Combining every season — this one is larger, give it a moment.
Team reportLigue 1 2026
Toulouse
A balanced-territory side, aggressive high-press out of possession, with a high-volume attack. Currently #11 of 18 on 10 points (2-4-2, 12:11). 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 Toulouse and how good was the season?
Read. Toulouse currently sit #11 of 18 on 10 points (2W-4D-2L, 1.25 pts/game), scoring 12 and conceding 11 for a goal difference of +1.
On the ball they are a balanced-territory team (51% field tilt, #9 in the league); off it they defend with a aggressive high-press (#8 of 18 for press intensity).
Across the 8 matches of event data, they create 1.50 xG/game (#7) and concede 1.37 (#9), a net of +0.14 xG/game — the underlying performance matches the actual goal difference.
Season Context — the league table
The question
Where did Toulouse actually finish, and against whom?
The authoritative final table (full season), centred on Toulouse.
#
team
P
W
D
L
GF
GA
GD
Pts
8
Marseille
8
4
0
4
18
13
+5
12
9
Lorient
8
3
3
2
7
6
+1
12
10
Nice
8
3
2
3
8
10
-2
11
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
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Toulouse 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
Toulouse tend to fade after a strong start — first-half net xG +0.78, second-half +0.33. Their strongest period is 46-60' (net +1.89 xG); their most dangerous period to face is 76-90+' (net -1.74 xG against them).
xG Race — the season, match by match
Expected goals piling up over 8 matches: Toulouse 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 (+1.1 xG). Hover a point for that match.
ToulouseOpponents against Toulouse
Tactical DNA
The football question
In five genes, what is Toulouse'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.
61
Build-Up
possession control from the back
75
Progression
moving the ball upfield with threat
50
Creation
manufacturing chances
53
Press
winning the ball high & hard
50
Solidity
resisting the opponent's threat
Genetic identity
Toulouse are defined most by their Progression DNA (75/100 · strong at moving the ball upfield with threat), and least by their Creation DNA (50/100). 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
30%
Possession
20%
Field tilt
45%
Disrupt
Central progression ~proxy
35%
Dribble tendency
85%
Progressive passes
50%
Finish
Final-third patience
20%
Shot quality
45%
Open-play xG
40%
Press
Forward press ~proxy
40%
High regains
75%
Pressing efficiency ~proxy
70%
Defend
Def-mid press ~proxy
25%
High line ~proxy
60%
PAdj defensive actions
25%
Toulouse is defined most by Press (62% in the league) and weakest on Possess (32%). 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 Toulouse actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Toulouse'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; Toulouse highlighted. Hover any dot for the team.
Vision AI Model Insight
Toulouse post 51% field tilt, ranking #9 of 18 in the league — comfortably above the league mid-point for territorial control, and their 1.25 points/game sits below the league-average return — a real disconnect: their territorial control isn't showing up on the scoreboard the way it should.
Where the time goes — how long each phase lasts
The question
When Toulouse has the ball, how much of that time is spent building, progressing and creating?
The share of Toulouse'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
28.9%
Progression
46.2%
Chance creation
21.5%
Attacking transition
3.3%
Vision AI Model Insight
Progression is where Toulouse 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
McKenzie ↔ Restes
147p · -0.1xT
McKenzie ↔ Cásseres
125p · -0.3xT
Cásseres ↔ Tapé
107p · 0.4xT
Cásseres ↔ Jørgensen
96p · 1.5xT
McKenzie ↔ Messali
94p · -0.4xT
Cásseres ↔ Messali
92p · 1.3xT
McKenzie ↔ Nicolaisen
90p · -0.7xT
Nicolaisen ↔ Restes
85p · -0.6xT
McKenzie ↔ Tapé
68p · 0.4xT
Nicolaisen ↔ Tapé
61p · -0.2xT
Vision AI Model Insight
Busiest connection: Mark McKenzie ↔ Guillaume Restes (147 passes). Most dangerous per pass: Jacen Russell-Rowe ↔ Christ Tapé (0.04 xT/pass over 27 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Toulouse 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 Toulouse 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
4391
ACTIONS
Carries
the ball moved with a player
999
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (11.4% of all actions). 62% of actions run through the inside lanes (centre + both half-spaces) versus 38% down the two wings — an inside-dominant, half-space build. By third: 30% defensive, 49% middle, 20% 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. Toulouse leaned on their right (42%). The bars under the pitch put the league’s share beside theirs.
Toulouse
37%21%42%
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. Toulouse made 346 this season (43.2 a match); 32% 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
107
13.4
31%
30%
Left half-space
35
4.4
10%
13%
Centre
45
5.6
13%
11%
Right half-space
48
6.0
14%
14%
Right wing
111
13.9
32%
32%
Build-up2 sections
Build-Up — the pass map
The football question
How does Toulouse 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.
1335build-up passes attempted
87%completed
27%reach the middle third
1%go long into the final third
Pass types
460CB · 40%
50Long Wide · 4%
5Long Central · 0%
494Wide → FB · 42%
155Central · 13%
Sequence success — build-up
91build-up sequences this season
12%succeed — reach the next third or a shot
38%turned over with nothing to show
CB460 · 40%
Long Wide50 · 4%
Long Central5 · 0%
Wide → FB494 · 42%
Central155 · 13%
◆ Vision AI Insight
Toulouse build predominantly down the right, with Restes as the fulcrum (265 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 → RHS def (93×).
Pass Explorer
Every pass of Toulouse’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. 389 progressive passes across 8 matches (48.6/game).
Origin lane
Right wing
33%
Right half-space
14%
Central
12%
Left half-space
12%
Left wing
30%
Progression is right-dominant: 46% right side · 12% central · 42% left.
Who generates it
Cristian Cásseres
77 · 20%
Christ Tapé
58 · 15%
Rafik Messali
44 · 11%
Mark McKenzie
30 · 8%
Thomas Jørgensen
28 · 7%
Top two — Cristian Cásseres & Christ Tapé — account for 35% of all progression.
PROGRESSION
48.6 prog passes/game
mostly right
→
PENETRATION
26% reach final third
19% reach the box
→
THREAT
the other 74% is recycled
progress ≠ danger
What came of it.26% of progressive passes reached the final third and 19% the box; the rest was recycled in front of the block. 35% 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 wingbalanced
Right half-spacebalanced
Centralsterile
Left half-spacebalanced
Left wingefficient
Progression — the pass map
The football question
Once Toulouse 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.
2160progression passes attempted
88%completed
14%break into the final third
12%go backward into the defensive third
Pass types
532CB · 28%
73Long Wide · 4%
12Long Central · 1%
1031Wide → FB · 54%
254Central · 13%
Sequence success — progression
141progression sequences this season
25%succeed — reach the next third or a shot
39%turned over with nothing to show
CB532 · 28%
Long Wide73 · 4%
Long Central12 · 1%
Wide → FB1031 · 54%
Central254 · 13%
◆ Vision AI Insight
Toulouse progress predominantly down the right, with Cásseres the busiest midfield outlet (356 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 (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 RHS mid → RW mid (117×) — 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%
14% of passes are progressive-or-better; the remaining 86% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Toulouse actually progress the ball with their feet, not a pass?
241 progressive carries this season across the whole squad (24% of 999 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 14m, longest 52m. Most active carrier: Tapé (33). Filter to one player below.
First (85)Second (72)Third (45)Fourth (39)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 Toulouse'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.
102shots
12.0xG
0.12xG per shot
7big chances (0.3+ xG)
12goals
#7key passes / game in the league
#9box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition37% of shots
38
1
3.84
0.10
Cross
1
0
0.04
0.04
Cut-back
3
0
0.41
0.14
Long ball
3
0
0.35
0.12
Pass into the box / short pass
23
1
2.32
0.10
Own creation (carry, dribble, rebound)
8
0
0.72
0.09
Settled attack44% of shots
45
8
5.15
0.11
Cross
6
1
1.12
0.19
Cut-back
4
1
0.45
0.11
Long ball
4
2
0.71
0.18
Pass into the box / short pass
24
3
1.87
0.08
Own creation (carry, dribble, rebound)
7
1
1.00
0.14
Set piece19% of shots
19
3
3.04
0.16
Corner
13
1
1.34
0.10
Free kick
4
0
0.11
0.03
Penalty
2
2
1.59
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
Cristian Cásseres
21
2.35
4
Thomas Jørgensen
9
1.19
1
Rafik Messali
6
1.12
0
Casper Tengstedt
4
0.55
1
Aron Dønnum
5
0.36
1
Who takes them
Player
Shots
xG
Goals
Casper Tengstedt
22
4.28
5
Jacen Russell-Rowe
13
1.69
2
Thomas Jørgensen
15
1.58
2
Christ Tapé
6
1.31
1
Santiago Hidalgo
9
0.75
0
Vision AI Model Insight
The biggest source of Toulouse's chances, by xG, is settled attack (5.2 of 12.0 xG, 45 of 102 shots), mostly pass into the box / short pass. 38 of the 102 shots (37%) came within 15 seconds of winning the ball. 19 of the 102 shots came from set pieces; 12 goals from 12.0 xG (-0.0).
Chance Creation — the pass map
The football question
How does Toulouse 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
1CB · 1%
7Long Wide · 9%
9Long Central · 12%
28Wide → FB · 38%
29Central · 39%
Sequence success — final-third
92final-third sequences this season
18%succeed — produce a shot
41%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
CB1 · 1%
Long Wide7 · 9%
Long Central9 · 12%
Wide → FB28 · 38%
Central29 · 39%
Who creates — volume × threat
26Cásseres
11Jørgensen
6Tapé
5Schmidt
5Dønnum
4Gboho
4Messali
74key passes #7 of 18
13.0box entries/game #9 of 18
35.6final-3rd entries/game #6 of 18
1.50xG/game #7 of 18
12goals #8 of 18
-0.0finishing vs xG #11 of 18
◆ Vision AI Insight
Toulouse lean right — 41% of their key passes come from that flank and its half-space (30 of 74), most often from Cásseres (14). They funnel chances into the c of the final third, most often via RHS att → C att (9 key passes, most often from Cásseres). Cásseres is the primary source overall. They generate 1.50 xG a game and finish it wasteful — they under-perform their xG, led by Casper Tengstedt (5G), Jacen Russell-Rowe (2G), Thomas Jørgensen (2G).
Crosses & Cutbacks — squad-wide
The question
How does Toulouse deliver into the box from wide areas, and what comes of it?
97 crosses: 32 found a team-mate (33%), 6 led to a shot (6%). 26 cut-backs: 11 found a team-mate (42%), 6 led to a shot (23%). 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 Toulouse actually cross from?
97 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. 24% come from one territory, the advanced right wing; 6 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
advanced · right wing
23
24%
0
advanced · left wing
21
22%
1
byline · right wing
20
21%
2
byline · left wing
15
15%
0
deep · right wing
10
10%
2
advanced · right half-space
3
3%
1
deep · left wing
2
2%
0
byline · right half-space
2
2%
0
byline · left half-space
1
1%
0
Finishing3 sections
Shot Map
102 shots for 12.0 xG (1.50/game, #7 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
High-volume attack. 12.8 shots/game at 0.118 xG/shot. Box entries 13/game (#9). Threat created 11.7 xT/game (#4).
Goal Sequences
The move behind each of Toulouse’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 Toulouse scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
9 · 75%
Set pieces
1 · 8%
Penalties
2 · 17%
By finish
Right foot
6 · 50%
Left foot
3 · 25%
Header
3 · 25%
Vision AI Model Insight
12 goals scored. 75% come in open play; set pieces add 8%. 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
235
Failed forward pass
166
Failed take-on
80
Lost in the defensive third
171
Their weakest zone is the right half-space in the attacking third: 36% of 154 pass attempts there are lost (56 times). Separately, 35% 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 Toulouse 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.
44
Pressing Index /100 · average
Intensity46
PPDA, high-press share, high-zone actions
Height39
how high up the pitch they defend
Effectiveness44
high recoveries & high-regain share
Disruption44
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
16%
RHS
23%
C
25%
LHS
19%
LW
16%
By third (high / mid / low regain)
Def 49%
Mid 36%
Att 16%
Read
Ranked #8 of 18 for press intensity, this is a high press. 51% of defensive actions happen in the middle & attacking thirds, at an average height of 38. Of recoveries, 50% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#8/18
lower = more intense; rank is what matters
Defensive actions / game
163
#5/18
High-press share
23%
#9/18
def actions won high up
Defensive-action height (0–100)
38.1
#11/18
avg pitch height of actions
High recoveries / game
24.1
#6/18
ball won in mid+att third
High-recovery share
50%
#14/18
share of recoveries won high
Opponent completion allowed
83%
#10/18
lower = more disruptive
Opponent progressive allowed
8.6%
#10/18
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 Toulouse win it back with a defensive action?
Counted over the 286 opposition possessions that Toulouse 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 Toulouse step in. Toulouse win it after 5.4 opponent passes in the first half-hour and after 5.0 after the hour mark (sooner).
PASSES THEY GET
5.3passes
median 4 · before Toulouse win it
TIME THEY KEEP IT
16sec
median 10s · 35.8 wins per game
How many passes the opponent got in before the ball was won
40%
26%
18%
17%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.0
18s
15–30′
5.0
14s
30–45+′
6.6
20s
45–60′
4.5
13s
60–75′
4.9
14s
75–90+′
5.2
17s
average passesaverage seconds
Attitude in each third
Every other style number here says how much Toulouse 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 Toulouse 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) 1,335 passes
kept on the floor, shorter passing, safer
Width of use-0.5119.95
Wide-channel share-0.690.26
Side bias-0.29-0.92
Pass length-1.0219.02
Long-ball share-1.030.13
Forward gain per pass-0.877.68
Backward-pass share-0.030.20
Deep-pass share-0.920.20
Completion+0.920.87
Seconds between passes-0.133.25
Side used
left 25% · central 46% · right 29%
Progression (middle third) 2,160 passes
nothing unusual in this zone
Width of use+0.1625.92
Wide-channel share+0.020.41
Side bias-0.81-3.13
Pass length-0.3516.74
Long-ball share-0.380.09
Forward gain per pass-0.033.56
Backward-pass share+0.060.34
Deep-pass share-0.310.15
Completion+0.530.88
Seconds between passes-0.163.12
Side used
left 31% · central 29% · right 40%
Final third 896 passes
nothing unusual in this zone
Width of use-0.0431.52
Wide-channel share+0.090.59
Side bias-0.07-0.98
Pass length-0.5514.62
Long-ball share-0.540.07
Forward gain per pass-0.090.93
Backward-pass share-0.100.38
Deep-pass share+0.320.10
Completion+0.430.73
Seconds between passes-0.533.00
Side used
left 40% · central 16% · right 44%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Toulouse'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 Toulouse 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 share20%
#2 of 18 · reaches final third in ≤3 passes
Patient build-up share25%
#14 of 18 · spells of 6+ passes
Tempo (possession length)16.3s
#5 of 18 · shorter = faster tempo
Passes per possession4.2
#13 of 18
Counter-attack shots /game1.02
#9 of 18 · shot within 12s of a regain in own half
Press→shot /game3.31
#8 of 18 · shot within 8s of a high regain
Speed to final third after regain11.9s
#6 of 18 · lower = faster break
Sequence success — attacking transition
15attacking transition sequences this season
20%succeed — produce a shot
67%turned over with nothing to show
Sequence success — defensive transition
34defensive transition sequences this season
76%succeed — reach the next third or a shot
15%turned over with nothing to show
Vision AI Model Insight
Toulouse are a direct, fast-break side: 20% of possessions reach the final third in 3 passes or fewer (#2 of 18), against 25% built patiently over 6+ passes (#14 of 18). Winning the ball back leads to a shot inside 12 seconds 1.02 times a game (#9), and a high regain converts to a shot within 8 seconds 3.31 times a game (#8 of 18) — a modest but real source of chances.
Defending the box2 sections
Vulnerability Map — how opponents hurt them
The report flipped: where do opponents create their threat against Toulouse? 354 opponent progressive passes and 111 shots faced (10.9 xG against) across the season.
Opponent threat by lane (attacking into Toulouse)
Right wing
36%
Right half-space
15%
Central
12%
Left half-space
9%
Left wing
29%
Where the danger came from. Opponents generated most of their threat through the right wing (36% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Toulouse actually come from — open play, dead balls, and who supplies them?
Every goal Toulouse conceded across the loaded matches — the opponent's shots in Toulouse'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 (73 total)
By situation
Open play
10 · 91%
Set pieces
1 · 9%
Penalties
0 · 0%
Vision AI Model Insight
11 goals conceded. 91% come in open play; set pieces account for only 9%, so dead-ball defending is not the main issue. 27% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre of the attacking third (21% 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
9 g · 9.0 xG
Set pieces
1 g · 1.5 xG
Penalties
2 g
8% of goals come from set pieces (1 of 12), worth 1.5 xG from 17 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Toulouse's corners go?
33 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 (20)
Delivered into the box 85%Short 15%
Where opponents attack Toulouse from set pieces
15 shots from opponent corners against Toulouse, 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 (9)
Shot 9Goals 1
Left flag (6)
Shot 6Goals 0
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
threat created /game — 11.66 (78th pct)
progression /game — 48.62 (72th pct)
pass retention % — 84.88 (72th pct)
Weaknesses (bottom-third vs league)
none stand out
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.
PSG
77%
Monaco
70%
Rennes
45%
Marseille
39%
Lens
38%
Performance vs Opponent Styles
The question
Not just how Toulouse 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 Toulouse's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (2m)
2.50
2.00
2.00
vs mid-block opponents (2m)
1.00
2.00
0.50
vs low-block opponents (4m)
1.25
0.75
1.25
Behaviour — how Toulouse actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
82%
11%
46
10.3
10.5
vs mid-block opponents
84%
12%
38
9.8
12.5
vs low-block opponents
86%
8%
56
13.3
14.5
Vision AI Model Insight
Facing a high press, retention drops to 82% vs 86% against a low block (4pt lower under pressure), and directness (long-ball share) sits at 11% when pressed vs 8% against a low block — a mild adjustment, not a wholesale change.
Scouting Summary — the team in brief
In brief. Toulouse are balanced-territory with a aggressive high-press.
Their attack creates 1.50 xG a game and they concede 1.37 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 Toulouse’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 Lille · 0-1 · 2026-09-038.28avg 6.48
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 Toulouse’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).
+14.5on-ball value, 8 matches
Where the value came from
Passes4391 actions+3.60
Carries999 actions+1.14
Dribbles148 actions+1.11
Shots102 actions+6.10
Ball wins530 actions+2.52
Most on-ball value (OBV)
Actions
OBV
per 100
Casper Tengstedt
132
+2.70
+2.04
Cristian Cásseres
974
+2.07
+0.21
Christ Tapé
564
+1.86
+0.33
Thomas Jørgensen
457
+1.24
+0.27
Jacen Russell-Rowe
201
+1.08
+0.54
Rafik Messali
463
+0.86
+0.19
Mark McKenzie
741
+0.85
+0.11
Niklas Schmidt
296
+0.57
+0.19
Biggest single moves
OBV
1 Casper Tengstedt · shot
+0.811
2 Casper Tengstedt · shot
+0.784
3 Jacen Russell-Rowe · shot
+0.646
4 Christ Tapé · shot
+0.494
5 Cristian Cásseres · pass
+0.453
6 Christ Tapé · shot
+0.402
Set Pieces by Player
Who delivers Toulouse’s dead balls and who finishes them this season. 33 corners taken, most by Cristian Cásseres (19); 17 shots from corners and free kicks, 1 goals, led by Casper Tengstedt (1 goals, 0.22 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
Cristian Cásseres
19
12 (63%)
2
—
0.05
1
—
Thomas Jørgensen
12
7 (58%)
3
—
0.20
2
—
Rasmus Nicolaisen
—
—
4
—
0.23
—
—
Casper Tengstedt
—
—
1
1
0.22
—
2/2
Santiago Hidalgo
—
—
2
—
0.20
1
—
Niko Sigur
—
—
1
—
0.03
—
—
Julián Vignolo
—
—
1
—
0.03
—
—
Christ Tapé
—
—
1
—
0.43
—
—
Alexis Vossah
—
—
1
—
0.03
—
—
Ilyas Azizi
—
—
1
—
0.03
—
—
Aron Dønnum
1
1 (100%)
—
—
0.00
—
—
Niklas Schmidt
1
1 (100%)
—
—
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
Cristian Cásseres
M
758
3.09
29
19.2
Thomas Jørgensen
M
729
1.36
11
6.0
Rafik Messali
D
485
0.74
10
8.4
Christ Tapé
D
748
0.72
8
9.7
Ilyas Azizi
M
354
0.76
7
3.4
Niklas Schmidt
M
238
1.89
3
5.1
Casper Tengstedt
F
422
0.64
4
1.1
Jacen Russell-Rowe
F
559
0.32
5
2.1
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)
Christ Tapé
FB
748
7 (71%)
8 (25%)
Rafik Messali
FB
485
9 (67%)
3 (0%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Cristian Cásseres
M
758
192
32
8
69
Mark McKenzie
D
758
149
9
7
28
Christ Tapé
D
748
122
6
4
41
Rafik Messali
D
485
105
13
11
27
Thomas Jørgensen
M
729
98
14
7
36
Rasmus Nicolaisen
D
462
96
2
7
19
Alexis Vossah
M
318
62
9
3
15
Ilyas Azizi
M
354
58
8
0
23
Full Squad Data
Every player with 100+ minutes (21 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Mark McKenzie
D
8
758
0
0.0
1
30
149
11.3
Cristian Cásseres
M
8
758
0
0.3
26
77
192
19.2
Christ Tapé
D
8
748
1
1.3
6
58
122
9.7
Thomas Jørgensen
M
8
729
2
1.6
11
28
98
6.0
Guillaume Restes
G
7
641
0
0.0
0
7
31
4.3
Jacen Russell-Rowe
F
8
559
2
1.7
2
7
53
2.1
Rafik Messali
D
8
485
0
0.1
4
44
105
8.4
Rasmus Nicolaisen
D
5
462
0
0.2
0
14
96
4.1
Casper Tengstedt
F
6
422
5
4.3
3
9
28
1.1
Niko Sigur
M
5
359
0
0.1
1
14
53
2.7
Ilyas Azizi
M
6
354
0
0.6
3
13
58
3.4
Alexis Vossah
M
7
318
0
0.1
1
4
62
2.1
Seny Koumbassa
D
5
314
0
0.0
0
10
42
3.3
Niklas Schmidt
M
5
238
0
0.1
5
27
32
5.1
Santiago Hidalgo
F
7
237
0
0.8
1
5
41
1.2
Julián Vignolo
M
4
194
0
0.2
1
5
27
0.9
Yann Gboho
M
2
174
0
0.2
4
6
25
2.0
Ismaïl Diallo
D
5
173
0
0.0
0
18
36
2.7
Sion Oppong
M
5
147
1
0.2
0
1
17
0.2
Aron Dønnum
M
3
141
1
0.3
5
11
25
3.1
Mathys Niflore
G
2
117
0
0.0
0
1
5
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.
Mark McKenzie
Stopper / marker · Defender
minutes758
goals · xG0 · 0.0
prog passes /903.6
key passes /900.12
def actions /9017.7
pass accuracy91%
Cristian Cásseres
Advanced creator · Attacking mid
minutes758
goals · xG0 · 0.3
prog passes /909.1
key passes /903.09
def actions /9022.8
pass accuracy82%
Christ Tapé
Ball-playing defender · Defender
minutes748
goals · xG1 · 1.3
prog passes /907.0
key passes /900.72
def actions /9014.7
pass accuracy84%
Thomas Jørgensen
Ball-winner / destroyer · Midfielder
minutes729
goals · xG2 · 1.6
prog passes /903.5
key passes /901.36
def actions /9012.1
pass accuracy75%
Guillaume Restes
Goalkeeper · Goalkeeper
minutes641
goals · xG0 · 0.0
prog passes /901.0
key passes /900.00
def actions /904.4
pass accuracy88%
Jacen Russell-Rowe
Box-to-box midfielder · Midfielder
minutes559
goals · xG2 · 1.7
prog passes /901.1
key passes /900.32
def actions /908.5
pass accuracy82%
Rafik Messali
Ball-playing defender · Defender
minutes485
goals · xG0 · 0.1
prog passes /908.2
key passes /900.74
def actions /9019.5
pass accuracy82%
Rasmus Nicolaisen
Stopper / marker · Defender
minutes462
goals · xG0 · 0.2
prog passes /902.7
key passes /900.00
def actions /9018.7
pass accuracy94%
Casper Tengstedt
Poacher / finisher · Forward
minutes422
goals · xG5 · 4.3
prog passes /901.9
key passes /900.64
def actions /906.0
pass accuracy71%
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 — below-average: shots /game (39th pct)
Sign a shot-taking forward to raise shot volume. The data flags this because shot volume is low (12.75, 39th percentile vs the league).
Need — below-average: xG conceded /game (50th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.37, 50th percentile vs the league).
Need — below-average: field tilt % (50th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (51.08, 50th percentile vs the league).