Combining every season — this one is larger, give it a moment.
Team reportLigue 1 2026
Strasbourg
A territorially-dominated side, aggressive high-press out of possession, with a moderate attack. Currently #16 of 18 on 7 points (2-1-5, 12:18). 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 Strasbourg and how good was the season?
Read. Strasbourg currently sit #16 of 18 on 7 points (2W-1D-5L, 0.88 pts/game), scoring 12 and conceding 18 for a goal difference of -6.
On the ball they are a territorially-dominated team (42% field tilt, #16 in the league); off it they defend with a aggressive high-press (#17 of 18 for press intensity).
Across the 8 matches of event data, they create 1.22 xG/game (#13) and concede 1.69 (#15), a net of -0.47 xG/game — the underlying performance matches the actual goal difference.
Season Context — the league table
The question
Where did Strasbourg actually finish, and against whom?
The authoritative final table (full season), centred on Strasbourg.
#
team
P
W
D
L
GF
GA
GD
Pts
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
18
Le Havre
8
0
2
6
8
15
-7
2
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Strasbourg 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
Strasbourg tend to fade after a strong start — first-half net xG -1.51, second-half -2.23. Their strongest period is 31-45' (net +0.36 xG); their most dangerous period to face is 76-90+' (net -1.87 xG against them).
xG Race — the season, match by match
Expected goals piling up over 8 matches: Strasbourg 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 (-3.7 xG). Hover a point for that match.
StrasbourgOpponents against Strasbourg
Tactical DNA
The football question
In five genes, what is Strasbourg'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.
33
Build-Up
possession control from the back
3
Progression
moving the ball upfield with threat
24
Creation
manufacturing chances
8
Press
winning the ball high & hard
17
Solidity
resisting the opponent's threat
Genetic identity
Strasbourg are defined most by their Build-Up DNA (33/100 · limited at possession control from the back), and least by their Progression DNA (3/100). 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
95%
Possession
65%
Field tilt
55%
Disrupt
Central progression ~proxy
55%
Dribble tendency
80%
Progressive passes
15%
Finish
Final-third patience
50%
Shot quality
85%
Open-play xG
60%
Press
Forward press ~proxy
30%
High regains
50%
Pressing efficiency ~proxy
25%
Defend
Def-mid press ~proxy
45%
High line ~proxy
50%
PAdj defensive actions
30%
Strasbourg is defined most by Possess (72% in the league) and weakest on Press (35%). 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 Strasbourg actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Strasbourg'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; Strasbourg highlighted. Hover any dot for the team.
Vision AI Model Insight
Strasbourg post 42% field tilt, ranking #16 of 18 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 0.88 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 Strasbourg has the ball, how much of that time is spent building, progressing and creating?
The share of Strasbourg'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
34.6%
Progression
44.0%
Chance creation
19.6%
Attacking transition
1.8%
Vision AI Model Insight
Progression is where Strasbourg spends most of its time on the ball (44% 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
Jörgensen ↔ Mitchell
149p · -0.7xT
Mitchell ↔ Antwi
137p · -0.6xT
Diop ↔ Mitchell
90p · -0.1xT
Yassine ↔ Antwi
67p · 0.9xT
Jörgensen ↔ Coulibaly
66p · -0.4xT
Diop ↔ Antwi
57p · -0.4xT
Oso ↔ Coulibaly
52p · -0.5xT
Diop ↔ Oso
51p · 0.0xT
Jörgensen ↔ Diop
43p · -0.2xT
Reyna ↔ Diop
42p · 0.6xT
Vision AI Model Insight
Busiest connection: Filip Jörgensen ↔ Jeyland Mitchell (149 passes). Most dangerous per pass: Diogo Sousa ↔ Gessime Yassine (0.04 xT/pass over 32 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Strasbourg 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 Strasbourg 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
3862
ACTIONS
Carries
the ball moved with a player
1081
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (13.7% of all actions). 65% of actions run through the inside lanes (centre + both half-spaces) versus 35% down the two wings — an inside-dominant, half-space build. By third: 36% defensive, 46% middle, 18% 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. Strasbourg leaned on their right (40%). The bars under the pitch put the league’s share beside theirs.
Strasbourg
36%24%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. Strasbourg made 288 this season (36.0 a match); 29% came into the right wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.
Channel
Entries
Per match
Share
League share
Left wing
76
9.5
26%
30%
Left half-space
49
6.1
17%
13%
Centre
47
5.9
16%
11%
Right half-space
33
4.1
11%
14%
Right wing
83
10.4
29%
32%
Build-up2 sections
Build-Up — the pass map
The football question
How does Strasbourg 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.
1408build-up passes attempted
83%completed
25%reach the middle third
1%go long into the final third
Pass types
430CB · 37%
64Long Wide · 5%
13Long Central · 1%
538Wide → FB · 46%
128Central · 11%
Sequence success — build-up
112build-up sequences this season
8%succeed — reach the next third or a shot
43%turned over with nothing to show
CB430 · 37%
Long Wide64 · 5%
Long Central13 · 1%
Wide → FB538 · 46%
Central128 · 11%
◆ Vision AI Insight
Strasbourg build predominantly down the right, with Jörgensen as the fulcrum (302 build-up passes). Only 26% of their build-up passes actually advance a third — the rest is lateral circulation, the hallmark of a possession-controlling side that circulates patiently in midfield before progressing. Their single most-repeated pattern is C def → RHS def (94×).
Pass Explorer
Every pass of Strasbourg’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. 285 progressive passes across 8 matches (35.6/game).
Origin lane
Right wing
24%
Right half-space
14%
Central
21%
Left half-space
16%
Left wing
25%
Progression is left-dominant: 38% right side · 21% central · 41% left.
Who generates it
Filip Jörgensen
43 · 15%
Oso
32 · 11%
Jeyland Mitchell
32 · 11%
Sebastian Nanasi
29 · 10%
Gessime Yassine
28 · 10%
Top two — Filip Jörgensen & Oso — account for 26% of all progression.
PROGRESSION
35.6 prog passes/game
mostly left
→
PENETRATION
31% reach final third
20% reach the box
→
THREAT
the other 69% is recycled
progress ≠ danger
What came of it.31% of progressive passes reached the final third and 20% 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
Centralbalanced
Left half-spacebalanced
Left wingbalanced
Progression — the pass map
The football question
Once Strasbourg 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.
1752progression passes attempted
89%completed
14%break into the final third
14%go backward into the defensive third
Pass types
467CB · 30%
49Long Wide · 3%
4Long Central · 0%
814Wide → FB · 52%
217Central · 14%
Sequence success — progression
157progression sequences this season
20%succeed — reach the next third or a shot
39%turned over with nothing to show
CB467 · 30%
Long Wide49 · 3%
Long Central4 · 0%
Wide → FB814 · 52%
Central217 · 14%
◆ Vision AI Insight
Strasbourg progress predominantly down the left, with Diop the busiest midfield outlet (247 progression passes). Only 14% of passes that start in midfield actually break the final-third line — the rest (73%) is recycled back into midfield or (14%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is C mid → RHS mid (79×) — 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
49%
Safe / backward
39%
12% of passes are progressive-or-better; the remaining 88% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Strasbourg actually progress the ball with their feet, not a pass?
211 progressive carries this season across the whole squad (20% of 1081 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 64m. Most active carrier: Oso (31). Filter to one player below.
First (59)Second (55)Third (54)Fourth (43)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 Strasbourg'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.
98shots
9.8xG
0.10xG per shot
5big chances (0.3+ xG)
10goals
#14key passes / game in the league
#15box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition27% of shots
26
5
2.40
0.09
Cross
2
1
0.12
0.06
Cut-back
2
1
0.44
0.22
Long ball
1
0
0.09
0.09
Pass into the box / short pass
16
2
1.41
0.09
Own creation (carry, dribble, rebound)
5
1
0.34
0.07
Settled attack61% of shots
60
5
5.59
0.09
Cross
4
0
0.19
0.05
Cut-back
11
2
1.52
0.14
Long ball
3
0
0.14
0.05
Pass into the box / short pass
29
3
2.78
0.10
Own creation (carry, dribble, rebound)
13
0
0.96
0.07
Set piece12% of shots
12
0
1.79
0.15
Corner
9
0
1.72
0.19
Free kick
3
0
0.08
0.03
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
Gessime Yassine
9
1.37
2
Oso
8
1.07
1
Sebastian Nanasi
7
0.74
2
Diogo Sousa
6
0.72
1
Giovanni Reyna
8
0.47
0
Who takes them
Player
Shots
xG
Goals
Diogo Sousa
9
1.28
1
Gessime Yassine
11
1.15
2
Jacobo Ortega
7
1.10
1
Jeyland Mitchell
4
1.10
0
Dário Essugo
7
0.94
1
Vision AI Model Insight
The biggest source of Strasbourg's chances, by xG, is settled attack (5.6 of 9.8 xG, 60 of 98 shots), mostly pass into the box / short pass. 26 of the 98 shots (27%) came within 15 seconds of winning the ball. 12 of the 98 shots came from set pieces; 10 goals from 9.8 xG (+0.2).
Chance Creation — the pass map
The football question
How does Strasbourg 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%
3Long Wide · 4%
2Long Central · 3%
22Wide → FB · 31%
38Central · 54%
Sequence success — final-third
105final-third sequences this season
26%succeed — produce a shot
36%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 Wide3 · 4%
Long Central2 · 3%
Wide → FB22 · 31%
Central38 · 54%
Who creates — volume × threat
10Reyna
9Yassine
7Diop
7Oso
7Nanasi
6Sousa
5Harder
70key passes #14 of 18
11.0box entries/game #15 of 18
27.8final-3rd entries/game #16 of 18
1.22xG/game #13 of 18
10goals #8 of 18
+0.2finishing vs xG #5 of 18
◆ Vision AI Insight
Strasbourg lean right — 39% of their key passes come from that flank and its half-space (27 of 70), most often from Yassine (9). They funnel chances into the c of the final third, most often via RHS att → C att (14 key passes, most often from Yassine). Reyna is the primary source overall. They generate 1.22 xG a game and finish it clinical — they beat their xG, led by Sam Amo-Ameyaw (2G), Giovanni Reyna (2G), Gessime Yassine (2G).
Crosses & Cutbacks — squad-wide
The question
How does Strasbourg deliver into the box from wide areas, and what comes of it?
91 crosses: 32 found a team-mate (35%), 10 led to a shot (11%). 24 cut-backs: 14 found a team-mate (58%), 10 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 Strasbourg actually cross from?
91 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. 31% come from one territory, the byline right wing; 7 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · right wing
28
31%
2
advanced · right wing
20
22%
4
byline · left wing
19
21%
0
advanced · left wing
9
10%
1
deep · right wing
4
4%
1
deep · left wing
4
4%
0
advanced · right half-space
2
2%
1
byline · right half-space
2
2%
0
byline · left half-space
2
2%
1
advanced · left half-space
1
1%
0
Finishing3 sections
Shot Map
98 shots for 9.8 xG (1.22/game, #13 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Moderate attack. 12.2 shots/game at 0.100 xG/shot. Box entries 11/game (#15). Threat created 9.4 xT/game (#17).
Goal Sequences
The move behind each of Strasbourg’s 12 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 — 12 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Strasbourg scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
10 · 100%
Set pieces
0 · 0%
Penalties
0 · 0%
By finish
Right foot
4 · 40%
Left foot
6 · 60%
Header
0 · 0%
Vision AI Model Insight
10 goals scored. 100% come in open play; set pieces add 0%. 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
174
Failed forward pass
115
Failed take-on
99
Lost in the defensive third
235
Their weakest zone is the right wing in the attacking third: 30% of 172 pass attempts there are lost (51 times). Separately, 29% 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 Strasbourg 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.
17
Pressing Index /100 · passive
Intensity11
PPDA, high-press share, high-zone actions
Height17
how high up the pitch they defend
Effectiveness11
high recoveries & high-regain share
Disruption33
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
23%
RHS
21%
C
18%
LHS
21%
LW
16%
By third (high / mid / low regain)
Def 51%
Mid 35%
Att 13%
Read
Ranked #17 of 18 for press intensity, this is a high press. Note the tension: 51% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (21% high-press share) means that when they do defend, it is often deep. Of recoveries, 47% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#17/18
lower = more intense; rank is what matters
Defensive actions / game
142
#17/18
High-press share
21%
#15/18
def actions won high up
Defensive-action height (0–100)
36.7
#15/18
avg pitch height of actions
High recoveries / game
20.4
#15/18
ball won in mid+att third
High-recovery share
47%
#17/18
share of recoveries won high
Opponent completion allowed
87%
#17/18
lower = more disruptive
Opponent progressive allowed
8.3%
#7/18
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 Strasbourg win it back with a defensive action?
Counted over the 275 opposition possessions that Strasbourg 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 Strasbourg step in. Strasbourg win it after 7.0 opponent passes in the first half-hour and after 6.6 after the hour mark (sooner).
PASSES THEY GET
6.6passes
median 4 · before Strasbourg win it
TIME THEY KEEP IT
19sec
median 11s · 34.4 wins per game
How many passes the opponent got in before the ball was won
37%
20%
20%
24%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.1
18s
15–30′
7.9
25s
30–45+′
6.5
18s
45–60′
6.0
17s
60–75′
6.5
20s
75–90+′
6.6
18s
average passesaverage seconds
Attitude in each third
Every other style number here says how much Strasbourg 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 Strasbourg 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) 1,408 passes
nothing unusual in this zone
Width of use+0.0721.14
Wide-channel share+0.150.31
Side bias-0.05-0.02
Pass length-0.7619.95
Long-ball share-0.540.18
Forward gain per pass-0.519.24
Backward-pass share+0.370.22
Deep-pass share-0.580.23
Completion+0.360.82
Seconds between passes+0.293.50
Side used
left 28% · central 44% · right 28%
Progression (middle third) 1,752 passes
more recycling, circulating
Width of use-0.7124.07
Wide-channel share-0.750.35
Side bias+0.160.70
Pass length-0.6616.31
Long-ball share-0.580.08
Forward gain per pass-0.872.29
Backward-pass share+1.080.38
Deep-pass share-0.750.12
Completion+0.550.88
Seconds between passes+0.693.50
Side used
left 34% · central 33% · right 33%
Final third 702 passes
narrow, central
Width of use-1.0529.01
Wide-channel share-0.710.53
Side bias-0.04-0.73
Pass length-0.4214.82
Long-ball share-0.130.09
Forward gain per pass+0.051.11
Backward-pass share+0.050.39
Deep-pass share+0.120.09
Completion+0.730.76
Seconds between passes+0.143.50
Side used
left 39% · central 20% · right 41%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Strasbourg'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 Strasbourg 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 share36%
#2 of 18 · spells of 6+ passes
Tempo (possession length)21.1s
#15 of 18 · shorter = faster tempo
Passes per possession5.6
#3 of 18
Counter-attack shots /game0.95
#11 of 18 · shot within 12s of a regain in own half
Press→shot /game2.79
#12 of 18 · shot within 8s of a high regain
Speed to final third after regain15.3s
#18 of 18 · lower = faster break
Sequence success — attacking transition
8attacking transition sequences this season
0%succeed — produce a shot
88%turned over with nothing to show
Sequence success — defensive transition
31defensive transition sequences this season
58%succeed — reach the next third or a shot
13%turned over with nothing to show
Vision AI Model Insight
Strasbourg are a patient build-up side: 15% of possessions reach the final third in 3 passes or fewer (#14 of 18), against 36% built patiently over 6+ passes (#2 of 18). Winning the ball back leads to a shot inside 12 seconds 0.95 times a game (#11), and a high regain converts to a shot within 8 seconds 2.79 times a game (#12 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 Strasbourg? 378 opponent progressive passes and 131 shots faced (13.5 xG against) across the season.
Opponent threat by lane (attacking into Strasbourg)
Right wing
38%
Right half-space
11%
Central
10%
Left half-space
11%
Left wing
29%
Where the danger came from. Opponents generated most of their threat through the right wing (38% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Strasbourg actually come from — open play, dead balls, and who supplies them?
Every goal Strasbourg conceded across the loaded matches — the opponent's shots in Strasbourg'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 (95 total)
By situation
Open play
14 · 82%
Set pieces
1 · 6%
Penalties
2 · 12%
Vision AI Model Insight
17 goals conceded. 82% come in open play; set pieces account for only 6%, so dead-ball defending is not the main issue. 0% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right half-space of the attacking third (20% 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
10 g · 8.0 xG
Set pieces
0 g · 1.8 xG
Penalties
0 g
0% of goals come from set pieces (0 of 10), worth 1.8 xG from 12 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Strasbourg's corners go?
19 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 (13)
Delivered into the box 92%Short 8%
Left side (6)
Delivered into the box 100%Short 0%
Where opponents attack Strasbourg from set pieces
29 shots from opponent corners against Strasbourg, 1 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 (17)
Shot 17Goals 0
Left flag (12)
Shot 12Goals 1
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
none stand out
Weaknesses (bottom-third vs league)
progression /game — 35.62 (0th pct)
press intensity (PPDA) — 7.39 (6th pct)
threat created /game — 9.39 (6th pct)
field tilt % — 42.08 (11th pct)
xG conceded /game — 1.69 (17th 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.
Lille
81%
Angers
70%
Lorient
58%
Lyon
54%
Paris FC
36%
Performance vs Opponent Styles
The question
Not just how Strasbourg 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 Strasbourg's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (2m)
0.50
3.50
0.00
vs mid-block opponents (2m)
0.50
2.50
0.00
vs low-block opponents (4m)
2.50
1.50
1.75
Behaviour — how Strasbourg actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
81%
16%
26
6.5
7.5
vs mid-block opponents
83%
11%
36
9.4
6.5
vs low-block opponents
86%
10%
40
10.8
15.0
Vision AI Model Insight
Facing a high press, retention drops to 81% vs 86% against a low block (5pt lower under pressure), and directness (long-ball share) sits at 16% when pressed vs 10% 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. Strasbourg are territorially-dominated with a aggressive high-press.
Their attack creates 1.22 xG a game and they concede 1.69 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 Strasbourg’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.
Threat from passingvs Lens · 2-1 · 2026-08-297.31avg 4.61
PPDAat Marseille · 0-4 · 2026-08-2111.7avg 7.4
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 Strasbourg’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).
+12.8on-ball value, 8 matches
Where the value came from
Passes3862 actions+4.66
Carries1081 actions+0.53
Dribbles168 actions+0.31
Shots98 actions+4.48
Ball wins519 actions+2.78
Most on-ball value (OBV)
Actions
OBV
per 100
Gessime Yassine
415
+2.07
+0.50
Sebastian Nanasi
213
+1.53
+0.72
Oso
483
+1.20
+0.25
Diogo Sousa
303
+1.02
+0.34
Jeyland Mitchell
630
+0.88
+0.14
Filip Jörgensen
516
+0.81
+0.16
Dário Essugo
174
+0.78
+0.45
Pape Diop
583
+0.76
+0.13
Biggest single moves
OBV
1 Jeyland Mitchell · shot
+0.375
2 Sebastian Nanasi · pass
+0.362
3 Diogo Sousa · shot
+0.262
4 Jacobo Ortega · shot
+0.261
5 Sam Amo-Ameyaw · shot
+0.225
6 Gessime Yassine · pass
+0.222
Set Pieces by Player
Who delivers Strasbourg’s dead balls and who finishes them this season. 19 corners taken, most by Giovanni Reyna (5); 12 shots from corners and free kicks, 0 goals. “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
Pape Diop
—
—
3
—
0.09
2
—
Jeyland Mitchell
—
—
3
—
1.07
—
—
Giovanni Reyna
5
5 (100%)
1
—
0.05
—
—
Oso
4
3 (75%)
1
—
0.02
1
—
Yaya Diémé
1
0 (0%)
1
—
0.06
—
—
Samir El Mourabet
3
3 (100%)
—
—
0.00
—
—
Diogo Sousa
3
1 (33%)
—
—
0.00
—
—
Dário Essugo
—
—
1
—
0.41
—
—
Guéla Doué
—
—
1
—
0.06
—
—
Karim Coulibaly
—
—
1
—
0.04
—
—
Sebastian Nanasi
2
1 (50%)
—
—
0.00
—
—
Gessime Yassine
1
0 (0%)
—
—
0.00
—
—
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
Gessime Yassine
F
685
1.18
17
5.7
Sebastian Nanasi
F
376
1.68
14
5.9
Oso
D
570
1.11
11
7.7
Diogo Sousa
M
533
1.01
12
5.1
Giovanni Reyna
M
521
1.73
7
3.7
Jacobo Ortega
F
377
0.95
4
0.6
Pape Diop
M
609
1.03
1
6.9
Sam Amo-Ameyaw
F
276
0.65
5
1.8
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)
Gessime Yassine
W
685
9 (44%)
5 (60%)
Oso
FB
570
9 (22%)
3 (33%)
Genesis Antwi
FB
745
2 (0%)
6 (50%)
Sebastian Nanasi
W
376
2 (100%)
4 (75%)
Sam Amo-Ameyaw
W
276
3 (33%)
1 (100%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Gessime Yassine
F
685
125
19
6
42
Jeyland Mitchell
D
649
120
17
13
26
Pape Diop
M
609
119
22
7
48
Genesis Antwi
D
745
104
16
8
36
Oso
D
570
91
10
8
32
Giovanni Reyna
M
521
68
6
3
26
Diogo Sousa
M
533
66
5
5
22
Dário Essugo
M
326
54
5
6
13
Full Squad Data
Every player with 100+ minutes (19 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Filip Jörgensen
G
8
764
0
0.0
0
43
26
9.5
Genesis Antwi
D
8
745
0
0.0
2
17
104
4.6
Gessime Yassine
F
8
685
2
1.2
9
28
125
5.7
Jeyland Mitchell
D
7
649
0
1.1
2
32
120
8.9
Pape Diop
M
8
609
0
0.3
7
21
119
6.9
Oso
D
6
570
0
0.4
7
32
91
7.7
Diogo Sousa
M
7
533
1
1.3
6
20
66
5.1
Giovanni Reyna
M
8
521
2
0.7
10
16
68
3.7
Jacobo Ortega
F
8
377
1
1.1
4
1
39
0.6
Sebastian Nanasi
F
5
376
0
0.6
7
29
31
5.9
Karim Coulibaly
D
6
329
0
0.1
1
8
43
2.4
Dário Essugo
M
6
326
1
0.9
4
4
54
2.2
Conrad Harder
F
6
304
1
0.9
5
3
31
0.5
Sam Amo-Ameyaw
F
7
276
2
0.5
2
6
31
1.8
Ismaël Doukouré
D
3
260
0
0.0
0
4
44
1.8
Samir El Mourabet
M
6
246
0
0.2
1
5
38
1.7
Lucas Høgsberg
D
4
215
0
0.0
2
9
27
2.8
Andrew Omobamidele
D
2
194
0
0.1
0
1
24
1.5
Fabio Baldé
M
4
107
0
0.1
1
1
8
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.
Filip Jörgensen
Goalkeeper · Goalkeeper
minutes764
goals · xG0 · 0.0
prog passes /905.1
key passes /900.00
def actions /903.1
pass accuracy80%
Genesis Antwi
Stopper / marker · Defender
minutes745
goals · xG0 · 0.0
prog passes /902.1
key passes /900.24
def actions /9012.6
pass accuracy87%
Gessime Yassine
Ball-winner / destroyer · Midfielder
minutes685
goals · xG2 · 1.2
prog passes /903.7
key passes /901.18
def actions /9016.4
pass accuracy76%
Jeyland Mitchell
Stopper / marker · Defender
minutes649
goals · xG0 · 1.1
prog passes /904.4
key passes /900.28
def actions /9016.6
pass accuracy86%
Pape Diop
Ball-winner / destroyer · Midfielder
minutes609
goals · xG0 · 0.3
prog passes /903.1
key passes /901.03
def actions /9017.6
pass accuracy91%
Oso
Ball-playing defender · Defender
minutes570
goals · xG0 · 0.4
prog passes /905.1
key passes /901.11
def actions /9014.4
pass accuracy82%
Diogo Sousa
Ball-winner / destroyer · Midfielder
minutes533
goals · xG1 · 1.3
prog passes /903.4
key passes /901.01
def actions /9011.1
pass accuracy77%
Giovanni Reyna
Ball-winner / destroyer · Midfielder
minutes521
goals · xG2 · 0.7
prog passes /902.8
key passes /901.73
def actions /9011.7
pass accuracy87%
Jacobo Ortega
Ball-winner / destroyer · Midfielder
minutes377
goals · xG1 · 1.1
prog passes /900.2
key passes /900.95
def actions /909.3
pass accuracy66%
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: progression /game (0th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (35.62, 0th percentile vs the league).
Need — bottom-third: press intensity (PPDA) (6th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (7.39, 6th percentile vs the league).
Need — bottom-third: threat created /game (6th pct)
Sign a threat-generating creator between the lines. The data flags this because little threat is manufactured (9.39, 6th percentile vs the league).