Combining every season — this one is larger, give it a moment.
Team reportLigue 1 2026
Angers
A territorially-dominated side, aggressive high-press out of possession, with a moderate attack. Currently #14 of 18 on 8 points (2-2-4, 9:15). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.
In one read, what kind of team is Angers and how good was the season?
Read. Angers currently sit #14 of 18 on 8 points (2W-2D-4L, 1.00 pts/game), scoring 9 and conceding 15 for a goal difference of -6.
On the ball they are a territorially-dominated team (43% field tilt, #15 in the league); off it they defend with a aggressive high-press (#12 of 18 for press intensity).
Across the 8 matches of event data, they create 1.31 xG/game (#11) and concede 1.67 (#14), a net of -0.36 xG/game — the underlying performance matches the actual goal difference.
Season Context — the league table
The question
Where did Angers actually finish, and against whom?
The authoritative final table (full season), centred on Angers.
#
team
P
W
D
L
GF
GA
GD
Pts
11
Toulouse
8
2
4
2
12
11
+1
10
12
Auxerre
8
3
1
4
12
18
-6
10
13
Brest
8
2
3
3
14
12
+2
9
14
Angers
8
2
2
4
9
15
-6
8
15
Le Mans
8
1
4
3
11
16
-5
7
16
Strasbourg
8
2
1
5
12
18
-6
7
17
Troyes
8
1
2
5
5
16
-11
5
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 -2.92, second-half +0.01. Their strongest period is 61-75' (net +0.89 xG); their most dangerous period to face is 46-60' (net -1.77 xG against them).
xG Race — the season, match by match
Expected goals piling up over 8 matches: Angers against what their opponents created. A line pulling away upwards is a side creating more than it gives away; the gap at the end is the season’s balance (-2.9 xG). Hover a point for that match.
AngersOpponents against Angers
Tactical DNA
The football question
In five genes, what is Angers's footballing identity?
Each gene is a 0–100 score — the team's league percentile across the metrics that define that phase of play. It distils the whole report into an identity fingerprint: the taller the gene, the more that trait defines them.
22
Build-Up
possession control from the back
22
Progression
moving the ball upfield with threat
37
Creation
manufacturing chances
25
Press
winning the ball high & hard
22
Solidity
resisting the opponent's threat
Genetic identity
Angers are defined most by their Creation DNA (37/100 · limited at manufacturing chances), and least by their Build-Up DNA (22/100). Percentiles vs the 18 teams in the league.
The Playstyle Wheel
Fifteen style metrics across five domains — Possess, Disrupt, Finish, Press, Defend — each a percentile against the rest of the league. Metrics marked ~proxy use the closest available event-data signal where the standard definition needs data this feed doesn't carry (explicit pressure events, offside/keeper-sweep incidents).
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 43% field tilt, ranking #15 of 18 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 1.00 points/game sits below the league-average return — territory is genuinely converting into results.
Where the time goes — how long each phase lasts
The question
When Angers has the ball, how much of that time is spent building, progressing and creating?
The share of Angers's time on the ball spent in each phase of play, in the order the phases happen. A phase is where the ball is on the pitch (own third, middle third, final third); a transition or a set piece skips the build-up and is counted on its own.
Phase
Share of the time
Build-up
30.5%
Progression
47.7%
Chance creation
19.2%
Attacking transition
2.5%
Vision AI Model Insight
Progression is where Angers spends most of its time on the ball (48% of its time on the ball).
Passing Network
The question
Who actually plays with whom — the real on-pitch connections, not just average positions?
Every pass linked to its likely receiver (the next same-team touch), aggregated into player-pair combinations at each player's average position. Line width = how often the pair combines; colour = threat generated per pass (blue low → red high). Hover a line for the pair, or click a player to isolate their connections.
width = passes between the paircolour = xT per pass: low → high
Top 10 combinations
Lopes ↔ Lefort
125p · 0.0xT
Lopes ↔ Camara
111p · 0.3xT
Lefort ↔ Camara
106p · -0.2xT
Boomen ↔ Lefort
98p · 0.3xT
Arcus ↔ Camara
87p · -0.3xT
Boomen ↔ Camara
79p · 0.8xT
Boomen ↔ Kalulu
77p · 0.2xT
Lefort ↔ Kalulu
77p · 0.1xT
Boomen ↔ Arcus
73p · 1.8xT
Arcus ↔ Allevinah
64p · 1.2xT
Vision AI Model Insight
Busiest connection: Anthony Lopes ↔ Jordan Lefort (125 passes). Most dangerous per pass: Branco van den Boomen ↔ Jim Allevinah (0.04 xT/pass over 45 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Angers had the ball
Every touch across 72 matches. Brighter means more touches.
Which Zones Do They Attack Through?
The question
Across the whole pitch, where does Angers actually do its on-ball work?
Passes on one map, carries (the ball travelling with a player) on the other. Each is binned into the 15 pitch zones (three thirds × five vertical lanes) and shaded by its share of that kind of action; the arrows are the real actions.
Passes
the ball moved by a pass
3841
ACTIONS
Carries
the ball moved with a player
985
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (11.6% of all actions). 57% of actions run through the inside lanes (centre + both half-spaces) versus 43% down the two wings — an inside-dominant, half-space build. By third: 33% defensive, 48% middle, 19% attacking.
Attack Sides
Which channel they attacked through this season: the share of every action made in the opponent’s half, down the left, through the middle and down the right. Angers leaned on their left (41%). The bars under the pitch put the league’s share beside theirs.
Angers
41%19%40%
League
38%22%40%
Final-Third Entries
Every completed pass or carry that took the ball from outside the final third into it, by the channel it arrived in. Angers made 323 this season (40.4 a match); 40% came into the left wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.
Channel
Entries
Per match
Share
League share
Left wing
128
16.0
40%
30%
Left half-space
37
4.6
11%
13%
Centre
19
2.4
6%
11%
Right half-space
26
3.2
8%
14%
Right wing
113
14.1
35%
32%
Build-up2 sections
Build-Up — the pass map
The football question
How does Angers progress possession from defence into attack — and who runs it?
Build-up passes grouped into 5 real categories — not the old zone grid, not raw individual lines: CB (passer is a centre-back), Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top passer.
1281build-up passes attempted
84%completed
27%reach the middle third
0%go long into the final third
Pass types
387CB · 36%
77Long Wide · 7%
18Long Central · 2%
477Wide → FB · 44%
113Central · 11%
Sequence success — build-up
82build-up sequences this season
7%succeed — reach the next third or a shot
52%turned over with nothing to show
CB387 · 36%
Long Wide77 · 7%
Long Central18 · 2%
Wide → FB477 · 44%
Central113 · 11%
◆ Vision AI Insight
Angers build predominantly down the right, with Lopes as the fulcrum (296 build-up passes). Only 28% of their build-up passes actually advance a third — the rest is lateral circulation, the hallmark of a possession-controlling side that circulates patiently in midfield before progressing. Their single most-repeated pattern is C def → LHS def (74×).
Pass Explorer
Every pass of Angers’s last 8 matches as an arrow, theirs first and the opponents’ with other team, each side attacking left to right (solid = completed, dashed grey = failed). Eight families per team — click any map to open it wide, then filter by channel or third, from one to another (or click a cell of the flow grids), by outcome, half, minute and passer. Channels: right wing, right half-space, centre, left half-space, left wing.
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. 324 progressive passes across 8 matches (40.5/game).
Origin lane
Right wing
35%
Right half-space
9%
Central
12%
Left half-space
9%
Left wing
35%
Progression is right-dominant: 44% right side · 12% central · 44% left.
Who generates it
Carlens Arcus
47 · 15%
Branco van den Boomen
47 · 15%
Amine Sbaï
46 · 14%
Joseph Kalulu
38 · 12%
Anthony Lopes
33 · 10%
Top two — Carlens Arcus & Branco van den Boomen — account for 29% of all progression.
PROGRESSION
40.5 prog passes/game
mostly right
→
PENETRATION
21% reach final third
22% reach the box
→
THREAT
the other 79% is recycled
progress ≠ danger
What came of it.21% of progressive passes reached the final third and 22% the box; the rest was recycled in front of the block. 29% of the progression ran through two players, mostly down the right side.
Which lanes actually create the threat
Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.
Per lane — volume vs threat
Right wingefficient
Right half-spacesterile
Centralsterile
Left half-spacebalanced
Left wingefficient
Progression — the pass map
The football question
Once Angers have the ball in midfield, how do they actually break into the final third — and who carries that job?
Progression passes grouped into 5 real categories: CB, Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top passer.
1809progression passes attempted
87%completed
15%break into the final third
13%go backward into the defensive third
Pass types
421CB · 27%
112Long Wide · 7%
13Long Central · 1%
857Wide → FB · 54%
173Central · 11%
Sequence success — progression
123progression sequences this season
26%succeed — reach the next third or a shot
45%turned over with nothing to show
CB421 · 27%
Long Wide112 · 7%
Long Central13 · 1%
Wide → FB857 · 54%
Central173 · 11%
◆ Vision AI Insight
Angers progress predominantly down the right, with Boomen the busiest midfield outlet (288 progression passes). Only 15% of passes that start in midfield actually break the final-third line — the rest (72%) is recycled back into midfield or (13%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is RHS mid → RW mid (89×) — press that lane and midfield progression stalls.
Decision Quality — not all completed passes are equal
A 90% pass completion can hide a sideways habit. Grading every pass by the threat it adds separates value creation from safe circulation.
Excellent (high xT gain)
13%
Progressive
1%
Neutral / sideways
49%
Safe / backward
37%
15% of passes are progressive-or-better; the remaining 85% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Angers actually progress the ball with their feet, not a pass?
256 progressive carries this season across the whole squad (26% of 985 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 15m, longest 42m. Most active carrier: Lefort (38). Filter to one player below.
First (83)Second (60)Third (57)Fourth (56)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Chance creation4 sections
Chance creation — how the shots come
The question
Where do Angers's chances actually come from?
Every shot sorted twice. First by the kind of attack: an attacking transition (the shot came within 15 seconds of winning the ball), a settled attack (open play after the team had the ball), or a set piece. Then by how it was set up: a cross, a cut-back, a long ball, a pass into the box, or no pass at all (the player created it himself). So a cut-back from an attacking transition is counted apart from a cut-back in a settled attack.
103shots
10.4xG
0.10xG per shot
5big chances (0.3+ xG)
9goals
#11key passes / game in the league
#13box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition23% of shots
24
0
2.10
0.09
Cross
5
0
0.84
0.17
Long ball
1
0
0.05
0.05
Pass into the box / short pass
11
0
0.80
0.07
Own creation (carry, dribble, rebound)
7
0
0.41
0.06
Settled attack53% of shots
55
5
5.53
0.10
Cross
17
2
2.63
0.15
Cut-back
8
0
0.65
0.08
Long ball
3
0
0.16
0.05
Pass into the box / short pass
14
1
1.10
0.08
Own creation (carry, dribble, rebound)
13
2
0.99
0.08
Set piece23% of shots
24
4
2.82
0.12
Corner
23
3
2.03
0.09
Penalty
1
1
0.79
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
Amine Sbaï
23
2.56
1
Jim Allevinah
9
1.29
0
Joseph Kalulu
7
0.64
1
Amine El Ouazzani
5
0.51
1
Carlens Arcus
5
0.39
0
Who takes them
Player
Shots
xG
Goals
Prosper Peter
12
2.24
2
Amine El Ouazzani
13
1.86
2
Amine Sbaï
19
1.32
1
Jim Allevinah
16
1.11
0
Usman Simbakoli
9
1.01
0
Vision AI Model Insight
The biggest source of Angers's chances, by xG, is settled attack (5.5 of 10.4 xG, 55 of 103 shots), mostly cross. 24 of the 103 shots (23%) came within 15 seconds of winning the ball. 24 of the 103 shots came from set pieces; 9 goals from 10.4 xG (-1.4).
Chance Creation — the pass map
The football question
How does Angers consistently create dangerous chances — from which zones, and who creates them?
Key passes (the pass immediately before a shot) grouped into 5 real categories: CB, Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top creator.
Pass types
5CB · 7%
7Long Wide · 10%
13Long Central · 18%
20Wide → FB · 27%
28Central · 38%
Sequence success — final-third
117final-third sequences this season
26%succeed — produce a shot
38%turned over with nothing to show
Danger Funnel — which service carries threat
Every key pass pooled by where it was played FROM, then drawn with its arrow width set by total xT rather than by count. A zone that produces a lot of cheap balls shrinks; one that produces a few decisive ones dominates. Where this disagrees with the volume map, the volume map is the misleading one.
0 key passes shown● low threat● mid● high threatarrow width = total xT, not count
CB5 · 7%
Long Wide7 · 10%
Long Central13 · 18%
Wide → FB20 · 27%
Central28 · 38%
Who creates — volume × threat
22Sbaï
13Boomen
8Allevinah
7Kalulu
5Arcus
3Ouazzani
3Lefort
73key passes #11 of 18
11.5box entries/game #13 of 18
30.5final-3rd entries/game #10 of 18
1.31xG/game #11 of 18
9goals #14 of 18
-1.4finishing vs xG #15 of 18
◆ Vision AI Insight
Angers lean right — 44% of their key passes come from that flank and its half-space (32 of 73), most often from Boomen (11). They funnel chances into the c of the final third, most often via RW att → C att (19 key passes, most often from Boomen). Sbaï is the primary source overall. They generate 1.31 xG a game and finish it wasteful — they under-perform their xG, led by Amine El Ouazzani (2G), Prosper Peter (2G), Harouna Djibirin (1G).
Crosses & Cutbacks — squad-wide
The question
How does Angers deliver into the box from wide areas, and what comes of it?
153 crosses: 46 found a team-mate (30%), 21 led to a shot (14%). 12 cut-backs: 6 found a team-mate (50%), 5 led to a shot (42%). A cross starts wide and is aimed into the box; a cut-back starts near the byline and is squared back. Grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball.
Crosses by Territory
The question
Which part of the final third does Angers actually cross from?
153 crosses this season (the same crosses as the map above), split into fifteen territories — five channels (both wings, both half-spaces and the centre) by three depths from the halfway line to the byline. 25% come from one territory, the byline right wing; 8 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · right wing
38
25%
6
advanced · left wing
34
22%
5
advanced · right wing
32
21%
2
byline · left wing
32
21%
7
deep · left wing
5
3%
0
deep · right wing
4
3%
0
byline · right half-space
4
3%
1
advanced · left half-space
2
1%
0
advanced · right half-space
1
1%
0
byline · left half-space
1
1%
0
Finishing3 sections
Shot Map
103 shots for 10.4 xG (1.31/game, #11 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Moderate attack. 12.9 shots/game at 0.101 xG/shot. Box entries 12/game (#13). Threat created 10.2 xT/game (#13).
Goal Sequences
The move behind each of Angers’s 9 goals this season, from the moment they got the ball to the finish. Pick a goal from the list, then step through it or press Play: numbered circles are passes and touches, dotted lines are carries (the ball travelling with a player), dashed grey is a pass that was lost, the star is the shot.
Each goal’s possession, rebuilt from the raw event feed — 9 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Angers scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
5 · 56%
Set pieces
3 · 33%
Penalties
1 · 11%
By finish
Right foot
2 · 22%
Left foot
3 · 33%
Header
4 · 44%
Vision AI Model Insight
9 goals scored. 56% come in open play, but 33% from set pieces — a genuine dead-ball weapon that bypasses the open-play build-up.
When they lose it1 section
Ball-Loss Map — where attacks die
Every turnover has a location and a cause. This is a rate, not a raw count — the share of pass attempts from each zone that end in a turnover, so a zone they simply play through more often doesn't automatically look riskier. Grey cells are real zones with too few attempts to trust a rate.
Loss rate by zone
How they lose it
Incomplete pass — attacking third
265
Failed forward pass
174
Failed take-on
61
Lost in the defensive third
209
Their weakest zone is the left half-space in the attacking third: 44% of 80 pass attempts there are lost (35 times). Separately, 37% of all losses happen in the attacking third — a fair share happen deeper, which invites transitions.
Out of possession
Out of possession
How they press, where they win the ball back, and how they concede.
How hard does Angers press, where, and does it actually work — beyond a single PPDA number?
A composite Pressing Index built from four event-derived dimensions, each ranked against the league. Not one metric — intensity, height, effectiveness and opponent disruption together. The pitch shows every defensive action (the only five events this data records); the white line is the average height that feeds the score. Toggle by action type below, hover any dot for the player.
13
Pressing Index /100 · passive
Intensity13
PPDA, high-press share, high-zone actions
Height11
how high up the pitch they defend
Effectiveness11
high recoveries & high-regain share
Disruption17
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
21%
RHS
19%
C
22%
LHS
17%
LW
21%
By third (high / mid / low regain)
Def 53%
Mid 35%
Att 13%
Read
Ranked #12 of 18 for press intensity, this is a high press. Note the tension: 53% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (18% high-press share) means that when they do defend, it is often deep. Of recoveries, 48% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#12/18
lower = more intense; rank is what matters
Defensive actions / game
145
#15/18
High-press share
18%
#17/18
def actions won high up
Defensive-action height (0–100)
36.2
#16/18
avg pitch height of actions
High recoveries / game
18.4
#17/18
ball won in mid+att third
High-recovery share
48%
#15/18
share of recoveries won high
Opponent completion allowed
84%
#13/18
lower = more disruptive
Opponent progressive allowed
9.9%
#17/18
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 227 opposition possessions that Angers ended with a tackle, interception, recovery or challenge. Fewer passes and seconds means the ball is won quickly (a press); more means the opponent is allowed to play before Angers step in. Angers win it after 6.6 opponent passes in the first half-hour and after 5.9 after the hour mark (sooner).
PASSES THEY GET
6.2passes
median 3 · before Angers win it
TIME THEY KEEP IT
19sec
median 11s · 28.4 wins per game
How many passes the opponent got in before the ball was won
36%
26%
19%
19%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.8
21s
15–30′
6.4
19s
30–45+′
6.2
21s
45–60′
5.7
16s
60–75′
8.1
23s
75–90+′
4.7
16s
average passesaverage seconds
Attitude in each third
Every other style number here says how much Angers does. This says
how: wide or central, short or long, patient or direct. Bars are standard deviations
from the league mean for passes played from that third; a solid bar marks a dimension
where Angers are genuinely unusual, and a verdict is only written where something clears
0.85 sd — a side that is ordinary in a third is told so rather than given a label
for average play.
Build-up (own third) 1,281 passes
nothing unusual in this zone
Width of use+0.2621.54
Wide-channel share+0.310.32
Side bias-0.67-2.35
Pass length-0.6020.55
Long-ball share-0.390.19
Forward gain per pass-0.598.91
Backward-pass share+0.110.20
Deep-pass share-0.280.26
Completion+0.470.83
Seconds between passes-0.333.12
Side used
left 26% · central 42% · right 31%
Progression (middle third) 1,809 passes
longer passing, slower
Width of use+0.4326.48
Wide-channel share+0.270.42
Side bias-0.38-1.46
Pass length+1.0018.62
Long-ball share+0.460.12
Forward gain per pass+0.093.75
Backward-pass share+0.410.35
Deep-pass share+0.370.18
Completion+0.380.87
Seconds between passes+0.973.62
Side used
left 34% · central 27% · right 38%
Final third 751 passes
played in the channels, touchline to touchline, longer passing
Width of use+1.7335.87
Wide-channel share+1.750.73
Side bias+0.090.16
Pass length+1.2017.32
Long-ball share+0.730.13
Forward gain per pass-0.110.90
Backward-pass share+0.150.40
Deep-pass share+0.020.09
Completion-0.630.64
Seconds between passes+0.303.62
Side used
left 45% · central 11% · right 44%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Angers's own league. The means
behave as football should: width of use grows 21.0 → 25.6 → 31.6 going forward,
pass length shrinks 22.7 → 17.2 → 15.5 m, and completion is hardest in the
final third. Tempo is integer-resolution because the feed records whole seconds.
Transitions1 section
Transitions — attacking & defensive
The question
When Angers win or lose the ball, what actually happens in the seconds after?
Reconstructed from the full timestamped event stream: real possession spells (not zone-clustered), and shots that follow a regain within a fixed window. This phase of play needs ordered, per-event timestamps — which every match here carries.
Direct play share15%
#15 of 18 · reaches final third in ≤3 passes
Patient build-up share26%
#12 of 18 · spells of 6+ passes
Tempo (possession length)16.4s
#6 of 18 · shorter = faster tempo
Passes per possession4.4
#12 of 18
Counter-attack shots /game1.31
#4 of 18 · shot within 12s of a regain in own half
Press→shot /game2.64
#15 of 18 · shot within 8s of a high regain
Speed to final third after regain12.8s
#9 of 18 · lower = faster break
Sequence success — attacking transition
6attacking transition sequences this season
17%succeed — produce a shot
17%turned over with nothing to show
Sequence success — defensive transition
16defensive transition sequences this season
75%succeed — reach the next third or a shot
12%turned over with nothing to show
Vision AI Model Insight
Angers are a patient build-up side: 15% of possessions reach the final third in 3 passes or fewer (#15 of 18), against 26% built patiently over 6+ passes (#12 of 18). Winning the ball back leads to a shot inside 12 seconds 1.31 times a game (#4), and a high regain converts to a shot within 8 seconds 2.64 times a game (#15 of 18) — not yet a major source of chances.
Defending the box2 sections
Vulnerability Map — how opponents hurt them
The report flipped: where do opponents create their threat against Angers? 401 opponent progressive passes and 132 shots faced (13.4 xG against) across the season.
Opponent threat by lane (attacking into Angers)
Right wing
30%
Right half-space
14%
Central
15%
Left half-space
13%
Left wing
28%
Where the danger came from. Opponents generated most of their threat through the right wing (30% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Angers actually come from — open play, dead balls, and who supplies them?
Every goal Angers conceded across the loaded matches — the opponent's shots in Angers's own matches — plus every individual opponent key pass faced, each drawn as its own real arrow (not zone-clustered) with the % share of each zone behind it.
Where the goals go in
Every opponent key pass against them (101 total)
By situation
Open play
11 · 79%
Set pieces
2 · 14%
Penalties
1 · 7%
Vision AI Model Insight
14 goals conceded. 79% come in open play; set pieces account for only 14%, so dead-ball defending is not the main issue. 29% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the left half-space of the attacking third (26% of key passes faced) — that is the zone to shut off.
Context
Shape and tactics
Set pieces, strengths and weaknesses, and who they resemble.
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
5 g · 7.6 xG
Set pieces
3 g · 2.0 xG
Penalties
1 g
33% of goals come from set pieces (3 of 9), worth 2.0 xG from 23 shots. A genuine set-piece weapon — defend the box seriously.
Where do Angers's corners go?
51 corners taken this season, split by which flag they were taken from — arrows from the flag, dots at the delivery point, shaded by % of that side's corners landing in each zone (same treatment as the concede map below). No swing-direction (inswinger/outswinger) data is recorded here, only a start and end point per pass, which cannot show how the ball curved — so this shows what is genuinely knowable: where it lands, and short vs actually delivered. Tap or hover a dot for who took it and the match; filter to one match below and the shading recomputes for just that game.
Right side (27)
Delivered into the box 100%Short 0%
Left side (24)
Delivered into the box 96%Short 4%
Where opponents attack Angers from set pieces
20 shots from opponent corners against Angers, 2 conceded, split by the flag the corner came from — arrows from the flag, dots where the shot was taken (gold = goal), shaded by the % of that flag's shots in each zone. Tap or hover a shot for who took it, the minute and the match; filter to one match and the shading recomputes for just that game.
Right flag (13)
Shot 13Goals 1
Left flag (7)
Shot 7Goals 1
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
none stand out
Weaknesses (bottom-third vs league)
field tilt % — 43.45 (17th pct)
progression /game — 40.50 (17th pct)
xG conceded /game — 1.67 (22th pct)
box entries /game — 11.50 (22th pct)
threat created /game — 10.18 (28th pct)
Style Archetype & Similar Teams
Team archetype: Direct / counter high-press. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.
Le Mans
78%
Strasbourg
70%
Auxerre
67%
Lille
48%
Troyes
29%
Performance vs Opponent Styles
The question
Not just how Angers results against a high press or a low block — how does their own play actually change?
Every match split into three tiers by how hard that specific opponent pressed (opponent PPDA — lower means a more aggressive press), matching Angers's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (2m)
1.50
1.50
1.50
vs mid-block opponents (2m)
1.50
3.50
0.00
vs low-block opponents (4m)
0.75
1.25
1.25
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
78%
18%
52
11.1
18.0
vs mid-block opponents
80%
13%
35
9.4
10.0
vs low-block opponents
83%
14%
38
10.1
9.0
Vision AI Model Insight
Facing a high press, retention drops to 78% vs 83% against a low block (5pt lower under pressure), and directness (long-ball share) sits at 18% when pressed vs 14% against a low block — a real style switch: they go noticeably more direct when pressed rather than trying to play through it.
Scouting Summary — the team in brief
In brief. Angers are territorially-dominated with a aggressive high-press.
Their attack creates 1.31 xG a game and they concede 1.67 a game.
[Event-data based — no tracking, so off-ball structure and marking scheme need video.]
For each of ten match numbers, the one match this season that departed furthest from Angers’s own average, the eight biggest swings first. Bar right of centre means more than usual, left means less. It shows how much the way they play moves from game to game, and which opponent moved it.
Angers
across 8 matches this season
Progressive passesvs Lille · 0-2 · 2026-08-2360avg 40
Every pass, carry, take-on, shot and ball win is worth the change it made to the chance of scoring minus the chance of conceding in the next 10 seconds. This is Angers’s last 8 matches added up: where the value came from, who produced it, and the six biggest single moves. OBV only measures what a player does with the ball: it shows who added the most on-ball value, not who was the most important player (defending off the ball, positioning and pressing are not in it).
+12.1on-ball value, 8 matches
Where the value came from
Passes3841 actions+4.34
Carries985 actions+0.18
Dribbles103 actions+0.17
Shots103 actions+5.36
Ball wins450 actions+2.11
Most on-ball value (OBV)
Actions
OBV
per 100
Amine Sbaï
406
+2.51
+0.62
Amine El Ouazzani
165
+1.45
+0.88
Prosper Peter
79
+1.14
+1.45
Ousmane Camara
504
+1.01
+0.20
Jim Allevinah
319
+0.93
+0.29
Anthony Lopes
438
+0.82
+0.19
Branco van den Boomen
712
+0.81
+0.11
Carlens Arcus
438
+0.68
+0.15
Biggest single moves
OBV
1 Amine El Ouazzani · shot
+0.806
2 Joseph Kalulu · pass
+0.385
3 Ousmane Camara · pass
+0.379
4 Prosper Peter · shot
+0.357
5 Anthony Bermont · shot
+0.298
6 Amine Sbaï · take-on
+0.279
Set Pieces by Player
Who delivers Angers’s dead balls and who finishes them this season. 51 corners taken, most by Branco van den Boomen (50); 23 shots from corners and free kicks, 3 goals, led by Amine El Ouazzani (1 goals, 0.35 xG). “Into the box” counts corners that landed inside the penalty area; free-kick takers are the players who shot from one, because this feed does not mark who delivers the others.
Player
Corners taken
Into the box
Set-piece shots
Goals
xG
Free-kick shots
Penalties
Branco van den Boomen
50
47 (94%)
—
—
0.00
—
—
Amine El Ouazzani
—
—
4
1
0.35
—
1/1
Amine Sbaï
1
1 (100%)
3
—
0.10
—
—
Usman Simbakoli
—
—
3
—
0.45
—
—
Carlens Arcus
—
—
3
1
0.21
—
—
Ousmane Camara
—
—
2
—
0.25
—
—
Harouna Djibirin
—
—
2
1
0.11
—
—
Anthony Bermont
—
—
1
—
0.06
—
—
Prosper Peter
—
—
1
—
0.17
—
—
Joseph Kalulu
—
—
1
—
0.03
—
—
Marius Louër
—
—
1
—
0.11
—
—
Jordan Lefort
—
—
1
—
0.16
—
—
Emmanuel Biumla
—
—
1
—
0.05
—
—
Top Performers
Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 216 minutes). Coloured chips are that player's strongest capability blocks.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Amine Sbaï
M
695
2.85
21
8.7
Branco van den Boomen
M
765
1.53
18
14.8
Jim Allevinah
M
592
1.22
10
4.7
Joseph Kalulu
D
600
1.05
7
6.7
Carlens Arcus
D
518
0.87
8
7.7
Jordan Lefort
D
670
0.40
5
9.1
Amine El Ouazzani
F
531
0.51
5
1.4
Lilian Raolisoa
D
375
0.00
7
4.9
Wide Delivery Leaders
Crosses and cutbacks — wingers and full-backs only (by real average position, not the raw D/M position code), ranked by combined volume.
player
pos
min
crosses (completed)
cutbacks (completed)
Amine Sbaï
W
695
16 (25%)
5 (40%)
Lilian Raolisoa
FB
375
16 (25%)
4 (25%)
Joseph Kalulu
FB
600
6 (33%)
7 (29%)
Jim Allevinah
W
592
6 (50%)
3 (67%)
Carlens Arcus
FB
518
3 (67%)
4 (75%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Jordan Lefort
D
670
109
5
7
26
Branco van den Boomen
M
765
97
14
2
28
Joseph Kalulu
D
600
93
12
10
29
Yassin Belkhdim
M
672
93
16
12
21
Ousmane Camara
D
606
90
8
6
15
Jim Allevinah
M
592
89
4
5
35
Amine El Ouazzani
F
531
83
5
1
13
Carlens Arcus
D
518
77
9
8
22
Full Squad Data
Every player with 100+ minutes (19 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Anthony Lopes
G
8
765
0
0.0
0
33
28
7.3
Branco van den Boomen
M
8
765
1
0.1
13
47
97
14.8
Amine Sbaï
M
8
695
1
1.3
22
46
64
8.7
Yassin Belkhdim
M
8
672
0
0.1
3
12
93
3.1
Jordan Lefort
D
7
670
0
0.2
3
28
109
9.1
Ousmane Camara
D
7
606
0
0.2
2
9
90
5.6
Joseph Kalulu
D
7
600
0
0.0
7
38
93
6.7
Jim Allevinah
M
8
592
0
1.1
8
18
89
4.7
Amine El Ouazzani
F
8
531
2
1.9
3
1
83
1.4
Carlens Arcus
D
7
518
1
0.2
5
47
77
7.7
Lilian Raolisoa
D
7
375
1
0.4
0
24
63
4.9
Prosper Peter
F
8
366
2
2.2
2
0
40
0.3
Anthony Bermont
M
5
189
0
0.8
1
2
28
0.9
Harouna Djibirin
M
7
162
1
0.4
2
2
33
0.8
Haris Belkebla
M
3
153
0
0.0
0
2
31
0.9
Bané Diatta
M
5
149
0
0.1
0
3
22
0.7
Emmanuel Biumla
D
2
135
0
0.0
0
5
25
1.2
Maël Gernigon
D
2
131
0
0.0
0
0
20
0.4
Usman Simbakoli
F
6
111
0
1.0
1
1
34
0.5
Player Role Architecture
The question
Who does what — and what tactical job does each key player actually perform?
The nine most-used players (450+ minutes), each with the role their event fingerprint points to — not just their listed position.
Anthony Lopes
Goalkeeper · Goalkeeper
minutes765
goals · xG0 · 0.0
prog passes /903.9
key passes /900.00
def actions /903.3
pass accuracy87%
Branco van den Boomen
Advanced creator · Attacking mid
minutes765
goals · xG1 · 0.1
prog passes /905.5
key passes /901.53
def actions /9011.4
pass accuracy79%
Amine Sbaï
Advanced creator · Attacking mid
minutes695
goals · xG1 · 1.3
prog passes /906.0
key passes /902.85
def actions /908.3
pass accuracy68%
Yassin Belkhdim
Ball-winner / destroyer · Midfielder
minutes672
goals · xG0 · 0.1
prog passes /901.6
key passes /900.40
def actions /9012.5
pass accuracy85%
Jordan Lefort
Stopper / marker · Defender
minutes670
goals · xG0 · 0.2
prog passes /903.8
key passes /900.40
def actions /9014.6
pass accuracy85%
Ousmane Camara
Stopper / marker · Defender
minutes606
goals · xG0 · 0.2
prog passes /901.3
key passes /900.30
def actions /9013.4
pass accuracy93%
Joseph Kalulu
Ball-playing defender · Defender
minutes600
goals · xG0 · 0.0
prog passes /905.7
key passes /901.05
def actions /9013.9
pass accuracy79%
Jim Allevinah
Ball-winner / destroyer · Midfielder
minutes592
goals · xG0 · 1.1
prog passes /902.7
key passes /901.22
def actions /9013.5
pass accuracy77%
Amine El Ouazzani
Ball-winner / destroyer · Midfielder
minutes531
goals · xG2 · 1.9
prog passes /900.2
key passes /900.51
def actions /9014.1
pass accuracy72%
Recruitment Intelligence — profiles to sign
The question
If you were sporting director, which player profiles would move the needle most?
Each recruitment target is derived directly from the team's weakest areas vs the league — the gap, why it shows in the data, and the profile that closes it.
Need — bottom-third: field tilt % (17th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (43.45, 17th percentile vs the league).
Need — bottom-third: progression /game (17th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (40.50, 17th percentile vs the league).
Need — bottom-third: xG conceded /game (22th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.67, 22th percentile vs the league).