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Team reportLigue 1 2025/26

Angers

A territorially-dominated side, moderate-press out of possession, with a low-output attack. Finished #13 of 18 on 36 points (9-9-16, 29:48). Tactical profile below is built from 34 matches of ball-by-ball event data, contextualised against the league.

territorially-dominatedmoderate-presslow-output attack
D
L
D
L
L
D
D
L
W
L
D
W
L
L
D
36
points
#13 of 18 · 34 games
29:48
goals
-19 GD
9-9-16
record
W-D-L
1.06
points/game
#13 in the league
0.90
xG for/game
rank #18
1.46
xG against/game
rank #15
#18
press rank
of 18 · most aggressive
39%
field tilt
#18
Angers
League average
Expected goals for / game
0.901.30
Expected goals against / game
1.461.30
Field tilt
39%50%
Pass retention
81%82%
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 finished #13 of 18 on 36 points (9W-9D-16L, 1.06 pts/game), scoring 29 and conceding 48 for a goal difference of -19. On the ball they are a territorially-dominated team (39% field tilt, #18 in the league); off it they defend with a moderate-press (#18 of 18 for press intensity). Across the 34 matches of event data, they create 0.90 xG/game (#18) and concede 1.46 (#15), a net of -0.56 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
10Lorient341112114851-345
11Paris FC341111124750-344
12Brest34109154355-1239
13Angers3499162948-1936
14Le Havre34714133244-1235
15Auxerre34810163444-1034
16Nice34711163760-2332

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+'+1.51-5.24
Vision AI Model Insight
Angers tend to come alive after the break — first-half net xG -13.15, second-half -6.01. Their strongest period is 76-90+' (net +1.51 xG); their most dangerous period to face is 46-60' (net -5.24 xG against them).

xG Race — the season, match by match

Expected goals piling up over 34 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 (-19.2 xG). Hover a point for that match.

018365430.549.6Paris FC (H) 1-0 · xG 0.73 to 0.83PSG (A) 0-1 · xG 0.21 to 1.97Rennes (H) 1-1 · xG 0.96 to 1.49Metz (A) 1-1 · xG 2.03 to 1.72Lyon (A) 0-1 · xG 1.21 to 1.90Brest (H) 0-2 · xG 0.81 to 1.39Strasbourg (A) 0-5 · xG 0.37 to 3.27Monaco (H) 1-1 · xG 1.71 to 1.24Lorient (H) 2-0 · xG 0.97 to 2.07Marseille (A) 2-2 · xG 0.91 to 1.15Lille (A) 0-1 · xG 0.34 to 1.61Auxerre (H) 2-0 · xG 1.08 to 0.84Toulouse (A) 1-0 · xG 0.38 to 1.74Lens (H) 1-2 · xG 0.79 to 1.54Nice (A) 1-0 · xG 0.61 to 0.93Nantes (H) 4-1 · xG 2.24 to 0.39Le Havre (A) 1-2 · xG 0.55 to 1.27Marseille (H) 2-5 · xG 0.72 to 2.33Paris FC (A) 0-0 · xG 0.60 to 0.74Metz (H) 1-0 · xG 1.28 to 0.46Toulouse (H) 1-0 · xG 0.79 to 0.68Lorient (A) 0-2 · xG 0.59 to 1.13Lille (H) 0-1 · xG 0.36 to 2.18Monaco (A) 0-2 · xG 0.82 to 1.55Nantes (A) 1-0 · xG 0.69 to 0.77Nice (H) 0-2 · xG 0.78 to 0.93Lens (A) 1-5 · xG 1.44 to 2.65Lyon (H) 0-0 · xG 0.41 to 0.87Rennes (A) 1-2 · xG 1.11 to 0.99Le Havre (H) 1-1 · xG 0.84 to 1.53PSG (H) 0-3 · xG 0.84 to 2.13Auxerre (A) 1-3 · xG 2.04 to 1.77Strasbourg (H) 1-1 · xG 0.66 to 1.89Brest (A) 1-1 · xG 0.58 to 1.68M1M5M9M13M17M21M25M29M33
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.

17
Build-Up
possession control from the back
3
Progression
moving the ball upfield with threat
0
Creation
manufacturing chances
0
Press
winning the ball high & hard
17
Solidity
resisting the opponent's threat
Genetic identity
Angers are defined most by their Build-Up DNA (17/100 · limited at possession control from the back), and least by their Creation DNA (0/100). 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: 70% tilt, 2.24 pts/gLens: 55% tilt, 2.06 pts/gLille: 62% tilt, 1.79 pts/gLyon: 53% tilt, 1.76 pts/gRennes: 53% tilt, 1.74 pts/gMarseille: 61% tilt, 1.74 pts/gMonaco: 54% tilt, 1.59 pts/gStrasbourg: 52% tilt, 1.56 pts/gToulouse: 49% tilt, 1.32 pts/gLorient: 43% tilt, 1.32 pts/gParis FC: 47% tilt, 1.29 pts/gBrest: 43% tilt, 1.15 pts/gAngers: 39% tilt, 1.06 pts/gLe Havre: 43% tilt, 1.03 pts/gAuxerre: 49% tilt, 1.00 pts/gNice: 44% tilt, 0.94 pts/gNantes: 41% tilt, 0.71 pts/gMetz: 43% tilt, 0.50 pts/gAngers39%49%60%70%0.51.11.72.2FIELD TILT %POINTS / GAME
Vision AI Model Insight
Angers post 39% field tilt, ranking #18 of 18 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 1.06 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: 32.4% of the time on the ball32%Progression: 45.5% of the time on the ball46%Chance creation: 18.6% of the time on the ball19%Attacking transition: 3.4% of the time on the ball46%PROGRESSION
PhaseShare of the time
Build-up32.4%
Progression45.5%
Chance creation18.6%
Attacking transition3.4%
Vision AI Model Insight
Progression is where Angers spends most of its time on the ball (46% 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.

Jordan Lefort ↔ Ousmane Camara: 647 passes, 6.9 combined xTHervé Koffi ↔ Jordan Lefort: 479 passes, 17.8 combined xTCarlens Arcus ↔ Ousmane Camara: 424 passes, 15.6 combined xTJordan Lefort ↔ Jacques Ekomié: 398 passes, 24.1 combined xTHaris Belkebla ↔ Jordan Lefort: 297 passes, 10.3 combined xTHaris Belkebla ↔ Carlens Arcus: 278 passes, 8.7 combined xTCarlens Arcus ↔ Yassin Belkhdim: 278 passes, 11.2 combined xTHervé Koffi ↔ Ousmane Camara: 214 passes, 7.1 combined xTHaris Belkebla ↔ Ousmane Camara: 211 passes, 6.4 combined xTJordan Lefort ↔ Himad Abdelli: 171 passes, 6.9 combined xTHaris Belkebla ↔ Jacques Ekomié: 168 passes, 5.6 combined xTCarlens Arcus ↔ Lilian Raolisoa: 162 passes, 10.3 combined xTFlorent Hanin ↔ Jordan Lefort: 154 passes, 7.1 combined xTHaris Belkebla ↔ Yassin Belkhdim: 150 passes, 4.5 combined xTJordan Lefort ↔ Amine Sbaï: 149 passes, 16.4 combined xTHaris Belkebla ↔ Himad Abdelli: 139 passes, 3.7 combined xTCarlens Arcus ↔ Louis Mouton: 133 passes, 9.5 combined xTOusmane Camara ↔ Lilian Raolisoa: 130 passes, 7.2 combined xTHaris Belkebla ↔ Louis Mouton: 126 passes, 5.1 combined xTJacques Ekomié ↔ Amine Sbaï: 123 passes, 8.7 combined xTCarlens Arcus ↔ Hervé Koffi: 121 passes, 8.0 combined xTYassin Belkhdim ↔ Ousmane Camara: 109 passes, 4.8 combined xTHaris Belkebla ↔ Amine Sbaï: 108 passes, 5.0 combined xTCarlens Arcus ↔ Himad Abdelli: 106 passes, 3.9 combined xTJordan Lefort — isolate this player's connectionsLefortEstéban Lepaul — isolate this player's connectionsLepaulHaris Belkebla — isolate this player's connectionsBelkeblaAnthony Lopes — isolate this player's connectionsLopesOusmane Camara — isolate this player's connectionsCamaraLilian Raolisoa — isolate this player's connectionsRaolisoaJacques Ekomié — isolate this player's connectionsEkomiéLouis Mouton — isolate this player's connectionsMoutonHervé Koffi — isolate this player's connectionsKoffiProsper Peter — isolate this player's connectionsPeterYassin Belkhdim — isolate this player's connectionsBelkhdimCarlens Arcus — isolate this player's connectionsArcusAmine Sbaï — isolate this player's connectionsSbaïFlorent Hanin — isolate this player's connectionsHaninHimad Abdelli — isolate this player's connectionsAbdelliLanroy Machine — isolate this player's connectionsMachine
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Lefort ↔ Camara
647p · 6.9xT
Koffi ↔ Lefort
479p · 17.8xT
Arcus ↔ Camara
424p · 15.6xT
Lefort ↔ Ekomié
398p · 24.1xT
Belkebla ↔ Lefort
297p · 10.3xT
Belkebla ↔ Arcus
278p · 8.7xT
Arcus ↔ Belkhdim
278p · 11.2xT
Koffi ↔ Camara
214p · 7.1xT
Belkebla ↔ Camara
211p · 6.4xT
Lefort ↔ Abdelli
171p · 6.9xT
Vision AI Model Insight
Busiest connection: Jordan Lefort ↔ Ousmane Camara (647 passes). Most dangerous per pass: Jordan Lefort ↔ Amine Sbaï (0.11 xT/pass over 149 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 306 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
14825
ACTIONS
6%6%12%6%6%9%8%10%9%10%5%2%2%2%5%PASSES
Carries
the ball moved with a player
3543
ACTIONS
4%5%9%7%5%10%9%11%11%12%5%2%2%3%6%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (11.7% 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: 35% defensive, 48% middle, 17% 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 (43%). The bars under the pitch put the league’s share beside theirs.

43%Left side19%Middle38%Right sideATTACKING →
Angers
43%19%38%
League
39%22%39%

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 1044 this season (30.7 a match); 32% 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: 336 entries (32%)33632%LEFT WINGLeft half-space: 158 entries (15%)15815%LEFT HALF-SPACECentre: 94 entries (9%)949%CENTRERight half-space: 136 entries (13%)13613%RIGHT HALF-SPACERight wing: 320 entries (31%)32031%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing3369.932%30%
Left half-space1584.615%15%
Centre942.89%11%
Right half-space1364.013%14%
Right wing3209.431%30%
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.

5400build-up passes attempted
82%completed
27%reach the middle third
1%go long into the final third

Pass types

1870CB · 42%
260Long Wide · 6%
38Long Central · 1%
1819Wide → FB · 41%
456Central · 10%

Sequence success — build-up

1015build-up sequences this season
10%succeed — reach the next third or a shot
44%turned over with nothing to show
CB1870 · 42%
left: 1045 passes, most from Lefort1045right: 825 passes, most from Camara825
Long Wide260 · 6%
left: 133 passes, most from Koffi133right: 127 passes, most from Koffi127
Long Central38 · 1%
left: 24 passes, most from Koffi24right: 14 passes, most from Koffi14
Wide → FB1819 · 41%
left: 933 passes, most from Koffi933right: 886 passes, most from Arcus886
Central456 · 10%
right: 235 passes, most from Arcus235left: 221 passes, most from Koffi221
◆ Vision AI Insight
Angers build predominantly down the right, with Lefort as the fulcrum (989 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 (266×).

Pass Explorer

Every pass of Angers’s last 10 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. 1197 progressive passes across 34 matches (35.2/game).

Origin lane

Right wing
31%
Right half-space
10%
Central
11%
Left half-space
12%
Left wing
35%
Progression is left-dominant: 41% right side · 11% central · 47% left.

Who generates it

Carlens Arcus
168 · 14%
Jordan Lefort
149 · 12%
Lilian Raolisoa
105 · 9%
Jacques Ekomié
99 · 8%
Branco van den Boomen
91 · 8%
Top two — Carlens Arcus & Jordan Lefort — account for 26% of all progression.
PROGRESSION
35.2 prog passes/game
mostly left
→
PENETRATION
26% reach final third
17% reach the box
→
THREAT
the other 74% is recycled
progress ≠ danger
What came of it. 26% of progressive passes reached the final third and 17% the box; the rest was recycled in front of the block. 26% of the progression ran through two players, mostly down the left 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 wingbalanced
Right half-spacebalanced
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.

6954progression passes attempted
84%completed
13%break into the final third
12%go backward into the defensive third

Pass types

1433CB · 25%
200Long Wide · 3%
29Long Central · 0%
3383Wide → FB · 58%
794Central · 14%

Sequence success — progression

1399progression sequences this season
23%succeed — reach the next third or a shot
43%turned over with nothing to show
CB1433 · 25%
left: 809 passes, most from Lefort809right: 624 passes, most from Camara624
Long Wide200 · 3%
right: 107 passes, most from Boomen107left: 93 passes, most from Abdelli93
Long Central29 · 0%
left: 15 passes, most from Arcus15right: 14 passes, most from Arcus14
Wide → FB3383 · 58%
left: 1767 passes, most from Ekomié1767right: 1616 passes, most from Arcus1616
Central794 · 14%
right: 438 passes, most from Belkebla438left: 356 passes, most from Belkebla356
◆ Vision AI Insight
Angers progress predominantly down the left, with Belkebla the busiest midfield outlet (732 progression passes). Only 13% of passes that start in midfield actually break the final-third line — the rest (75%) is recycled back into midfield or (12%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LHS mid → LW mid (323×) — 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)
12%
Progressive
1%
Neutral / sideways
52%
Safe / backward
35%
13% of passes are progressive-or-better; the remaining 87% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.

Carries Map — progressive ball-carries, squad-wide

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

863 progressive carries this season across the whole squad (25% of 3415 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 58m. Most active carrier: Sbaï (122). Filter to one player below.

First (283)Second (218)Third (215)Fourth (147)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.

316shots
30.5xG
0.10xG per shot
13big chances (0.3+ xG)
28goals
#18key passes / game in the league
#18box entries / game in the league
Attacking transition: 87 shots (28%)28%87Settled attack: 172 shots (54%)54%172Set piece: 57 shots (18%)18%57316SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 28% of shots8798.150.09
Cross630.890.15
Cut-back710.910.13
Long ball510.740.15
Pass into the box / short pass4624.010.09
Own creation (carry, dribble, rebound)2321.580.07
Settled attack 54% of shots1721315.240.09
Cross5365.530.10
Cut-back921.310.15
Long ball1100.680.06
Pass into the box / short pass6525.230.08
Own creation (carry, dribble, rebound)3432.490.07
Set piece 18% of shots5767.080.12
Corner4632.960.06
Free kick600.140.02
Penalty533.970.79

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
Lilian Raolisoa222.834
Amine Sbaï252.782
Louis Mouton171.911
Carlens Arcus171.693
Prosper Peter121.591

Who takes them

PlayerShotsxGGoals
Prosper Peter234.775
Amine Sbaï343.753
Goduine Koyalipou222.772
Louis Mouton362.762
Sidiki Cherif282.654
Vision AI Model Insight
The biggest source of Angers's chances, by xG, is settled attack (15.2 of 30.5 xG, 172 of 316 shots), mostly cross. 87 of the 316 shots (28%) came within 15 seconds of winning the ball. 57 of the 316 shots came from set pieces; 28 goals from 30.5 xG (-2.5).

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

13CB · 6%
14Long Wide · 6%
23Long Central · 10%
76Wide → FB · 34%
96Central · 43%

Sequence success — final-third

736final-third sequences this season
21%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
CB13 · 6%
left: 7 passes, most from Lefort7right: 6 passes, most from Louër6
Long Wide14 · 6%
left: 8 passes, most from Raolisoa8right: 6 passes, most from Boomen6
Long Central23 · 10%
left: 13 passes, most from Boomen13right: 10 passes, most from Boomen10
Wide → FB76 · 34%
left: 45 passes, most from Belkebla45right: 31 passes, most from Arcus31
Central96 · 43%
right: 50 passes, most from Raolisoa50left: 46 passes, most from Sbaï46

Who creates — volume × threat

27Boomen
26Sbaï
22Raolisoa
21Mouton
16Arcus
15Belkebla
14Belkhdim
222key passes #18 of 18
8.0box entries/game #18 of 18
22.9final-3rd entries/game #17 of 18
0.90xG/game #18 of 18
28goals #17 of 18
-2.5finishing vs xG #15 of 18
◆ Vision AI Insight
Angers lean right — 39% of their key passes come from that flank and its half-space (86 of 222), most often from Arcus (16). They funnel chances into the c of the final third, most often via RW att → C att (43 key passes, most often from Boomen). Boomen is the primary source overall. They generate 0.90 xG a game and finish it wasteful — they under-perform their xG, led by Prosper Peter (5G), Sidiki Cherif (4G), Amine Sbaï (3G).

Crosses & Cutbacks — squad-wide

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

402 crosses: 132 found a team-mate (33%), 58 led to a shot (14%). 51 cut-backs: 24 found a team-mate (47%), 15 led to a shot (29%). 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?

402 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; 15 come from the half-spaces and 0 from the centre.

deep right wing: 17 crosses (4%)4%17deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 1 crosses (0%)0%1deep left wing: 24 crosses (6%)6%24advanced right wing: 77 crosses (19%)19%77advanced right half-space: 3 crosses (1%)1%3advanced centre: 0 crosses (0%)advanced left half-space: 4 crosses (1%)1%4advanced left wing: 75 crosses (19%)19%75byline right wing: 100 crosses (25%)25%100byline right half-space: 4 crosses (1%)1%4byline centre: 0 crosses (0%)byline left half-space: 3 crosses (1%)1%3byline left wing: 94 crosses (23%)23%94
TerritoryCrossesShareLed to a shot
byline · right wing10025%21
byline · left wing9423%15
advanced · right wing7719%9
advanced · left wing7519%8
deep · left wing246%2
deep · right wing174%0
advanced · left half-space41%0
byline · right half-space41%2
advanced · right half-space31%0
byline · left half-space31%1
deep · left half-space10%0
Finishing3 sections

Shot Map

316 shots for 30.5 xG (0.90/game, #18 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

Low-output attack. 9.3 shots/game at 0.096 xG/shot. Box entries 8/game (#18). Threat created 8.6 xT/game (#18).

Goal Sequences

The move behind each of Angers’s 29 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 — 29 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
22 · 79%
Set pieces
3 · 11%
Penalties
3 · 11%

By finish

Right foot
19 · 68%
Left foot
7 · 25%
Header
2 · 7%
Vision AI Model Insight
28 goals scored. 79% come in open play; set pieces add 11%. 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

205 of 853 pass attempts lost here (24%).24%205/853Arcus100 of 876 pass attempts lost here (11%).11%100/876Camara311 of 1823 pass attempts lost here (17%).17%311/1823Koffi108 of 894 pass attempts lost here (12%).12%108/894Lefort233 of 954 pass attempts lost here (24%).24%233/954Lefort251 of 1302 pass attempts lost here (19%).19%251/1302Raolisoa161 of 1242 pass attempts lost here (13%).13%161/1242Belkebla198 of 1464 pass attempts lost here (14%).14%198/1464Camara201 of 1396 pass attempts lost here (14%).14%201/1396Lefort304 of 1550 pass attempts lost here (20%).20%304/1550Lefort261 of 773 pass attempts lost here (34%).34%261/773Raolisoa94 of 325 pass attempts lost here (29%).29%94/325Raolisoa49 of 234 pass attempts lost here (21%).21%49/234Sbaï137 of 350 pass attempts lost here (39%).39%137/350Sbaï244 of 789 pass attempts lost here (31%).31%244/789Ekomiéattacking →

How they lose it

Incomplete pass — attacking third
785
Failed forward pass
518
Failed take-on
357
Lost in the defensive third
957
Their weakest zone is the left half-space in the attacking third: 39% of 350 pass attempts there are lost (137 times). Separately, 27% 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.

Pressing3 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.

11
Pressing Index
/100 · passive
Intensity0
PPDA, high-press share, high-zone actions
Height6
how high up the pitch they defend
Effectiveness14
high recoveries & high-regain share
Disruption28
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
19%
RHS
20%
C
20%
LHS
21%
LW
21%
By third (high / mid / low regain)
Def 56%
Mid 35%
Att 9%
Read
Ranked #18 of 18 for press intensity, this is a mid block. 44% of defensive actions happen in the middle & attacking thirds, at an average height of 34. Of recoveries, 49% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#18/18lower = more intense; rank is what matters
Defensive actions / game130#8/18
High-press share15%#18/18def actions won high up
Defensive-action height (0–100)33.8#17/18avg pitch height of actions
High recoveries / game20.1#15/18ball won in mid+att third
High-recovery share49%#16/18share of recoveries won high
Opponent completion allowed86%#18/18lower = more disruptive
Opponent progressive allowed8.3%#8/18of 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 1168 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 7.5 opponent passes in the first half-hour and after 4.6 after the hour mark (sooner).

PASSES THEY GET
6.2passes
median 4 · before Angers win it
TIME THEY KEEP IT
19sec
median 10s · 34.4 wins per game
How many passes the opponent got in before the ball was won
36%
26%
18%
20%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
7.2
21s
15–30′
7.9
24s
30–45+′
7.8
25s
45–60′
5.7
18s
60–75′
4.7
13s
75–90+′
4.6
14s
average passesaverage seconds

Phases of play

Every moment of the match read twice — what Angers were doing with the ball, and what the opposition were doing about it at that exact moment. Built from the real action sequence in time order, so one possession is split across the phases it genuinely passed through rather than labelled once by where it began.

5,766phase segments analysed
7.0smedian time before the opposition engage
2.0their passes per defensive action when pressed
#17of 18 for share of defending spent pressing high

With the ball

Share of possession time spent in each phase.

Build-up 32.4%Progression 45.5%Chance creation 18.6%Attacking transition 3.4%

Without the ball

How Angers defend when the opponent has it.

High press 4.5%Mid block 12.3%Low block 52.7%Unopposed 30.5%

What opponents do against Angers

The mirror image, and the part no other section can show: whether teams come out to press Angers or sit in and invite them on. A side that is always faced with a low block is playing a different sport from one that is pressed every week.

High press 10.5%Mid block 14.5%Low block 43.8%Unopposed 31.2%

Which phases actually produce

PhaseSegmentsAvg lengthAvg actionsEnds in shotTurned over
Build-up2,0375.2s3.20.1%49.1%
Progression2,4076.1s3.80.4%52.1%
Chance creation1,1685.2s3.025.5%56.6%
Attacking transition1547.2s4.51.3%40.9%

Most common routes through the phases

How a possession actually travelled, in order. The chain is the tactical signature — a move that climbs all three thirds is a different thing from one that never leaves the first.

RouteTimesEnds in shot
build_up8210.1%
progression5820.3%
build_up → progression4420.2%
progression → chance_creation28420.8%
chance_creation25737.0%
build_up → progression → chance_creation16729.9%

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) 5,400 passes

nothing unusual in this zone

Width of use+0.7022.44
Wide-channel share+0.660.35
Side bias+0.180.84
Pass length-0.6320.41
Long-ball share-0.470.18
Forward gain per pass-0.429.62
Backward-pass share-0.170.19
Deep-pass share-0.350.25
Completion+0.290.82
Seconds between passes-0.393.09
Side used

left 30% · central 41% · right 29%

Progression (middle third) 6,954 passes

nothing unusual in this zone

Width of use+0.4426.51
Wide-channel share+0.420.43
Side bias+0.441.78
Pass length-0.5616.45
Long-ball share-0.450.08
Forward gain per pass-0.053.53
Backward-pass share-0.010.33
Deep-pass share-0.210.15
Completion-0.240.83
Seconds between passes-0.183.12
Side used

left 38% · central 28% · right 33%

Final third 2,471 passes

touchline to touchline, played in the channels

Width of use+0.9233.87
Wide-channel share+0.880.66
Side bias+0.140.49
Pass length+0.1515.70
Long-ball share+0.050.10
Forward gain per pass-0.060.97
Backward-pass share-0.130.38
Deep-pass share-0.250.08
Completion-0.250.68
Seconds between passes-0.053.36
Side used

left 45% · central 12% · right 43%

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%
#14 of 18 · reaches final third in ≤3 passes
Patient build-up share26%
#13 of 18 · spells of 6+ passes
Tempo (possession length)16.4s
#5 of 18 · shorter = faster tempo
Passes per possession4.4
#13 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
#8 of 18 · lower = faster break

Sequence success — attacking transition

106attacking transition sequences this season
20%succeed — produce a shot
51%turned over with nothing to show

Sequence success — defensive transition

270defensive transition sequences this season
66%succeed — reach the next third or a shot
9%turned over with nothing to show
Vision AI Model Insight
Angers are balanced between tempo and patience: 15% of possessions reach the final third in 3 passes or fewer (#14 of 18), against 26% built patiently over 6+ passes (#13 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? 1719 opponent progressive passes and 490 shots faced (49.6 xG against) across the season.

Opponent threat by lane (attacking into Angers)

Right wing
32%
Right half-space
13%
Central
13%
Left half-space
13%
Left wing
29%
Where the danger came from. Opponents generated most of their threat through the right wing (32% 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 (354 total)

2%4%4%3%16%16%22%15%17%Lohann DoucetLohann DoucetIlan KebbalLohann DoucetMaxime LopezMoses SimonNhoa SanguiMaxime LopezTimothée KolodziejczakVincent MarchettiNhoa SanguiIlan KebbalFabián RuizBradley BarcolaBradley BarcolaOusmane DembéléAchraf HakimiOusmane DembéléNuno MendesDésiré DouéOusmane DembéléOusmane DembéléAchraf HakimiVitinhaOusmane DembéléAchraf HakimiWarren Zaïre-EmerySeko FofanaSeko FofanaValentin RongierQuentin MerlinQuentin MerlinMohamed MeïtéLudovic BlasQuentin MerlinQuentin MerlinValentin RongierBertug YildirimPablo PagisPablo PagisJean-Victor MakengoDarlin YongwaThéo Le BrisLaurent AbergelLaurent AbergelIgor SilvaArthur AvomArthur AvomArsène KouassiDarlin YongwaArsène KouassiArsène KouassiValentín BarcoSamir El MourabetValentín BarcoValentín BarcoJoaquín PanichelliFélix LemaréchalValentín BarcoDiego MoreiraRafael LuísRafael LuísMika BierethJordan TezeCaio HenriqueMamadou CoulibalyJordan TezeJordan TezeKassoum OuattaraTakumi MinaminoAmir MurilloPierre-Emerick AubameyangAngel GomesPierre-Emerick AubameyangEmersonPierre-Emerick AubameyangMatt O'RileyBenjamin StambouliGauthier HeinGauthier HeinBenjamin StambouliGauthier HeinHákon HaraldssonThomas MeunierOlivier GiroudAyyoub BouaddiHákon HaraldssonThomas MeunierAyyoub BouaddiThomas MeunierNgal'ayel MukauMalick FofanaCorentin TolissoKhalis MerahAdam KarabecNicolás TagliaficoMalick FofanaPavel SulcAdam KarabecDanny NamasoElisha OwusuFredrik OppegårdDanny NamasoFredrik OppegårdFredrik OppegårdKévin DanoisFredrik OppegårdGideon MensahKenny LalaRomain Del CastilloRomain Del CastilloRomain Del CastilloRomain Del CastilloLudovic AjorqueTom LouchetCharles VanhoutteJonathan ClaussAli AbdiJonathan ClaussAli AbdiIsak JanssonTanguy NdombéléIsak JanssonIsak JanssonMatthis AblineChidozie AwaziemMayckel LahdoMatthis AblineYoussef El-ArabiEmersonnMark McKenzieAron DønnumFrank MagriAron DønnumYann GbohoAron DønnumAron DønnumAron DønnumMark McKenzieAlexis VossahAron DønnumAron DønnumAron DønnumYann GbohoCharlie CresswellYann GbohoDjibril SidibéRuben AguilarMatthieu UdolRuben AguilarFlorian ThauvinOdsonne ÉdouardRuben AguilarFlorian ThauvinMatthieu UdolFlorian ThauvinFlorian ThauvinMamadou SangaréFlorian ThauvinSamson BaidooFlorian SotocaYanis ZouaouiRassoul NdiayeFelix MambimbiRassoul NdiayeYanis ZouaouiLoïc NégoRassoul NdiayeGodson KyeremehAmine GouiriAmine GouiriAmir MurilloHamed TraoréEmersonEmersonTimothy WeahHamed TraoréPierre-Emile HøjbjergHamed TraoréAmine GouiriFacundo MedinaAmine GouiriPierre-Emile HøjbjergPierre-Emile HøjbjergPierre-Emile HøjbjergPierre-Emile HøjbjergHamari TraoréOtávioIlan KebbalIlan KebbalLuca KoleoshoMaxime LopezAdama CamaraMaxime LopezBenjamin StambouliGiorgi AbuashviliGiorgi TsitaishviliJessy DeminguetSantiago HidalgoPape DiopEmersonnCristian CásseresCristian CásseresYann GbohoJacen Russell-RoweCristian CásseresArsène KouassiArsène KouassiPablo PagisPablo PagisThéo Le BrisPablo PagisSambou SoumanoMatias Fernandez-PardoGaëtan PerrinOlivier GiroudGaëtan PerrinMatias Fernandez-PardoGaëtan PerrinGaëtan PerrinGaëtan PerrinCalvin VerdonkMatias Fernandez-PardoNabil BentalebLamine CamaraJordan TezeAladji BambaFolarin BalogunFolarin BalogunAladji BambaJordan TezeAleksandr GolovinLamine CamaraMatthis AblineMatthis AblineAli YoussifFabien CentonzeJohann LepenantKaïl BoudacheJonathan ClaussMorgan SansonMelvin BardElye WahiJonathan ClaussSofiane DiopJonathan ClaussAdrien ThomassonSaud AbdulhamidSaud AbdulhamidFlorian ThauvinMatthieu UdolMatthieu UdolFlorian ThauvinMalang SarrFlorian ThauvinAdrien ThomassonFlorian ThauvinMamadou SangaréFlorian ThauvinOdsonne ÉdouardFlorian ThauvinFlorian ThauvinSaud AbdulhamidAbdallah SimaAllan Saint-MaximinAbdallah SimaAndrija BulatovicRayan FofanaRomain Del CastilloRomain Del CastilloKenny LalaRomain Del CastilloKenny LalaRomain Del CastilloKamory DoumbiaKenny LalaHamidou MakalouDaouda GuindoLudovic AjorqueTanner TessmannCorentin TolissoTanner TessmannTyler MortonAfonso MoreiraEndrickAbner ViníciusRoman YaremchukLudovic BlasValentin RongierValentin RongierQuentin MerlinLudovic BlasLudovic BlasMousa Al TamariLudovic BlasLilian BrassierLudovic BlasSebastian SzymanskiAboubakar NagidaIssa SoumaréMbwana SamattaFodé DoucouréYanis ZouaouiSofiane BoufalSofiane BoufalLucas Gourna-DouathMbwana SamattaSofiane BoufalYassine KechtaYanis ZouaouiTimothée PembéléYanis ZouaouiBeraldoSenny MayuluBeraldoBeraldoBeraldoBeraldoBeraldoGonçalo RamosLee Kang-InBradley BarcolaIbrahim MbayeLee Kang-InLee Kang-InWarren Zaïre-EmeryLamine SyLassine SinayokoDanny NamasoLassine SinayokoLassine SinayokoDanny NamasoKévin DanoisGideon MensahKévin DanoisLassine SinayokoLamine SyLassine SinayokoDanny NamasoSékou MaraKévin DanoisLasso CoulibalyGuéla DouéMartial GodoMathis AmougouMathis AmougouGuéla DouéJulio EncisoGuéla DouéGuéla DouéGuéla DouéMartial GodoMartial GodoMartial Godo← own goal

By situation

Open play
39 · 83%
Set pieces
5 · 11%
Penalties
3 · 6%
Vision AI Model Insight
47 goals conceded. 83% come in open play; set pieces account for only 11%, so dead-ball defending is not the main issue. 4% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre of the attacking third (22% 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
22 g · 23.4 xG
Set pieces
3 g · 3.1 xG
Penalties
3 g
11% of goals come from set pieces (3 of 28), worth 3.1 xG from 52 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Angers's corners go?

121 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 (63)

3%17%22%16%2%5%13%11%5%
Delivered into the box 94%Short 6%

Left side (58)

5%19%17%9%3%3%29%10%2%
Delivered into the box 98%Short 2%

Where opponents attack Angers from set pieces

70 shots from opponent corners against Angers, 5 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 (35)

11%6%23%34%14%11%
Shot 35Goals 4

Left flag (35)

9%9%40%20%14%9%
Shot 35Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • none stand out
Weaknesses (bottom-third vs league)
  • xG created /game — 0.90 (0th pct)
  • press intensity (PPDA) — 10.21 (0th pct)
  • field tilt % — 38.73 (0th pct)
  • box entries /game — 8.00 (0th pct)
  • threat created /game — 8.59 (0th 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.

Metz
88%
Lorient
79%
Nice
77%
Nantes
76%
Paris FC
60%

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 (11m)0.641.271.00
vs mid-block opponents (11m)0.821.820.82
vs low-block opponents (12m)1.081.171.33

Behaviour — how Angers actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents77%14%296.75.5
vs mid-block opponents80%13%348.48.3
vs low-block opponents83%11%4210.510.1
Vision AI Model Insight
Facing a high press, retention drops to 77% vs 83% against a low block (7pt lower under pressure), and directness (long-ball share) sits at 14% when pressed vs 11% against a low block — a mild adjustment, not a wholesale change.

Scouting Summary — the team in brief

In brief. Angers are territorially-dominated with a moderate-press. Their attack creates 0.90 xG a game and they concede 1.46 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 34 matches this season
Final-third entriesvs Metz · 1-0 · 2026-02-0189avg 31
Progressive carriesvs Metz · 1-0 · 2026-02-0189avg 43
Threat from passingvs Brest · 0-2 · 2025-09-2810.57avg 4.92
Passesvs Metz · 1-0 · 2026-02-01709avg 436
Field tiltvs Metz · 1-0 · 2026-02-0177%avg 39%
PPDAat PSG · 0-1 · 2025-08-2218.4avg 10.2
Expected goalsvs Nantes · 4-1 · 2025-12-122.24avg 0.90
Pass accuracyvs Strasbourg · 1-1 · 2026-05-1069%avg 80%

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 12 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).

+14.5on-ball value, 12 matches
Where the value came from
Passes4901 actions+6.45
Carries1112 actions-1.14
Dribbles170 actions-0.03
Shots106 actions+5.32
Ball wins705 actions+3.95
Most on-ball value (OBV)ActionsOBVper 100
Branco van den Boomen860+2.98+0.35
Amine Sbaï450+2.46+0.55
Hervé Koffi377+1.30+0.34
Goduine Koyalipou159+1.19+0.75
Jordan Lefort1007+1.17+0.12
Pierrick Capelle312+1.08+0.35
Lilian Raolisoa542+0.99+0.18
Ousmane Camara585+0.67+0.11
123456
Biggest single movesOBV
1  Goduine Koyalipou · shot+0.889
2  Amine Sbaï · shot+0.829
3  Branco van den Boomen · shot+0.821
4  Lilian Raolisoa · pass+0.553
5  Lilian Raolisoa · pass+0.369
6  Amine Sbaï · pass+0.327

Set Pieces by Player

Who delivers Angers’s dead balls and who finishes them this season. 121 corners taken, most by Branco van den Boomen (38); 52 shots from corners and free kicks, 3 goals, led by Ousmane Camara (1 goals, 0.46 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 Boomen3835 (92%)2—0.0520/1
Amine Sbaï2719 (70%)310.25—0/1
Lilian Raolisoa1917 (89%)2—0.061—
Louis Mouton1614 (88%)2—0.05——
Himad Abdelli55 (100%)3—0.21—2/2
Ousmane Camara——610.46——
Jordan Lefort——6—0.321—
Pierrick Capelle33 (100%)4—0.112—
Justin Kalumba119 (82%)1—0.02——
Yassin Belkhdim10 (0%)4—0.17——
Jacques Ekomié——4—0.63——
Florent Hanin10 (0%)3—0.09——
Carlens Arcus——3—0.07——
Prosper Peter——2—0.12——

Top Performers

Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 300 minutes). Coloured chips are that player's strongest capability blocks.

playerposminVision AI Scorecapability blocks
Hervé KoffiGK28108.3Shot-Stopping 83%
Branco van den BoomenCM12895.2Progression 74%Chance Creation 68%Ball-Carrying 46%Successful Dribble 14%
Ousmane CamaraCB28734.5Ball-Winning 44%Aerial & Box Defending 38%Progression 24%Ball-Carrying 18%
Jordan LefortCB32344.0Ball-Carrying 60%Progression 50%Ball-Winning 44%Aerial & Box Defending 26%
Carlens ArcusFB21343.5Ball-Carrying 60%Ball-Winning 49%Wide Delivery 5%
Amine SbaïW19102.5Ball-Carrying 61%Chance Creation 42%Box Threat 37%Wide Delivery 22%
Yassin BelkhdimCM21952.5Progression 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 SbaïM19101.233416.0
Branco van den BoomenM12891.893224.6
Lilian RaolisoaM20560.962418.5
Louis MoutonM19890.952114.0
Carlens ArcusD21340.672330.5
Jacques EkomiéD23600.461918.4
Yassin BelkhdimM21950.571010.8
Florent HaninD9460.761513.5

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)
Jacques EkomiéFB236020 (25%)17 (41%)
Carlens ArcusFB213417 (41%)20 (65%)
Amine SbaïW191016 (25%)9 (22%)
Florent HaninFB94617 (35%)8 (62%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Jordan LefortD32345025148136
Ousmane CamaraD28734994731117
Haris BelkeblaM30213887232147
Jacques EkomiéD23603516031107
Carlens ArcusD2134302373193
Lilian RaolisoaM2056287521583
Yassin BelkhdimM2195270593683
Louis MoutonM1989222401471

Full Squad Data

Every player with 100+ minutes (26 players).

playerposappsmingoalsxGkey PprogdefxT
Jordan LefortD34323400.6714950243.4
Haris BelkeblaM33302100.2155238816.4
Ousmane CamaraD32287310.834849918.8
Hervé KoffiG30281000.00667119.1
Jacques EkomiéD32236001.1129935118.4
Yassin BelkhdimM27219522.3144127010.8
Carlens ArcusD26213400.41616830230.5
Lilian RaolisoaM32205621.02210528718.5
Louis MoutonM32198922.8215422214.0
Amine SbaïM25191033.7266815216.0
Prosper PeterF29137854.810131482.7
Branco van den BoomenM15128901.2279115724.6
Sidiki CherifF19119242.6451221.9
Florent HaninD2594600.188314713.5
Goduine KoyalipouF1369522.854731.1
Pierrick CapelleM1669400.56211085.5
Lanroy MachineF2261711.647631.6
Marius LouërD958900.03201005.0
Marius CourcoulM1844900.122561.8
Emmanuel BiumlaD941400.107642.3
Harouna DjibirinM1540820.748652.1
Abdoulaye BambaD628100.004451.2
Justin KalumbaF423800.0319304.4
Melvin ZingaG323400.00881.5
Oumar PonaG219000.00831.5
Jim AllevinahM616410.613170.8

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.

Jordan Lefort
Stopper / marker · Defender
minutes3234
goals · xG0 · 0.6
prog passes /904.1
key passes /900.19
def actions /9014.0
pass accuracy86%
Haris Belkebla
Ball-winner / destroyer · Midfielder
minutes3021
goals · xG0 · 0.2
prog passes /901.5
key passes /900.45
def actions /9011.6
pass accuracy87%
Ousmane Camara
Stopper / marker · Defender
minutes2873
goals · xG1 · 0.8
prog passes /901.5
key passes /900.09
def actions /9015.6
pass accuracy90%
Hervé Koffi
Goalkeeper · Goalkeeper
minutes2810
goals · xG0 · 0.0
prog passes /902.1
key passes /900.00
def actions /902.3
pass accuracy74%
Jacques Ekomié
Stopper / marker · Defender
minutes2360
goals · xG0 · 1.1
prog passes /903.8
key passes /900.46
def actions /9013.4
pass accuracy77%
Yassin Belkhdim
Ball-winner / destroyer · Midfielder
minutes2195
goals · xG2 · 2.3
prog passes /901.7
key passes /900.57
def actions /9011.1
pass accuracy80%
Carlens Arcus
Ball-playing defender · Defender
minutes2134
goals · xG0 · 0.4
prog passes /907.1
key passes /900.67
def actions /9012.7
pass accuracy86%
Lilian Raolisoa
Ball-winner / destroyer · Midfielder
minutes2056
goals · xG2 · 1.0
prog passes /904.6
key passes /900.96
def actions /9012.6
pass accuracy68%
Louis Mouton
Ball-winner / destroyer · Midfielder
minutes1989
goals · xG2 · 2.8
prog passes /902.4
key passes /900.95
def actions /9010.0
pass accuracy74%

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: xG created /game (0th pct)
Sign a higher-volume goalscorer or chance creator. The data flags this because the attack under-produces xG (0.90, 0th percentile vs the league).
Need — bottom-third: press intensity (PPDA) (0th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (10.21, 0th percentile vs the league).
Need — bottom-third: field tilt % (0th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (38.73, 0th percentile vs the league).
Vision AI · building report