%)196%CENTRERight half-space: 26 entries (8%)268%RIGHT HALF-SPACERight wing: 113 entries (35%)11335%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing12816.040%30%
Left half-space374.611%13%
Centre192.46%11%
Right half-space263.28%14%
Right wing11314.135%32%
Build-up2 sections

Build-Up — the pass map

The football question
How does Angers 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.

1281build-up passes attempted
84%completed
27%reach the middle third
0%go long into the final third

Pass types

387CB · 36%
77Long Wide · 7%
18Long Central · 2%
477Wide → FB · 44%
113Central · 11%

Sequence success — build-up

82build-up sequences this season
7%succeed — reach the next third or a shot
52%turned over with nothing to show
CB387 · 36%
left: 213 passes, most from Lefort213right: 174 passes, most from Camara174
Long Wide77 · 7%
right: 42 passes, most from Lopes42left: 35 passes, most from Lopes35
Long Central18 · 2%
left: 9 passes, most from Lopes9right: 9 passes, most from Lopes9
Wide → FB477 · 44%
right: 261 passes, most from Lopes261left: 216 passes, most from Lopes216
Central113 · 11%
right: 58 passes, most from Lopes58left: 55 passes, most from Lopes55
◆ Vision AI Insight
Angers build predominantly down the right, with Lopes as the fulcrum (296 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 → LHS def (74×).

Pass Explorer

Every pass of Angers’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. 324 progressive passes across 8 matches (40.5/game).

Origin lane

Right wing
35%
Right half-space
9%
Central
12%
Left half-space
9%
Left wing
35%
Progression is right-dominant: 44% right side · 12% central · 44% left.

Who generates it

Carlens Arcus
47 · 15%
Branco van den Boomen
47 · 15%
Amine Sbaï
46 · 14%
Joseph Kalulu
38 · 12%
Anthony Lopes
33 · 10%
Top two — Carlens Arcus & Branco van den Boomen — account for 29% of all progression.
PROGRESSION
40.5 prog passes/game
mostly right
→
PENETRATION
21% reach final third
22% reach the box
→
THREAT
the other 79% is recycled
progress ≠ danger
What came of it. 21% of progressive passes reached the final third and 22% the box; the rest was recycled in front of the block. 29% 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-spacesterile
Centralsterile
Left half-spacebalanced
Left wingefficient

Progression — the pass map

The football question
Once Angers 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.

1809progression passes attempted
87%completed
15%break into the final third
13%go backward into the defensive third

Pass types

421CB · 27%
112Long Wide · 7%
13Long Central · 1%
857Wide → FB · 54%
173Central · 11%

Sequence success — progression

123progression sequences this season
26%succeed — reach the next third or a shot
45%turned over with nothing to show
CB421 · 27%
left: 225 passes, most from Lefort225right: 196 passes, most from Camara196
Long Wide112 · 7%
left: 56 passes, most from Boomen56right: 56 passes, most from Boomen56
Long Central13 · 1%
right: 7 passes, most from Boomen7left: 6 passes, most from Boomen6
Wide → FB857 · 54%
right: 466 passes, most from Arcus466left: 391 passes, most from Boomen391
Central173 · 11%
left: 90 passes, most from Belkhdim90right: 83 passes, most from Boomen83
◆ Vision AI Insight
Angers progress predominantly down the right, with Boomen the busiest midfield outlet (288 progression passes). Only 15% of passes that start in midfield actually break the final-third line — the rest (72%) 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 (89×) — 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
37%
15% of passes are progressive-or-better; the remaining 85% 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 Angers actually progress the ball with their feet, not a pass?

256 progressive carries this season across the whole squad (26% of 985 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 42m. Most active carrier: Lefort (38). Filter to one player below.

First (83)Second (60)Third (57)Fourth (56)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 Angers'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.

103shots
10.4xG
0.10xG per shot
5big chances (0.3+ xG)
9goals
#11key passes / game in the league
#13box entries / game in the league
Attacking transition: 24 shots (23%)23%24Settled attack: 55 shots (53%)53%55Set piece: 24 shots (23%)23%24103SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 23% of shots2402.100.09
Cross500.840.17
Long ball100.050.05
Pass into the box / short pass1100.800.07
Own creation (carry, dribble, rebound)700.410.06
Settled attack 53% of shots5555.530.10
Cross1722.630.15
Cut-back800.650.08
Long ball300.160.05
Pass into the box / short pass1411.100.08
Own creation (carry, dribble, rebound)1320.990.08
Set piece 23% of shots2442.820.12
Corner2332.030.09
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
Amine Sbaï232.561
Jim Allevinah91.290
Joseph Kalulu70.641
Amine El Ouazzani50.511
Carlens Arcus50.390

Who takes them

PlayerShotsxGGoals
Prosper Peter122.242
Amine El Ouazzani131.862
Amine Sbaï191.321
Jim Allevinah161.110
Usman Simbakoli91.010
Vision AI Model Insight
The biggest source of Angers's chances, by xG, is settled attack (5.5 of 10.4 xG, 55 of 103 shots), mostly cross. 24 of the 103 shots (23%) came within 15 seconds of winning the ball. 24 of the 103 shots came from set pieces; 9 goals from 10.4 xG (-1.4).

Chance Creation — the pass map

The football question
How does Angers 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%
7Long Wide · 10%
13Long Central · 18%
20Wide → FB · 27%
28Central · 38%

Sequence success — final-third

117final-third sequences this season
26%succeed — produce a shot
38%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%
left: 4 passes, most from Lefort4
Long Wide7 · 10%
right: 4 passes, most from Kalulu4left: 3 passes, most from Sbaï3
Long Central13 · 18%
right: 8 passes, most from Boomen8left: 5 passes, most from Boomen5
Wide → FB20 · 27%
left: 11 passes, most from Sbaï11right: 9 passes, most from Sbaï9
Central28 · 38%
left: 15 passes, most from Sbaï15right: 13 passes, most from Allevinah13

Who creates — volume × threat

22Sbaï
13Boomen
8Allevinah
7Kalulu
5Arcus
3Ouazzani
3Lefort
73key passes #11 of 18
11.5box entries/game #13 of 18
30.5final-3rd entries/game #10 of 18
1.31xG/game #11 of 18
9goals #14 of 18
-1.4finishing vs xG #15 of 18
◆ Vision AI Insight
Angers lean right — 44% of their key passes come from that flank and its half-space (32 of 73), most often from Boomen (11). They funnel chances into the c of the final third, most often via RW att → C att (19 key passes, most often from Boomen). Sbaï is the primary source overall. They generate 1.31 xG a game and finish it wasteful — they under-perform their xG, led by Amine El Ouazzani (2G), Prosper Peter (2G), Harouna Djibirin (1G).

Crosses & Cutbacks — squad-wide

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

153 crosses: 46 found a team-mate (30%), 21 led to a shot (14%). 12 cut-backs: 6 found a team-mate (50%), 5 led to a shot (42%). 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 Angers actually cross from?

153 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. 25% come from one territory, the byline right wing; 8 come from the half-spaces and 0 from the centre.

deep right wing: 4 crosses (3%)3%4deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 5 crosses (3%)3%5advanced right wing: 32 crosses (21%)21%32advanced right half-space: 1 crosses (1%)1%1advanced centre: 0 crosses (0%)advanced left half-space: 2 crosses (1%)1%2advanced left wing: 34 crosses (22%)22%34byline right wing: 38 crosses (25%)25%38byline right half-space: 4 crosses (3%)3%4byline centre: 0 crosses (0%)byline left half-space: 1 crosses (1%)1%1byline left wing: 32 crosses (21%)21%32
TerritoryCrossesShareLed to a shot
byline · right wing3825%6
advanced · left wing3422%5
advanced · right wing3221%2
byline · left wing3221%7
deep · left wing53%0
deep · right wing43%0
byline · right half-space43%1
advanced · left half-space21%0
advanced · right half-space11%0
byline · left half-space11%0
Finishing3 sections

Shot Map

103 shots for 10.4 xG (1.31/game, #11 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

Moderate attack. 12.9 shots/game at 0.101 xG/shot. Box entries 12/game (#13). Threat created 10.2 xT/game (#13).

Goal Sequences

The move behind each of Angers’s 9 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 — 9 goals traced.

How Do They Score?

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

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

By situation

Open play
5 · 56%
Set pieces
3 · 33%
Penalties
1 · 11%

By finish

Right foot
2 · 22%
Left foot
3 · 33%
Header
4 · 44%
Vision AI Model Insight
9 goals scored. 56% come in open play, but 33% from set pieces — a genuine dead-ball weapon that bypasses the open-play build-up.
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

53 of 238 pass attempts lost here (22%).22%53/238Arcus24 of 205 pass attempts lost here (12%).12%24/205Camara49 of 458 pass attempts lost here (11%).11%49/458Lopes36 of 216 pass attempts lost here (17%).17%36/216Lopes47 of 164 pass attempts lost here (29%).29%47/164Kalulu58 of 383 pass attempts lost here (15%).15%58/383Allevinah40 of 388 pass attempts lost here (10%).10%40/388Boomen40 of 349 pass attempts lost here (11%).11%40/349Boomen44 of 338 pass attempts lost here (13%).13%44/338Lefort51 of 351 pass attempts lost here (15%).15%51/351Kalulu93 of 271 pass attempts lost here (34%).34%93/271Boomen29 of 78 pass attempts lost here (37%).37%29/78Allevinah15 of 52 pass attempts lost here (29%).29%15/52Sbaï35 of 80 pass attempts lost here (44%).44%35/80Sbaï93 of 270 pass attempts lost here (34%).34%93/270Boomenattacking →

How they lose it

Incomplete pass — attacking third
265
Failed forward pass
174
Failed take-on
61
Lost in the defensive third
209
Their weakest zone is the left half-space in the attacking third: 44% of 80 pass attempts there are lost (35 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 Angers 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.

13
Pressing Index
/100 · passive
Intensity13
PPDA, high-press share, high-zone actions
Height11
how high up the pitch they defend
Effectiveness11
high recoveries & high-regain share
Disruption17
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
21%
RHS
19%
C
22%
LHS
17%
LW
21%
By third (high / mid / low regain)
Def 53%
Mid 35%
Att 13%
Read
Ranked #12 of 18 for press intensity, this is a high press. Note the tension: 53% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (18% high-press share) means that when they do defend, it is often deep. Of recoveries, 48% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#12/18lower = more intense; rank is what matters
Defensive actions / game145#15/18
High-press share18%#17/18def actions won high up
Defensive-action height (0–100)36.2#16/18avg pitch height of actions
High recoveries / game18.4#17/18ball won in mid+att third
High-recovery share48%#15/18share of recoveries won high
Opponent completion allowed84%#13/18lower = more disruptive
Opponent progressive allowed9.9%#17/18of 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 Angers win it back with a defensive action?

Counted over the 227 opposition possessions that Angers 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 Angers step in. Angers win it after 6.6 opponent passes in the first half-hour and after 5.9 after the hour mark (sooner).

PASSES THEY GET
6.2passes
median 3 · before Angers win it
TIME THEY KEEP IT
19sec
median 11s · 28.4 wins per game
How many passes the opponent got in before the ball was won
36%
26%
19%
19%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.8
21s
15–30′
6.4
19s
30–45+′
6.2
21s
45–60′
5.7
16s
60–75′
8.1
23s
75–90+′
4.7
16s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Angers 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 Angers 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) 1,281 passes

nothing unusual in this zone

Width of use+0.2621.54
Wide-channel share+0.310.32
Side bias-0.67-2.35
Pass length-0.6020.55
Long-ball share-0.390.19
Forward gain per pass-0.598.91
Backward-pass share+0.110.20
Deep-pass share-0.280.26
Completion+0.470.83
Seconds between passes-0.333.12
Side used

left 26% · central 42% · right 31%

Progression (middle third) 1,809 passes

longer passing, slower

Width of use+0.4326.48
Wide-channel share+0.270.42
Side bias-0.38-1.46
Pass length+1.0018.62
Long-ball share+0.460.12
Forward gain per pass+0.093.75
Backward-pass share+0.410.35
Deep-pass share+0.370.18
Completion+0.380.87
Seconds between passes+0.973.62
Side used

left 34% · central 27% · right 38%

Final third 751 passes

played in the channels, touchline to touchline, longer passing

Width of use+1.7335.87
Wide-channel share+1.750.73
Side bias+0.090.16
Pass length+1.2017.32
Long-ball share+0.730.13
Forward gain per pass-0.110.90
Backward-pass share+0.150.40
Deep-pass share+0.020.09
Completion-0.630.64
Seconds between passes+0.303.62
Side used

left 45% · central 11% · right 44%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Angers'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 Angers 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 share15%
#15 of 18 · reaches final third in ≤3 passes
Patient build-up share26%
#12 of 18 · spells of 6+ passes
Tempo (possession length)16.4s
#6 of 18 · shorter = faster tempo
Passes per possession4.4
#12 of 18
Counter-attack shots /game1.31
#4 of 18 · shot within 12s of a regain in own half
Press→shot /game2.64
#15 of 18 · shot within 8s of a high regain
Speed to final third after regain12.8s
#9 of 18 · lower = faster break

Sequence success — attacking transition

6attacking transition sequences this season
17%succeed — produce a shot
17%turned over with nothing to show

Sequence success — defensive transition

16defensive transition sequences this season
75%succeed — reach the next third or a shot
12%turned over with nothing to show
Vision AI Model Insight
Angers are a patient build-up side: 15% of possessions reach the final third in 3 passes or fewer (#15 of 18), against 26% built patiently over 6+ passes (#12 of 18). Winning the ball back leads to a shot inside 12 seconds 1.31 times a game (#4), and a high regain converts to a shot within 8 seconds 2.64 times a game (#15 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 Angers? 401 opponent progressive passes and 132 shots faced (13.4 xG against) across the season.

Opponent threat by lane (attacking into Angers)

Right wing
30%
Right half-space
14%
Central
15%
Left half-space
13%
Left wing
28%
Where the danger came from. Opponents generated most of their threat through the right wing (30% of the danger conceded).

How Do They Concede?

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

Every goal Angers conceded across the loaded matches — the opponent's shots in Angers'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 (101 total)

4%4%4%14%17%16%26%14%Ethan MbappéHákon HaraldssonNabil BentalebRomain PerraudHákon HaraldssonAyumu SekoKaito MizutaNabil BentalebKaito MizutaKaito MizutaAmir RichardsonAmir RichardsonKaito MizutaAmir RichardsonSota NakamuraJosh MajaAmir RichardsonIsmaïl BounebDanny NamasoLamine SyRomain FaivreRomain FaivreKévin DanoisKévin DanoisNaouirou AhamadaRémy Labeau LascaryNaouirou AhamadaNaouirou AhamadaNaouirou AhamadaLamine SyNaouirou AhamadaAristide ZossouMousa Al TamariSebastian SzymanskiLudovic BlasLudovic BlasLudovic BlasQuentin MerlinQuentin MerlinMousa Al TamariValentin RongierMousa Al TamariMahdi CamaraSebastian SzymanskiMahdi CamaraPrzemyslaw FrankowskiAdrien ThomassonAdrien ThomassonPathé MboupHugo MagnettiKamory DoumbiaJoris ChotardLucas TousartArsène KouassiArsène KouassiArthur AvomNoah CadiouArsène KouassiArthur AvomArthur AvomGabin BernardeauJérémy Le DouaronAnis OuzenadjiJérémy Le DouaronAntoine MilleAntoine MilleJunior DiazJérémy Le DouaronDermane KarimAdrien MonfrayNoah DonkorHugo PicardHugo PicardIron GomisHugo MagnettiPathé MboupMama BaldéLudovic AjorqueLucas TousartBradley LockoIbrahim KantéNoah EdjoumaBradley LockoArsène KouassiEmersonHimad AbdelliAmine GouiriEmersonAmine HaritAmine HaritHimad AbdelliTimothy WeahAmine GouiriNouhoum KamissokoEmersonHimad AbdelliHimad AbdelliEmersonTochukwu NnadiTimothy WeahAmine Harit← own goal

By situation

Open play
11 · 79%
Set pieces
2 · 14%
Penalties
1 · 7%
Vision AI Model Insight
14 goals conceded. 79% come in open play; set pieces account for only 14%, so dead-ball defending is not the main issue. 29% 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
5 g · 7.6 xG
Set pieces
3 g · 2.0 xG
Penalties
1 g
33% of goals come from set pieces (3 of 9), worth 2.0 xG from 23 shots. A genuine set-piece weapon — defend the box seriously.

Where do Angers's corners go?

51 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 (27)

15%56%7%15%7%
Delivered into the box 100%Short 0%

Left side (24)

12%4%8%4%4%33%29%
Delivered into the box 96%Short 4%

Where opponents attack Angers from set pieces

20 shots from opponent corners against Angers, 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 (13)

8%15%62%15%
Shot 13Goals 1

Left flag (7)

43%29%29%
Shot 7Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • none stand out
Weaknesses (bottom-third vs league)
  • field tilt % — 43.45 (17th pct)
  • progression /game — 40.50 (17th pct)
  • xG conceded /game — 1.67 (22th pct)
  • box entries /game — 11.50 (22th pct)
  • threat created /game — 10.18 (28th 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.

Le Mans
78%
Strasbourg
70%
Auxerre
67%
Lille
48%
Troyes
29%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)1.501.501.50
vs mid-block opponents (2m)1.503.500.00
vs low-block opponents (4m)0.751.251.25

Behaviour — how Angers actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents78%18%5211.118.0
vs mid-block opponents80%13%359.410.0
vs low-block opponents83%14%3810.19.0
Vision AI Model Insight
Facing a high press, retention drops to 78% vs 83% against a low block (5pt lower under pressure), and directness (long-ball share) sits at 18% when pressed vs 14% 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. Angers are territorially-dominated with a aggressive high-press. Their attack creates 1.31 xG a game and they concede 1.67 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 Angers’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.

Angers
across 8 matches this season
Progressive passesvs Lille · 0-2 · 2026-08-2360avg 40
PPDAvs Lorient · 0-0 · 2026-10-259.8avg 6.0
Final-third entriesvs Lorient · 0-0 · 2026-10-2558avg 40
Defensive actionsat Auxerre · 3-1 · 2026-08-29172avg 145
Passesat Auxerre · 3-1 · 2026-08-29364avg 480
Field tiltvs Lille · 0-2 · 2026-08-2359%avg 43%
Pass accuracyat Auxerre · 3-1 · 2026-08-2976%avg 81%
Expected goalsvs Lorient · 0-0 · 2026-10-250.45avg 1.31

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 Angers’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).

+12.1on-ball value, 8 matches
Where the value came from
Passes3841 actions+4.34
Carries985 actions+0.18
Dribbles103 actions+0.17
Shots103 actions+5.36
Ball wins450 actions+2.11
Most on-ball value (OBV)ActionsOBVper 100
Amine Sbaï406+2.51+0.62
Amine El Ouazzani165+1.45+0.88
Prosper Peter79+1.14+1.45
Ousmane Camara504+1.01+0.20
Jim Allevinah319+0.93+0.29
Anthony Lopes438+0.82+0.19
Branco van den Boomen712+0.81+0.11
Carlens Arcus438+0.68+0.15
123456
Biggest single movesOBV
1  Amine El Ouazzani · shot+0.806
2  Joseph Kalulu · pass+0.385
3  Ousmane Camara · pass+0.379
4  Prosper Peter · shot+0.357
5  Anthony Bermont · shot+0.298
6  Amine Sbaï · take-on+0.279

Set Pieces by Player

Who delivers Angers’s dead balls and who finishes them this season. 51 corners taken, most by Branco van den Boomen (50); 23 shots from corners and free kicks, 3 goals, led by Amine El Ouazzani (1 goals, 0.35 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
Branco van den Boomen5047 (94%)——0.00——
Amine El Ouazzani——410.35—1/1
Amine Sbaï11 (100%)3—0.10——
Usman Simbakoli——3—0.45——
Carlens Arcus——310.21——
Ousmane Camara——2—0.25——
Harouna Djibirin——210.11——
Anthony Bermont——1—0.06——
Prosper Peter——1—0.17——
Joseph Kalulu——1—0.03——
Marius Louër——1—0.11——
Jordan Lefort——1—0.16——
Emmanuel Biumla——1—0.05——

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
Anthony LopesGK7657.1Shot-Stopping 71%
Joseph KaluluFB6006.1Ball-Carrying 52%Ball-Winning 49%Wide Delivery 7%
Branco van den BoomenCM7655.2Progression 74%Chance Creation 68%Ball-Carrying 46%Successful Dribble 14%
Jim AllevinahW5924.7Box Threat 89%Chance Creation 36%Ball-Carrying 34%Wide Delivery 28%
Ousmane CamaraCB6064.5Ball-Winning 44%Aerial & Box Defending 38%Progression 24%Ball-Carrying 18%
Jordan LefortCB6704.0Ball-Carrying 60%Progression 50%Ball-Winning 44%Aerial & Box Defending 26%
Amine El OuazzaniST5313.6Ball-Carrying 50%Box Threat 30%Finishing 25%Aerial Threat 0%
Carlens ArcusFB5183.5Ball-Carrying 60%Ball-Winning 49%Wide Delivery 5%
Amine SbaïW6952.5Ball-Carrying 61%Chance Creation 42%Box Threat 37%Wide Delivery 22%
Yassin BelkhdimCM6722.5Progression 12%Chance Creation 7%Ball-Carrying 6%Successful Dribble 3%

Top Creators

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

playerposminkey P /90box entriesxT
Amine SbaïM6952.85218.7
Branco van den BoomenM7651.531814.8
Jim AllevinahM5921.22104.7
Joseph KaluluD6001.0576.7
Carlens ArcusD5180.8787.7
Jordan LefortD6700.4059.1
Amine El OuazzaniF5310.5151.4
Lilian RaolisoaD3750.0074.9

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)
Amine SbaïW69516 (25%)5 (40%)
Lilian RaolisoaFB37516 (25%)4 (25%)
Joseph KaluluFB6006 (33%)7 (29%)
Jim AllevinahW5926 (50%)3 (67%)
Carlens ArcusFB5183 (67%)4 (75%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Jordan LefortD6701095726
Branco van den BoomenM7659714228
Joseph KaluluD60093121029
Yassin BelkhdimM67293161221
Ousmane CamaraD606908615
Jim AllevinahM592894535
Amine El OuazzaniF531835113
Carlens ArcusD518779822

Full Squad Data

Every player with 100+ minutes (19 players).

playerposappsmingoalsxGkey PprogdefxT
Anthony LopesG876500.0033287.3
Branco van den BoomenM876510.113479714.8
Amine SbaïM869511.32246648.7
Yassin BelkhdimM867200.1312933.1
Jordan LefortD767000.23281099.1
Ousmane CamaraD760600.229905.6
Joseph KaluluD760000.0738936.7
Jim AllevinahM859201.1818894.7
Amine El OuazzaniF853121.931831.4
Carlens ArcusD751810.2547777.7
Lilian RaolisoaD737510.4024634.9
Prosper PeterF836622.220400.3
Anthony BermontM518900.812280.9
Harouna DjibirinM716210.422330.8
Haris BelkeblaM315300.002310.9
Bané DiattaM514900.103220.7
Emmanuel BiumlaD213500.005251.2
Maël GernigonD213100.000200.4
Usman SimbakoliF611101.011340.5

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.

Anthony Lopes
Goalkeeper · Goalkeeper
minutes765
goals · xG0 · 0.0
prog passes /903.9
key passes /900.00
def actions /903.3
pass accuracy87%
Branco van den Boomen
Advanced creator · Attacking mid
minutes765
goals · xG1 · 0.1
prog passes /905.5
key passes /901.53
def actions /9011.4
pass accuracy79%
Amine Sbaï
Advanced creator · Attacking mid
minutes695
goals · xG1 · 1.3
prog passes /906.0
key passes /902.85
def actions /908.3
pass accuracy68%
Yassin Belkhdim
Ball-winner / destroyer · Midfielder
minutes672
goals · xG0 · 0.1
prog passes /901.6
key passes /900.40
def actions /9012.5
pass accuracy85%
Jordan Lefort
Stopper / marker · Defender
minutes670
goals · xG0 · 0.2
prog passes /903.8
key passes /900.40
def actions /9014.6
pass accuracy85%
Ousmane Camara
Stopper / marker · Defender
minutes606
goals · xG0 · 0.2
prog passes /901.3
key passes /900.30
def actions /9013.4
pass accuracy93%
Joseph Kalulu
Ball-playing defender · Defender
minutes600
goals · xG0 · 0.0
prog passes /905.7
key passes /901.05
def actions /9013.9
pass accuracy79%
Jim Allevinah
Ball-winner / destroyer · Midfielder
minutes592
goals · xG0 · 1.1
prog passes /902.7
key passes /901.22
def actions /9013.5
pass accuracy77%
Amine El Ouazzani
Ball-winner / destroyer · Midfielder
minutes531
goals · xG2 · 1.9
prog passes /900.2
key passes /900.51
def actions /9014.1
pass accuracy72%

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: field tilt % (17th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (43.45, 17th percentile vs the league).
Need — bottom-third: progression /game (17th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (40.50, 17th percentile vs the league).
Need — bottom-third: xG conceded /game (22th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.67, 22th percentile vs the league).
Vision AI · building report