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Team reportLigue 1 2026

PSG

A possession-dominant side, aggressive high-press out of possession, with a high-volume attack. Currently #1 of 18 on 17 points (5-2-1, 16:9). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

possession-dominantaggressive high-presshigh-volume attack
L
W
W
D
W
W
L
D
D
L
W
W
W
W
W
17
points
#1 of 18 · 8 games
16:9
goals
+7 GD
5-2-1
record
W-D-L
2.12
points/game
#1 in the league
2.19
xG for/game
rank #1
1.05
xG against/game
rank #2
#1
press rank
of 18 · most aggressive
74%
field tilt
#1
PSG
League average
Expected goals for / game
2.191.41
Expected goals against / game
1.051.41
Field tilt
74%50%
Pass retention
89%83%
Overview

The team

Who they are and how the season went.

Who Are They? — Identity

The question
In one read, what kind of team is PSG and how good was the season?
Read. PSG currently sit #1 of 18 on 17 points (5W-2D-1L, 2.12 pts/game), scoring 16 and conceding 9 for a goal difference of +7. On the ball they are a possession-dominant team (74% field tilt, #1 in the league); off it they defend with a aggressive high-press (#1 of 18 for press intensity). Across the 8 matches of event data, they create 2.19 xG/game (#1) and concede 1.05 (#2), a net of +1.14 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

The question
Where did PSG actually finish, and against whom?

The authoritative final table (full season), centred on PSG.

#teamPWDLGFGAGDPts
1PSG8521169+717
2Rennes85121814+416
3Lille8431116+515
4Monaco8431117+415

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does PSG actually dominate for chances — and which periods hurt them?

Net xG (created minus conceded) in each 15-minute window, summed across the whole season's matches — above the line is time they dominate for chances, below is time it hurts them. Real on-clock shot timing.

dominant (net xG for)conceding (net xG against)
even0-15'16-30'31-45'46-60'61-75'76-90+'+3.03
Vision AI Model Insight
PSG tend to come alive after the break — first-half net xG +3.74, second-half +5.41. Their strongest period is 76-90+' (net +3.03 xG); their most dangerous period to face is 31-45' (net +0.79 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: PSG 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 (+9.2 xG). Hover a point for that match.

06131917.58.4Rennes (A) 2-2 · xG 1.53 to 0.66Lille (A) 2-2 · xG 1.33 to 0.85Monaco (H) 1-2 · xG 2.28 to 0.42Brest (A) 1-0 · xG 1.04 to 1.06Marseille (A) 2-1 · xG 4.36 to 1.55Le Mans (H) 3-1 · xG 3.55 to 1.11Strasbourg (A) 3-1 · xG 2.27 to 2.08Lyon (H) 2-0 · xG 1.18 to 0.66M1M2M3M4M5M6M7M8
PSGOpponents against PSG

Tactical DNA

The football question
In five genes, what is PSG'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.

94
Build-Up
possession control from the back
94
Progression
moving the ball upfield with threat
94
Creation
manufacturing chances
94
Press
winning the ball high & hard
89
Solidity
resisting the opponent's threat
Genetic identity
PSG are defined most by their Build-Up DNA (94/100 · elite at possession control from the back), and least by their Solidity DNA (89/100). 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).

Possess93Disrupt65Finish83Press95Defend93
Possess
Deep buildup
90%
Possession
95%
Field tilt
95%
Disrupt
Central progression ~proxy
95%
Dribble tendency
5%
Progressive passes
95%
Finish
Final-third patience
95%
Shot quality
60%
Open-play xG
95%
Press
Forward press ~proxy
95%
High regains
95%
Pressing efficiency ~proxy
95%
Defend
Def-mid press ~proxy
95%
High line ~proxy
90%
PAdj defensive actions
95%
PSG is defined most by Press (95% in the league) and weakest on Disrupt (65%). Percentiles vs the 20 teams in the league this season.
In possession

In possession

How they keep the ball, build up, progress, create and finish, and where their attacks die.

Keeping the ball6 sections

Field Tilt — Territorial Control

The question
How much of the pitch does PSG actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across PSG'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; PSG highlighted. Hover any dot for the team.

PSG: 74% tilt, 2.12 pts/gRennes: 50% tilt, 2.00 pts/gLille: 44% tilt, 1.88 pts/gMonaco: 52% tilt, 1.88 pts/gLyon: 49% tilt, 1.75 pts/gParis FC: 46% tilt, 1.75 pts/gLens: 55% tilt, 1.62 pts/gLorient: 40% tilt, 1.50 pts/gMarseille: 58% tilt, 1.50 pts/gNice: 53% tilt, 1.38 pts/gToulouse: 51% tilt, 1.25 pts/gAuxerre: 52% tilt, 1.25 pts/gBrest: 44% tilt, 1.12 pts/gAngers: 43% tilt, 1.00 pts/gStrasbourg: 42% tilt, 0.88 pts/gLe Mans: 41% tilt, 0.88 pts/gTroyes: 54% tilt, 0.62 pts/gLe Havre: 51% tilt, 0.25 pts/gPSG40%52%63%74%0.20.91.52.1FIELD TILT %POINTS / GAME
Vision AI Model Insight
PSG post 74% field tilt, ranking #1 of 18 in the league — a genuinely territory-dominant side, and their 2.12 points/game sits above the league-average return — territory is genuinely converting into results.

Where the time goes — how long each phase lasts

The question
When PSG has the ball, how much of that time is spent building, progressing and creating?

The share of PSG's time on the ball spent in each phase of play, in the order the phases happen. A phase is where the ball is on the pitch (own third, middle third, final third); a transition or a set piece skips the build-up and is counted on its own.

Build-up: 21.1% of the time on the ball21%Progression: 49.3% of the time on the ball49%Chance creation: 28.3% of the time on the ball28%Attacking transition: 1.3% of the time on the ball49%PROGRESSION
PhaseShare of the time
Build-up21.1%
Progression49.3%
Chance creation28.3%
Attacking transition1.3%
Vision AI Model Insight
Progression is where PSG spends most of its time on the ball (49% 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.

Marquinhos ↔ Willian Pacho: 138 passes, -0.1 combined xTAchraf Hakimi ↔ Vitinha: 122 passes, 1.2 combined xTVitinha ↔ Willian Pacho: 101 passes, -0.4 combined xTAchraf Hakimi ↔ Maghnes Akliouche: 100 passes, 1.7 combined xTVitinha ↔ Warren Zaïre-Emery: 100 passes, -0.3 combined xTMarquinhos ↔ Achraf Hakimi: 89 passes, 0.1 combined xTFabián Ruiz ↔ Vitinha: 85 passes, 0.3 combined xTDésiré Doué ↔ Warren Zaïre-Emery: 80 passes, 0.9 combined xTVitinha ↔ João Neves: 75 passes, 0.3 combined xTWillian Pacho ↔ Warren Zaïre-Emery: 74 passes, -0.6 combined xTMarquinhos ↔ Vitinha: 70 passes, 0.3 combined xTFabián Ruiz ↔ Warren Zaïre-Emery: 68 passes, 0.3 combined xTVitinha ↔ Maghnes Akliouche: 66 passes, 0.8 combined xTVitinha ↔ Désiré Doué: 60 passes, 1.2 combined xTFabián Ruiz ↔ Khvicha Kvaratskhelia: 59 passes, 1.4 combined xTAchraf Hakimi ↔ João Neves: 52 passes, 0.5 combined xTMarquinhos ↔ João Neves: 49 passes, -0.3 combined xTFabián Ruiz ↔ Désiré Doué: 49 passes, 1.2 combined xTMarquinhos ↔ Warren Zaïre-Emery: 47 passes, -0.3 combined xTFabián Ruiz ↔ Willian Pacho: 46 passes, 0.4 combined xTOusmane Dembélé ↔ Achraf Hakimi: 41 passes, 1.1 combined xTWarren Zaïre-Emery ↔ João Neves: 41 passes, 0.2 combined xTMatvey Safonov ↔ Willian Pacho: 40 passes, -0.1 combined xTKhvicha Kvaratskhelia ↔ Vitinha: 40 passes, 0.3 combined xTMatvey Safonov — isolate this player's connectionsSafonovFerran Torres — isolate this player's connectionsTorresVitinha — isolate this player's connectionsVitinhaMaghnes Akliouche — isolate this player's connectionsAklioucheWarren Zaïre-Emery — isolate this player's connectionsZaïre-EmerDésiré Doué — isolate this player's connectionsDouéMika Godts — isolate this player's connectionsGodtsJoão Neves — isolate this player's connectionsNevesKhvicha Kvaratskhelia — isolate this player's connectionsKvaratskheAchraf Hakimi — isolate this player's connectionsHakimiFabián Ruiz — isolate this player's connectionsRuizWillian Pacho — isolate this player's connectionsPachoBeraldo — isolate this player's connectionsBeraldoDro Fernández — isolate this player's connectionsFernándezOusmane Dembélé — isolate this player's connectionsDembéléMarquinhos — isolate this player's connectionsMarquinhos
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Marquinhos ↔ Pacho
138p · -0.1xT
Hakimi ↔ Vitinha
122p · 1.2xT
Vitinha ↔ Pacho
101p · -0.4xT
Hakimi ↔ Akliouche
100p · 1.7xT
Vitinha ↔ Zaïre-Emery
100p · -0.3xT
Marquinhos ↔ Hakimi
89p · 0.1xT
Ruiz ↔ Vitinha
85p · 0.3xT
Doué ↔ Zaïre-Emery
80p · 0.9xT
Vitinha ↔ Neves
75p · 0.3xT
Pacho ↔ Zaïre-Emery
74p · -0.6xT
Vision AI Model Insight
Busiest connection: Marquinhos ↔ Willian Pacho (138 passes). Most dangerous per pass: Ousmane Dembélé ↔ Achraf Hakimi (0.03 xT/pass over 41 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where PSG 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 PSG 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
6050
ACTIONS
4%4%7%4%3%9%11%11%10%9%8%5%3%4%6%PASSES
Carries
the ball moved with a player
1598
ACTIONS
3%6%8%4%3%11%11%12%10%10%8%4%3%3%8%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the middle third (11.4% of all actions). 60% of actions run through the inside lanes (centre + both half-spaces) versus 40% down the two wings — an inside-dominant, half-space build. By third: 22% defensive, 51% middle, 27% 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. PSG leaned on their right (40%). The bars under the pitch put the league’s share beside theirs.

38%Left side21%Middle40%Right sideATTACKING →
PSG
38%21%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. PSG made 583 this season (72.9 a match); 37% 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.

Left wing: 181 entries (31%)18131%LEFT WINGLeft half-space: 67 entries (11%)6711%LEFT HALF-SPACECentre: 60 entries (10%)6010%CENTRERight half-space: 58 entries (10%)5810%RIGHT HALF-SPACERight wing: 217 entries (37%)21737%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing18122.631%30%
Left half-space678.411%13%
Centre607.510%11%
Right half-space587.210%14%
Right wing21727.137%32%
Build-up2 sections

Build-Up — the pass map

The football question
How does PSG 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.

1321build-up passes attempted
89%completed
27%reach the middle third
0%go long into the final third

Pass types

602CB · 51%
55Long Wide · 5%
8Long Central · 1%
394Wide → FB · 34%
111Central · 9%

Sequence success — build-up

38build-up sequences this season
11%succeed — reach the next third or a shot
47%turned over with nothing to show
CB602 · 51%
right: 315 passes, most from Marquinhos315left: 287 passes, most from Pacho287
Long Wide55 · 5%
right: 34 passes, most from Safonov34left: 21 passes, most from Safonov21
Long Central8 · 1%
left: 4 passes, most from Mendes4right: 4 passes, most from Mendes4
Wide → FB394 · 34%
right: 204 passes, most from Safonov204left: 190 passes, most from Safonov190
Central111 · 9%
left: 69 passes, most from Safonov69right: 42 passes, most from Vitinha42
◆ Vision AI Insight
PSG build predominantly down the right, with Pacho as the fulcrum (184 build-up passes). Only 27% 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 (77×).

Pass Explorer

Every pass of PSG’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.

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. 446 progressive passes across 8 matches (55.8/game).

Origin lane

Right wing
33%
Right half-space
14%
Central
6%
Left half-space
13%
Left wing
34%
Progression is left-dominant: 47% right side · 6% central · 48% left.

Who generates it

Achraf Hakimi
54 · 12%
Désiré Doué
52 · 12%
Vitinha
42 · 9%
Fabián Ruiz
31 · 7%
Maghnes Akliouche
30 · 7%
Top two — Achraf Hakimi & Désiré Doué — account for 24% of all progression.
PROGRESSION
55.8 prog passes/game
mostly left
→
PENETRATION
23% reach final third
23% reach the box
→
THREAT
the other 77% is recycled
progress ≠ danger
What came of it. 23% of progressive passes reached the final third and 23% the box; the rest was recycled in front of the block. 24% of the progression ran through two players, mostly down the left side.

Which lanes actually create the threat

Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.

Per lane — volume vs threat
Right wingbalanced
Right half-spacebalanced
Centralsterile
Left half-spacebalanced
Left wingefficient

Progression — the pass map

The football question
Once PSG 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.

3093progression passes attempted
93%completed
16%break into the final third
9%go backward into the defensive third

Pass types

987CB · 34%
127Long Wide · 4%
19Long Central · 1%
1398Wide → FB · 49%
351Central · 12%

Sequence success — progression

104progression sequences this season
43%succeed — reach the next third or a shot
28%turned over with nothing to show
CB987 · 34%
left: 516 passes, most from Hernández516right: 471 passes, most from Marquinhos471
Long Wide127 · 4%
right: 71 passes, most from Vitinha71left: 56 passes, most from Vitinha56
Long Central19 · 1%
right: 12 passes, most from Ruiz12left: 7 passes, most from Akliouche7
Wide → FB1398 · 49%
right: 709 passes, most from Hakimi709left: 689 passes, most from Vitinha689
Central351 · 12%
left: 197 passes, most from Vitinha197right: 154 passes, most from Vitinha154
◆ Vision AI Insight
PSG progress predominantly down the right, with Vitinha the busiest midfield outlet (458 progression passes). Only 16% of passes that start in midfield actually break the final-third line — the rest (75%) is recycled back into midfield or (9%) 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 → C mid (163×) — 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
2%
Neutral / sideways
45%
Safe / backward
42%
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.

Carries Map — progressive ball-carries, squad-wide

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

307 progressive carries this season across the whole squad (19% of 1598 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 40m. Most active carrier: Vitinha (39). Filter to one player below.

First (88)Second (84)Third (81)Fourth (54)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 PSG'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.

163shots
17.5xG
0.11xG per shot
10big chances (0.3+ xG)
16goals
#1key passes / game in the league
#1box entries / game in the league
Attacking transition: 41 shots (25%)25%41Settled attack: 93 shots (57%)57%93Set piece: 29 shots (18%)18%29163SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 25% of shots4133.560.09
Cross200.170.08
Cut-back200.390.19
Long ball210.150.08
Pass into the box / short pass2822.340.08
Own creation (carry, dribble, rebound)700.510.07
Settled attack 57% of shots93910.010.11
Cross1031.980.20
Cut-back1110.980.09
Long ball610.660.11
Pass into the box / short pass5024.580.09
Own creation (carry, dribble, rebound)1621.810.11
Set piece 18% of shots2943.980.14
Corner1831.370.08
Free kick800.230.03
Penalty312.380.79

Every attempt to create — and what came of it

Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.

Who sets the shots up

PlayerSet-upsxG createdGoals
Nuno Mendes92.351
Désiré Doué151.831
Vitinha100.890
Ousmane Dembélé80.871
Fabián Ruiz90.662

Who takes them

PlayerShotsxGGoals
Désiré Doué242.481
Ousmane Dembélé202.271
Ferran Torres161.804
Marquinhos41.643
Maghnes Akliouche91.461
Vision AI Model Insight
The biggest source of PSG's chances, by xG, is settled attack (10.0 of 17.5 xG, 93 of 163 shots), mostly pass into the box / short pass. 41 of the 163 shots (25%) came within 15 seconds of winning the ball. 29 of the 163 shots came from set pieces; 16 goals from 17.5 xG (-1.5).

Chance Creation — the pass map

The football question
How does PSG 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

9CB · 8%
6Long Wide · 5%
6Long Central · 5%
47Wide → FB · 40%
49Central · 42%

Sequence success — final-third

87final-third sequences this season
31%succeed — produce a shot
39%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
CB9 · 8%
right: 5 passes, most from Marquinhos5left: 4 passes, most from Hernández4
Long Wide6 · 5%
left: 4 passes, most from Ruiz4right: 2 passes, most from Safonov2
Long Central6 · 5%
right: 4 passes, most from Mendes4left: 2 passes, most from Mendes2
Wide → FB47 · 40%
right: 25 passes, most from Vitinha25left: 22 passes, most from Ruiz22
Central49 · 42%
left: 25 passes, most from Doué25right: 24 passes, most from Hakimi24

Who creates — volume × threat

14Vitinha
11Doué
11Kvaratskhelia
10Hakimi
10Dembélé
10Ruiz
8Mendes
117key passes #1 of 18
19.4box entries/game #1 of 18
58.4final-3rd entries/game #1 of 18
2.19xG/game #1 of 18
16goals #3 of 18
-1.5finishing vs xG #16 of 18
◆ Vision AI Insight
PSG lean right — 41% of their key passes come from that flank and its half-space (48 of 117), most often from Hakimi (9). They funnel chances into the c of the final third, most often via RHS att → C att (17 key passes, most often from Doué). Vitinha is the primary source overall. They generate 2.19 xG a game and finish it wasteful — they under-perform their xG, led by Ferran Torres (4G), Marquinhos (3G), Ousmane Dembélé (1G).

Crosses & Cutbacks — squad-wide

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

117 crosses: 50 found a team-mate (43%), 13 led to a shot (11%). 43 cut-backs: 21 found a team-mate (49%), 14 led to a shot (33%). 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 PSG actually cross from?

117 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. 23% come from one territory, the byline right wing; 10 come from the half-spaces and 0 from the centre.

deep right wing: 3 crosses (3%)3%3deep right half-space: 1 crosses (1%)1%1deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 4 crosses (3%)3%4advanced right wing: 25 crosses (21%)21%25advanced right half-space: 3 crosses (3%)3%3advanced centre: 0 crosses (0%)advanced left half-space: 1 crosses (1%)1%1advanced left wing: 26 crosses (22%)22%26byline right wing: 27 crosses (23%)23%27byline right half-space: 4 crosses (3%)3%4byline centre: 0 crosses (0%)byline left half-space: 1 crosses (1%)1%1byline left wing: 22 crosses (19%)19%22
TerritoryCrossesShareLed to a shot
byline · right wing2723%2
advanced · left wing2622%5
advanced · right wing2521%0
byline · left wing2219%2
deep · left wing43%1
byline · right half-space43%2
deep · right wing33%0
advanced · right half-space33%0
deep · right half-space11%0
advanced · left half-space11%0
byline · left half-space11%1
Finishing3 sections

Shot Map

163 shots for 17.5 xG (2.19/game, #1 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

High-volume attack. 20.4 shots/game at 0.108 xG/shot. Box entries 19/game (#1). Threat created 15.5 xT/game (#1).

Goal Sequences

The move behind each of PSG’s 16 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 — 16 goals traced.

How Do They Score?

The question
Where do the goals actually come from — open play, dead balls, which foot?

Every goal PSG scored across the loaded matches, broken down by how it was created and finished.

By situation

Open play
12 · 75%
Set pieces
3 · 19%
Penalties
1 · 6%

By finish

Right foot
8 · 50%
Left foot
4 · 25%
Header
3 · 19%
Other
1 · 6%
Vision AI Model Insight
16 goals scored. 75% come in open play; set pieces add 19%. 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

46 of 237 pass attempts lost here (19%).19%46/237Marquinhos24 of 244 pass attempts lost here (10%).10%24/244Marquinhos36 of 437 pass attempts lost here (8%).8%36/437Safonov12 of 218 pass attempts lost here (6%).6%12/218Hernández33 of 185 pass attempts lost here (18%).18%33/185Zaïre-Emer39 of 567 pass attempts lost here (7%).7%39/567Hakimi40 of 645 pass attempts lost here (6%).6%40/645Marquinhos45 of 689 pass attempts lost here (7%).7%45/689Vitinha45 of 618 pass attempts lost here (7%).7%45/618Hernández42 of 574 pass attempts lost here (7%).7%42/574Ruiz85 of 474 pass attempts lost here (18%).18%85/474Hakimi60 of 308 pass attempts lost here (19%).19%60/308Hakimi36 of 205 pass attempts lost here (18%).18%36/205Neves50 of 263 pass attempts lost here (19%).19%50/263Doué60 of 386 pass attempts lost here (16%).16%60/386Kvaratskheattacking →

How they lose it

Incomplete pass — attacking third
291
Failed forward pass
188
Failed take-on
80
Lost in the defensive third
151
Their weakest zone is the right half-space in the attacking third: 19% of 308 pass attempts there are lost (60 times). Separately, 45% 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.

Pressing2 sections

Pressing — the full picture

The football question
How hard does PSG 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.

79
Pressing Index
/100 · strong
Intensity72
PPDA, high-press share, high-zone actions
Height94
how high up the pitch they defend
Effectiveness94
high recoveries & high-regain share
Disruption53
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
21%
RHS
21%
C
21%
LHS
18%
LW
19%
By third (high / mid / low regain)
Def 36%
Mid 45%
Att 18%
Read
Ranked #1 of 18 for press intensity, this is a high press. 64% of defensive actions happen in the middle & attacking thirds, at an average height of 44. Of recoveries, 66% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#1/18lower = more intense; rank is what matters
Defensive actions / game127#18/18
High-press share29%#2/18def actions won high up
Defensive-action height (0–100)44.2#1/18avg pitch height of actions
High recoveries / game28.9#1/18ball won in mid+att third
High-recovery share66%#1/18share of recoveries won high
Opponent completion allowed80%#1/18lower = more disruptive
Opponent progressive allowed9.4%#16/18of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.

How long they keep it — passes and seconds until the ball is won

The question
Once the opponent has the ball, how many passes and how many seconds pass before PSG win it back with a defensive action?

Counted over the 276 opposition possessions that PSG 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 PSG step in. PSG win it after 4.4 opponent passes in the first half-hour and after 3.7 after the hour mark (sooner).

PASSES THEY GET
4.0passes
median 3 · before PSG win it
TIME THEY KEEP IT
11sec
median 6s · 34.5 wins per game
How many passes the opponent got in before the ball was won
46%
32%
15%
7%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
4.8
14s
15–30′
4.0
10s
30–45+′
3.8
10s
45–60′
3.7
10s
60–75′
3.4
8s
75–90+′
4.0
10s
average passesaverage seconds

Attitude in each third

Every other style number here says how much PSG 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 PSG 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) 1,321 passes

playing short, circulating, safer

Width of use+0.5122.06
Wide-channel share+0.310.32
Side bias-0.66-2.31
Pass length-1.0119.07
Long-ball share-0.890.14
Forward gain per pass-1.176.37
Backward-pass share+0.450.22
Deep-pass share-1.190.17
Completion+1.080.89
Seconds between passes-0.543.00
Side used

left 25% · central 41% · right 33%

Progression (middle third) 3,093 passes

safer

Width of use-0.2225.11
Wide-channel share-0.230.39
Side bias-0.04-0.11
Pass length+0.0617.31
Long-ball share-0.310.09
Forward gain per pass-0.582.73
Backward-pass share+0.430.35
Deep-pass share-0.670.13
Completion+1.390.93
Seconds between passes-0.443.00
Side used

left 35% · central 30% · right 35%

Final third 1,636 passes

safer, circulating, more recycling

Width of use-0.6330.07
Wide-channel share-0.550.54
Side bias-0.30-2.57
Pass length-0.6414.47
Long-ball share-0.920.06
Forward gain per pass-1.04-0.34
Backward-pass share+1.010.45
Deep-pass share-0.580.07
Completion+1.530.82
Seconds between passes-0.533.00
Side used

left 38% · central 18% · right 44%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with PSG'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 PSG 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%
#16 of 18 · reaches final third in ≤3 passes
Patient build-up share46%
#1 of 18 · spells of 6+ passes
Tempo (possession length)27.6s
#18 of 18 · shorter = faster tempo
Passes per possession7.7
#1 of 18
Counter-attack shots /game1.21
#5 of 18 · shot within 12s of a regain in own half
Press→shot /game3.48
#4 of 18 · shot within 8s of a high regain
Speed to final third after regain15.2s
#17 of 18 · lower = faster break

Sequence success — attacking transition

5attacking transition sequences this season
0%succeed — produce a shot
60%turned over with nothing to show

Sequence success — defensive transition

27defensive transition sequences this season
78%succeed — reach the next third or a shot
7%turned over with nothing to show
Vision AI Model Insight
PSG are a patient build-up side: 15% of possessions reach the final third in 3 passes or fewer (#16 of 18), against 46% built patiently over 6+ passes (#1 of 18). Winning the ball back leads to a shot inside 12 seconds 1.21 times a game (#5), and a high regain converts to a shot within 8 seconds 3.48 times a game (#4 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 PSG? 275 opponent progressive passes and 86 shots faced (8.4 xG against) across the season.

Opponent threat by lane (attacking into PSG)

Right wing
20%
Right half-space
11%
Central
32%
Left half-space
12%
Left wing
25%
Where the danger came from. Opponents generated most of their threat through the central (32% of the danger conceded).

How Do They Concede?

The question
Where do the goals against PSG actually come from — open play, dead balls, and who supplies them?

Every goal PSG conceded across the loaded matches — the opponent's shots in PSG's own matches — plus every individual opponent key pass faced, each drawn as its own real arrow (not zone-clustered) with the % share of each zone behind it.

Where the goals go in

← opponent shot at own goal

Every opponent key pass against them (63 total)

2%2%2%6%5%3%2%13%17%13%25%11%Issa SoumaréAboubakar NagidaAdrien ThomassonPrzemyslaw FrankowskiQuentin MerlinHenrick Do MarcolinoGiovani VersiniHugo MagnettiLudovic AjorquePathé MboupKenny LalaEgil SelvikJoris ChotardBradley LockoEthan MbappéBenjamin AndréTiago SantosOlivier GiroudEthan MbappéEthan MbappéTiago SantosOlivier GiroudFlávio NazinhoKamory DoumbiaConrad HarderConrad HarderJeyland MitchellOsoGessime YassineKarim CoulibalyOsoConrad HarderGenesis AntwiFabio BaldéSam Amo-AmeyawDário EssugoGiovanni ReynaAlexandre LaurayLucas CalodatAlexandre LaurayBillal BrahimiLucas BretelleNeal MaupayAmine GouiriAmine HaritAmine GouiriNeal MaupayHimad AbdelliAmine GouiriAmine GouiriAngel GomesFaris MoumbagnaJordan TezeParis BrunnerAleksandr GolovinTyler MortonErnest NuamahTyler MortonErnest NuamahRuben KluivertNoah NarteyZachary AthekameAbner Vinícius← own goal

By situation

Open play
9 · 100%
Set pieces
0 · 0%
Penalties
0 · 0%
Vision AI Model Insight
9 goals conceded. 100% come in open play; set pieces account for only 0%, so dead-ball defending is not the main issue. 11% 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 (25% of key passes faced) — that is the zone to shut off.
Context

Shape and tactics

Set pieces, strengths and weaknesses, and who they resemble.

Premium
Tactical Phase Read
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
Subscribe →

Set-Piece Threat

How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.

Open play
12 g · 13.6 xG
Set pieces
3 g · 1.6 xG
Penalties
1 g
19% of goals come from set pieces (3 of 16), worth 1.6 xG from 26 shots. Set pieces are a secondary threat; the danger is in open play.

Where do PSG's corners go?

47 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 (29)

14%17%3%3%17%10%
Delivered into the box 66%Short 34%

Left side (18)

28%17%11%11%17%6%
Delivered into the box 89%Short 11%

Where opponents attack PSG from set pieces

17 shots from opponent corners against PSG, 0 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 (11)

27%9%36%9%18%
Shot 11Goals 0

Left flag (6)

33%33%33%
Shot 6Goals 0

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • xG created /game — 2.19 (94th pct)
  • press intensity (PPDA) — 4.30 (94th pct)
  • field tilt % — 73.95 (94th pct)
  • progression /game — 55.75 (94th pct)
  • box entries /game — 19.38 (94th pct)
Weaknesses (bottom-third vs league)
  • none stand out

Style Archetype & Similar Teams

Team archetype: High-press possession side. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.

Lens
83%
Toulouse
77%
Monaco
52%
Rennes
46%
Marseille
39%

Performance vs Opponent Styles

The question
Not just how PSG 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 PSG's own passing behaviour to the result.

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)2.000.503.00
vs mid-block opponents (2m)2.001.502.00
vs low-block opponents (4m)2.001.251.75

Behaviour — how PSG actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents88%9%4212.116.5
vs mid-block opponents88%11%6418.424.0
vs low-block opponents90%8%5815.718.5
Vision AI Model Insight
Facing a high press, retention drops to 88% vs 90% against a low block (3pt lower under pressure), and directness (long-ball share) sits at 9% when pressed vs 8% against a low block — their passing style barely changes regardless of how the opponent sets up, for better or worse.

Scouting Summary — the team in brief

In brief. PSG are possession-dominant with a aggressive high-press. Their attack creates 2.19 xG a game and they concede 1.05 a game. [Event-data based — no tracking, so off-ball structure and marking scheme need video.]
Squad

Players

Who drives the numbers.

Against Their Own Norm

For each of ten match numbers, the one match this season that departed furthest from PSG’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.

PSG
across 8 matches this season
PPDAat Brest · 1-0 · 2026-09-137.2avg 4.3
Field tiltat Brest · 1-0 · 2026-09-1358%avg 74%
Progressive passesat Lille · 2-2 · 2026-08-2886avg 56
Expected goalsat Marseille · 2-1 · 2026-09-204.36avg 2.19
Pass accuracyvs Lyon · 2-0 · 2026-10-2692%avg 89%
Defensive actionsvs Monaco · 1-2 · 2026-09-04154avg 127
Threat from passingat Rennes · 2-2 · 2026-08-2310.19avg 6.73
Final-third entriesat Rennes · 2-2 · 2026-08-23100avg 73

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 PSG’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).

+18.8on-ball value, 8 matches
Where the value came from
Passes6050 actions+6.38
Carries1598 actions+1.35
Dribbles152 actions+0.13
Shots163 actions+8.44
Ball wins479 actions+2.49
Most on-ball value (OBV)ActionsOBVper 100
Ousmane Dembélé257+3.66+1.42
Désiré Doué472+2.77+0.59
Vitinha1057+2.44+0.23
Nuno Mendes234+1.27+0.54
Khvicha Kvaratskhelia372+1.06+0.29
Maghnes Akliouche507+1.03+0.20
Beraldo222+1.00+0.45
Achraf Hakimi694+0.94+0.13
123456
Biggest single movesOBV
1  Ousmane Dembélé · shot+0.750
2  Désiré Doué · shot+0.740
3  Beraldo · shot+0.740
4  Nuno Mendes · pass+0.492
5  Ousmane Dembélé · pass+0.484
6  Khvicha Kvaratskhelia · pass+0.417

Set Pieces by Player

Who delivers PSG’s dead balls and who finishes them this season. 47 corners taken, most by Ousmane Dembélé (16); 26 shots from corners and free kicks, 3 goals, led by Marquinhos (2 goals, 0.63 xG). “Into the box” counts corners that landed inside the penalty area; free-kick takers are the players who shot from one, because this feed does not mark who delivers the others.

PlayerCorners takenInto the boxSet-piece shotsGoalsxGFree-kick shotsPenalties
Ousmane Dembélé169 (56%)1—0.06—0/1
Khvicha Kvaratskhelia1210 (83%)3—0.092—
Désiré Doué105 (50%)1—0.05—0/1
Achraf Hakimi10 (0%)5—0.113—
Vitinha11 (100%)3—0.071—
Ollie Watkins——3—0.081—
João Neves——3—0.161—
Mika Godts74 (57%)——0.00——
Illia Zabarnyi——210.21——
Marquinhos——220.63——
Beraldo——1—0.02—1/1
Nuno Mendes——1—0.02——
Lucas Hernández——1—0.09——

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.

playerposminVision AI Scorecapability blocks
VitinhaCM6238.4Progression 93%Ball-Carrying 83%Successful Dribble 70%Chance Creation 48%
Warren Zaïre-EmeryCB5887.1Ball-Carrying 85%Progression 77%Ball-Winning 41%Aerial & Box Defending 0%
Désiré DouéST4556.8Ball-Carrying 87%Box Threat 79%Finishing 53%Aerial Threat 0%
João NevesCM5186.2Progression 64%Ball-Carrying 57%Chance Creation 40%Successful Dribble 34%
Willian PachoCB5686.1Ball-Winning 62%Ball-Carrying 44%Progression 34%Aerial & Box Defending 6%
MarquinhosCB4736.0Ball-Carrying 82%Progression 71%Ball-Winning 36%Aerial & Box Defending 4%
Achraf HakimiFB5216.0Ball-Carrying 90%Wide Delivery 43%Ball-Winning 24%
Matvey SafonovGK7605.0Shot-Stopping 50%
Ferran TorresST5234.8Box Threat 61%Finishing 59%Ball-Carrying 26%Aerial Threat 0%
Maghnes AklioucheST5122.7Ball-Carrying 48%Finishing 33%Box Threat 26%Aerial Threat 0%

Top Creators

Chance creation leaders — key passes /90 and box entries.

playerposminkey P /90box entriesxT
Désiré DouéF4552.18188.5
Ousmane DembéléF2483.63195.7
VitinhaM6232.021316.4
Khvicha KvaratskheliaF3872.56154.6
Achraf HakimiD5211.73149.3
Fabián RuizM4352.07129.6
Maghnes AklioucheF5121.41116.7
Nuno MendesD2323.10115.3

Wide Delivery Leaders

Crosses and cutbacks — wingers and full-backs only (by real average position, not the raw D/M position code), ranked by combined volume.

playerposmincrosses (completed)cutbacks (completed)
Achraf HakimiFB5216 (17%)13 (38%)
Khvicha KvaratskheliaW3873 (33%)12 (75%)
Ousmane DembéléW2483 (33%)8 (38%)
Mika GodtsW2416 (67%)3 (0%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
João NevesM51810014830
Willian PachoD5689212634
MarquinhosD473782127
VitinhaM623757640
Warren Zaïre-EmeryD588749234
Désiré DouéF4556914318
Maghnes AklioucheF5126712520
Achraf HakimiD521655726

Full Squad Data

Every player with 100+ minutes (20 players).

playerposappsmingoalsxGkey PprogdefxT
Matvey SafonovG876000.017263.3
VitinhaM862310.714427516.4
Warren Zaïre-EmeryD858800.8422747.2
Willian PachoD656800.005924.9
Ferran TorresF852341.858362.0
Achraf HakimiD752101.11054659.3
João NevesM751801.45241005.7
Maghnes AklioucheF851211.5830676.7
MarquinhosD547331.62247810.3
Désiré DouéF845512.51152698.5
Fabián RuizM743500.61031479.6
Khvicha KvaratskheliaF738711.31126324.6
Lucas HernándezD534900.1212495.3
Illia ZabarnyiD328710.216344.4
Ousmane DembéléF524812.31019125.7
Mika GodtsF724110.4725254.7
BeraldoM623210.806292.9
Nuno MendesD323200.3823335.3
Ollie WatkinsD317300.1422274.4
Dro FernándezM516500.126312.1

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.

Matvey Safonov
Goalkeeper · Goalkeeper
minutes760
goals · xG0 · 0.0
prog passes /900.8
key passes /900.12
def actions /903.1
pass accuracy84%
Vitinha
Deep-lying playmaker · Midfielder
minutes623
goals · xG1 · 0.7
prog passes /906.1
key passes /902.02
def actions /9010.8
pass accuracy91%
Warren Zaïre-Emery
Stopper / marker · Defender
minutes588
goals · xG0 · 0.8
prog passes /903.4
key passes /900.61
def actions /9011.3
pass accuracy92%
Willian Pacho
Stopper / marker · Defender
minutes568
goals · xG0 · 0.0
prog passes /900.8
key passes /900.00
def actions /9014.6
pass accuracy97%
Ferran Torres
Box-to-box midfielder · Midfielder
minutes523
goals · xG4 · 1.8
prog passes /901.4
key passes /900.86
def actions /906.2
pass accuracy79%
Achraf Hakimi
Ball-playing defender · Defender
minutes521
goals · xG0 · 1.1
prog passes /909.3
key passes /901.73
def actions /9011.2
pass accuracy88%
João Neves
Ball-winner / destroyer · Midfielder
minutes518
goals · xG0 · 1.4
prog passes /904.2
key passes /900.87
def actions /9017.4
pass accuracy90%
Maghnes Akliouche
Ball-winner / destroyer · Midfielder
minutes512
goals · xG1 · 1.5
prog passes /905.3
key passes /901.41
def actions /9011.8
pass accuracy89%
Marquinhos
Ball-playing defender · Defender
minutes473
goals · xG3 · 1.6
prog passes /904.6
key passes /900.38
def actions /9014.8
pass accuracy90%
Vision AI · building report