Combining every season — this one is larger, give it a moment.
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.
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.
#
team
P
W
D
L
GF
GA
GD
Pts
10
Lorient
34
11
12
11
48
51
-3
45
11
Paris FC
34
11
11
12
47
50
-3
44
12
Brest
34
10
9
15
43
55
-12
39
13
Angers
34
9
9
16
29
48
-19
36
14
Le Havre
34
7
14
13
32
44
-12
35
15
Auxerre
34
8
10
16
34
44
-10
34
16
Nice
34
7
11
16
37
60
-23
32
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)
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.
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).
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.
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.
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.
Phase
Share of the time
Build-up
32.4%
Progression
45.5%
Chance creation
18.6%
Attacking transition
3.4%
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.
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
Carries
the ball moved with a player
3543
ACTIONS
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.
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.
Channel
Entries
Per match
Share
League share
Left wing
336
9.9
32%
30%
Left half-space
158
4.6
15%
15%
Centre
94
2.8
9%
11%
Right half-space
136
4.0
13%
14%
Right wing
320
9.4
31%
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%
Long Wide260 · 6%
Long Central38 · 1%
Wide → FB1819 · 41%
Central456 · 10%
◆ 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.
From channel
To channel
From third
To third
Outcome
Minutes
Channel to channel · click a cell
Third to third · click a cell
Progression4 sections
How They Progress — the mechanism
Not just how many progressive passes, but where they start, who plays them, and whether they actually penetrate. 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%
Long Wide200 · 3%
Long Central29 · 0%
Wide → FB3383 · 58%
Central794 · 14%
◆ 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.
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
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition28% of shots
87
9
8.15
0.09
Cross
6
3
0.89
0.15
Cut-back
7
1
0.91
0.13
Long ball
5
1
0.74
0.15
Pass into the box / short pass
46
2
4.01
0.09
Own creation (carry, dribble, rebound)
23
2
1.58
0.07
Settled attack54% of shots
172
13
15.24
0.09
Cross
53
6
5.53
0.10
Cut-back
9
2
1.31
0.15
Long ball
11
0
0.68
0.06
Pass into the box / short pass
65
2
5.23
0.08
Own creation (carry, dribble, rebound)
34
3
2.49
0.07
Set piece18% of shots
57
6
7.08
0.12
Corner
46
3
2.96
0.06
Free kick
6
0
0.14
0.02
Penalty
5
3
3.97
0.79
Every attempt to create — and what came of it
Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.
Who sets the shots up
Player
Set-ups
xG created
Goals
Lilian Raolisoa
22
2.83
4
Amine Sbaï
25
2.78
2
Louis Mouton
17
1.91
1
Carlens Arcus
17
1.69
3
Prosper Peter
12
1.59
1
Who takes them
Player
Shots
xG
Goals
Prosper Peter
23
4.77
5
Amine Sbaï
34
3.75
3
Goduine Koyalipou
22
2.77
2
Louis Mouton
36
2.76
2
Sidiki Cherif
28
2.65
4
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%
Long Wide14 · 6%
Long Central23 · 10%
Wide → FB76 · 34%
Central96 · 43%
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.
Territory
Crosses
Share
Led to a shot
byline · right wing
100
25%
21
byline · left wing
94
23%
15
advanced · right wing
77
19%
9
advanced · left wing
75
19%
8
deep · left wing
24
6%
2
deep · right wing
17
4%
0
advanced · left half-space
4
1%
0
byline · right half-space
4
1%
2
advanced · right half-space
3
1%
0
byline · left half-space
3
1%
1
deep · left half-space
1
0%
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
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.
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
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#18/18
lower = more intense; rank is what matters
Defensive actions / game
130
#8/18
High-press share
15%
#18/18
def actions won high up
Defensive-action height (0–100)
33.8
#17/18
avg pitch height of actions
High recoveries / game
20.1
#15/18
ball won in mid+att third
High-recovery share
49%
#16/18
share of recoveries won high
Opponent completion allowed
86%
#18/18
lower = more disruptive
Opponent progressive allowed
8.3%
#8/18
of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.
How long they keep it — passes and seconds until the ball is won
The question
Once the opponent has the ball, how many passes and how many seconds pass before 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
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
Phase
Segments
Avg length
Avg actions
Ends in shot
Turned over
Build-up
2,037
5.2s
3.2
0.1%
49.1%
Progression
2,407
6.1s
3.8
0.4%
52.1%
Chance creation
1,168
5.2s
3.0
25.5%
56.6%
Attacking transition
154
7.2s
4.5
1.3%
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.
Route
Times
Ends in shot
build_up
821
0.1%
progression
582
0.3%
build_up → progression
442
0.2%
progression → chance_creation
284
20.8%
chance_creation
257
37.0%
build_up → progression → chance_creation
167
29.9%
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
Every opponent key pass against them (354 total)
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.
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.
Open play
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)
Delivered into the box 94%Short 6%
Left side (58)
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)
Shot 35Goals 4
Left flag (35)
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 type
goals for/g
goals against/g
points/g
vs high-pressing opponents (11m)
0.64
1.27
1.00
vs mid-block opponents (11m)
0.82
1.82
0.82
vs low-block opponents (12m)
1.08
1.17
1.33
Behaviour — how Angers actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
77%
14%
29
6.7
5.5
vs mid-block opponents
80%
13%
34
8.4
8.3
vs low-block opponents
83%
11%
42
10.5
10.1
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.]
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.
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)
Actions
OBV
per 100
Branco van den Boomen
860
+2.98
+0.35
Amine Sbaï
450
+2.46
+0.55
Hervé Koffi
377
+1.30
+0.34
Goduine Koyalipou
159
+1.19
+0.75
Jordan Lefort
1007
+1.17
+0.12
Pierrick Capelle
312
+1.08
+0.35
Lilian Raolisoa
542
+0.99
+0.18
Ousmane Camara
585
+0.67
+0.11
Biggest single moves
OBV
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.
Player
Corners taken
Into the box
Set-piece shots
Goals
xG
Free-kick shots
Penalties
Branco van den Boomen
38
35 (92%)
2
—
0.05
2
0/1
Amine Sbaï
27
19 (70%)
3
1
0.25
—
0/1
Lilian Raolisoa
19
17 (89%)
2
—
0.06
1
—
Louis Mouton
16
14 (88%)
2
—
0.05
—
—
Himad Abdelli
5
5 (100%)
3
—
0.21
—
2/2
Ousmane Camara
—
—
6
1
0.46
—
—
Jordan Lefort
—
—
6
—
0.32
1
—
Pierrick Capelle
3
3 (100%)
4
—
0.11
2
—
Justin Kalumba
11
9 (82%)
1
—
0.02
—
—
Yassin Belkhdim
1
0 (0%)
4
—
0.17
—
—
Jacques Ekomié
—
—
4
—
0.63
—
—
Florent Hanin
1
0 (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.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Amine Sbaï
M
1910
1.23
34
16.0
Branco van den Boomen
M
1289
1.89
32
24.6
Lilian Raolisoa
M
2056
0.96
24
18.5
Louis Mouton
M
1989
0.95
21
14.0
Carlens Arcus
D
2134
0.67
23
30.5
Jacques Ekomié
D
2360
0.46
19
18.4
Yassin Belkhdim
M
2195
0.57
10
10.8
Florent Hanin
D
946
0.76
15
13.5
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.
player
pos
min
crosses (completed)
cutbacks (completed)
Jacques Ekomié
FB
2360
20 (25%)
17 (41%)
Carlens Arcus
FB
2134
17 (41%)
20 (65%)
Amine Sbaï
W
1910
16 (25%)
9 (22%)
Florent Hanin
FB
946
17 (35%)
8 (62%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Jordan Lefort
D
3234
502
51
48
136
Ousmane Camara
D
2873
499
47
31
117
Haris Belkebla
M
3021
388
72
32
147
Jacques Ekomié
D
2360
351
60
31
107
Carlens Arcus
D
2134
302
37
31
93
Lilian Raolisoa
M
2056
287
52
15
83
Yassin Belkhdim
M
2195
270
59
36
83
Louis Mouton
M
1989
222
40
14
71
Full Squad Data
Every player with 100+ minutes (26 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Jordan Lefort
D
34
3234
0
0.6
7
149
502
43.4
Haris Belkebla
M
33
3021
0
0.2
15
52
388
16.4
Ousmane Camara
D
32
2873
1
0.8
3
48
499
18.8
Hervé Koffi
G
30
2810
0
0.0
0
66
71
19.1
Jacques Ekomié
D
32
2360
0
1.1
12
99
351
18.4
Yassin Belkhdim
M
27
2195
2
2.3
14
41
270
10.8
Carlens Arcus
D
26
2134
0
0.4
16
168
302
30.5
Lilian Raolisoa
M
32
2056
2
1.0
22
105
287
18.5
Louis Mouton
M
32
1989
2
2.8
21
54
222
14.0
Amine Sbaï
M
25
1910
3
3.7
26
68
152
16.0
Prosper Peter
F
29
1378
5
4.8
10
13
148
2.7
Branco van den Boomen
M
15
1289
0
1.2
27
91
157
24.6
Sidiki Cherif
F
19
1192
4
2.6
4
5
122
1.9
Florent Hanin
D
25
946
0
0.1
8
83
147
13.5
Goduine Koyalipou
F
13
695
2
2.8
5
4
73
1.1
Pierrick Capelle
M
16
694
0
0.5
6
21
108
5.5
Lanroy Machine
F
22
617
1
1.6
4
7
63
1.6
Marius Louër
D
9
589
0
0.0
3
20
100
5.0
Marius Courcoul
M
18
449
0
0.1
2
2
56
1.8
Emmanuel Biumla
D
9
414
0
0.1
0
7
64
2.3
Harouna Djibirin
M
15
408
2
0.7
4
8
65
2.1
Abdoulaye Bamba
D
6
281
0
0.0
0
4
45
1.2
Justin Kalumba
F
4
238
0
0.0
3
19
30
4.4
Melvin Zinga
G
3
234
0
0.0
0
8
8
1.5
Oumar Pona
G
2
190
0
0.0
0
8
3
1.5
Jim Allevinah
M
6
164
1
0.6
1
3
17
0.8
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).