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Team reportLa Liga 2026

Barcelona

A possession-dominant side, aggressive high-press out of possession, with a high-volume attack. Currently #1 of 20 on 27 points (9-0-1, 40:11). Tactical profile below is built from 10 matches of ball-by-ball event data, contextualised against the league.

possession-dominantaggressive high-presshigh-volume attack
W
W
L
W
L
W
W
W
W
W
W
W
W
W
L
27
points
#1 of 20 · 10 games
40:11
goals
+29 GD
9-0-1
record
W-D-L
2.70
points/game
#1 in the league
2.78
xG for/game
rank #1
0.88
xG against/game
rank #1
#1
press rank
of 20 · most aggressive
73%
field tilt
#1
Barcelona
League average
Expected goals for / game
2.781.35
Expected goals against / game
0.881.35
Field tilt
73%50%
Pass retention
90%82%
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 Barcelona and how good was the season?
Read. Barcelona currently sit #1 of 20 on 27 points (9W-0D-1L, 2.70 pts/game), scoring 40 and conceding 11 for a goal difference of +29. On the ball they are a possession-dominant team (73% field tilt, #1 in the league); off it they defend with a aggressive high-press (#1 of 20 for press intensity). Across the 10 matches of event data, they create 2.78 xG/game (#1) and concede 0.88 (#1), a net of +1.90 xG/game — the underlying performance diverges from the actual goal difference.

Season Context — the league table

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

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

#teamPWDLGFGAGDPts
1Barcelona109014011+2927
2Atletico10811208+1225
3Real Madrid108022510+1524
4Real Betis106221614+220

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Barcelona 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+'+5.03
Vision AI Model Insight
Barcelona tend to come alive after the break — first-half net xG +7.15, second-half +11.81. Their strongest period is 76-90+' (net +5.03 xG); their most dangerous period to face is 16-30' (net +2.14 xG against them).

xG Race — the season, match by match

Expected goals piling up over 10 matches: Barcelona against what their opponents created. A line pulling away upwards is a side creating more than it gives away; the gap at the end is the season’s balance (+19.0 xG). Hover a point for that match.

010203027.88.8Elche (A) 5-0 · xG 2.56 to 0.57Athletic Club (H) 2-0 · xG 3.12 to 0.31Rayo Vallecano (H) 5-2 · xG 2.31 to 1.04Valencia (A) 5-0 · xG 3.72 to 0.47Levante (A) 4-2 · xG 1.88 to 1.88Racing Santander (H) 7-2 · xG 5.85 to 1.69Sevilla (A) 3-1 · xG 2.73 to 0.50Getafe (H) 3-0 · xG 1.98 to 0.19Real Betis (A) 5-2 · xG 2.14 to 1.03Real Madrid (H) 1-2 · xG 1.48 to 1.13M1M2M3M4M5M6M7M8M9M10
BarcelonaOpponents against Barcelona

Tactical DNA

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

95
Build-Up
possession control from the back
90
Progression
moving the ball upfield with threat
92
Creation
manufacturing chances
95
Press
winning the ball high & hard
95
Solidity
resisting the opponent's threat
Genetic identity
Barcelona are defined most by their Build-Up DNA (95/100 · elite at possession control from the back), and least by their Progression DNA (90/100). Percentiles vs the 20 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).

Possess96Disrupt61Finish81Press91Defend94
Possess
Deep buildup
96%
Possession
96%
Field tilt
96%
Disrupt
Central progression ~proxy
83%
Dribble tendency
17%
Progressive passes
83%
Finish
Final-third patience
57%
Shot quality
91%
Open-play xG
96%
Press
Forward press ~proxy
96%
High regains
87%
Pressing efficiency ~proxy
91%
Defend
Def-mid press ~proxy
96%
High line ~proxy
91%
PAdj defensive actions
96%
Barcelona is defined most by Possess (96% in the league) and weakest on Disrupt (61%). Percentiles vs the 23 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 Barcelona actually control, relative to the rest of the league?

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

Barcelona: 73% tilt, 2.70 pts/gAtletico: 61% tilt, 2.50 pts/gReal Madrid: 52% tilt, 2.40 pts/gReal Betis: 51% tilt, 2.00 pts/gReal Sociedad: 47% tilt, 1.90 pts/gSevilla: 50% tilt, 1.56 pts/gAthletic Club: 60% tilt, 1.33 pts/gOsasuna: 45% tilt, 1.22 pts/gAlaves: 49% tilt, 1.20 pts/gVillarreal: 64% tilt, 1.20 pts/gCelta Vigo: 50% tilt, 1.20 pts/gDeportivo: 44% tilt, 1.10 pts/gRacing Santander: 47% tilt, 1.10 pts/gElche: 46% tilt, 1.00 pts/gRayo Vallecano: 47% tilt, 1.00 pts/gLevante: 43% tilt, 1.00 pts/gGetafe: 43% tilt, 0.90 pts/gEspanyol: 45% tilt, 0.80 pts/gValencia: 39% tilt, 0.60 pts/gMalaga: 46% tilt, 0.50 pts/gBarcelona39%50%61%73%0.51.22.02.7FIELD TILT %POINTS / GAME
Vision AI Model Insight
Barcelona post 73% field tilt, ranking #1 of 20 in the league — a genuinely territory-dominant side, and their 2.70 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 Barcelona has the ball, how much of that time is spent building, progressing and creating?

The share of Barcelona'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: 18.0% of the time on the ball18%Progression: 56.6% of the time on the ball57%Chance creation: 23.3% of the time on the ball23%Attacking transition: 2.2% of the time on the ball57%PROGRESSION
PhaseShare of the time
Build-up18.0%
Progression56.6%
Chance creation23.3%
Attacking transition2.2%
Vision AI Model Insight
Progression is where Barcelona spends most of its time on the ball (57% 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.

Pau Cubarsí ↔ Gerard Martín: 178 passes, 0.9 combined xTEric García ↔ Lamine Yamal: 174 passes, 2.8 combined xTRodri ↔ Pedri: 173 passes, 0.9 combined xTEric García ↔ Pau Cubarsí: 165 passes, -0.8 combined xTRodri ↔ Pau Cubarsí: 137 passes, -0.6 combined xTRodri ↔ Eric García: 126 passes, 0.9 combined xTRodri ↔ Gerard Martín: 123 passes, -0.5 combined xTPedri ↔ Pau Cubarsí: 111 passes, 0.0 combined xTGerard Martín ↔ Xavi Espart: 109 passes, -1.2 combined xTFermín López ↔ Lamine Yamal: 98 passes, 3.2 combined xTPedri ↔ Xavi Espart: 96 passes, 0.9 combined xTAndreas Christensen ↔ Gerard Martín: 91 passes, -0.1 combined xTEric García ↔ Pedri: 90 passes, 0.5 combined xTJoan García ↔ Gerard Martín: 83 passes, -0.2 combined xTPedri ↔ Lamine Yamal: 83 passes, 1.6 combined xTPedri ↔ Gerard Martín: 83 passes, -0.0 combined xTAndreas Christensen ↔ Pau Cubarsí: 76 passes, -0.1 combined xTAndreas Christensen ↔ Eric García: 74 passes, -0.1 combined xTEric García ↔ Fermín López: 73 passes, 1.1 combined xTRodri ↔ Fermín López: 66 passes, 0.7 combined xTRodri ↔ Xavi Espart: 65 passes, 0.5 combined xTRodri ↔ Lamine Yamal: 65 passes, 1.0 combined xTJoan García ↔ Pau Cubarsí: 62 passes, 0.0 combined xTAnthony Gordon ↔ Xavi Espart: 59 passes, 1.0 combined xTKarim Adeyemi — isolate this player's connectionsAdeyemiPedri — isolate this player's connectionsPedriLamine Yamal — isolate this player's connectionsYamalGerard Martín — isolate this player's connectionsMartínJoan García — isolate this player's connectionsGarcíaRodri — isolate this player's connectionsRodriAnthony Gordon — isolate this player's connectionsGordonFermín López — isolate this player's connectionsLópezDani Olmo — isolate this player's connectionsOlmoRaphinha — isolate this player's connectionsRaphinhaEric García — isolate this player's connectionsGarcíaMarc Bernal — isolate this player's connectionsBernalXavi Espart — isolate this player's connectionsEspartPau Cubarsí — isolate this player's connectionsCubarsíJoão Cancelo — isolate this player's connectionsCanceloAndreas Christensen — isolate this player's connectionsChristense
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Cubarsí ↔ Martín
178p · 0.9xT
García ↔ Yamal
174p · 2.8xT
Rodri ↔ Pedri
173p · 0.9xT
García ↔ Cubarsí
165p · -0.8xT
Rodri ↔ Cubarsí
137p · -0.6xT
Rodri ↔ García
126p · 0.9xT
Rodri ↔ Martín
123p · -0.5xT
Pedri ↔ Cubarsí
111p · 0.0xT
Martín ↔ Espart
109p · -1.2xT
López ↔ Yamal
98p · 3.2xT
Vision AI Model Insight
Busiest connection: Pau Cubarsí ↔ Gerard Martín (178 passes). Most dangerous per pass: Fermín López ↔ Lamine Yamal (0.03 xT/pass over 98 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Barcelona had the ball

Every touch across 98 matches. Brighter means more touches.

Which Zones Do They Attack Through?

The question
Across the whole pitch, where does Barcelona 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
7282
ACTIONS
3%4%7%3%3%10%13%14%13%8%5%5%4%5%5%PASSES
Carries
the ball moved with a player
1783
ACTIONS
2%5%7%5%2%8%11%16%14%8%5%3%2%3%8%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the middle third (14.6% of all actions). 67% of actions run through the inside lanes (centre + both half-spaces) versus 33% down the two wings — an inside-dominant, half-space build. By third: 20% defensive, 58% middle, 23% 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. Barcelona spread it evenly (no channel above 37%). The bars under the pitch put the league’s share beside theirs.

35%Left side28%Middle37%Right sideATTACKING →
Barcelona
35%28%37%
League
38%23%39%

Final-Third Entries

Every completed pass or carry that took the ball from outside the final third into it, by the channel it arrived in. Barcelona made 707 this season (70.7 a match); 28% came into the left wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.

Left wing: 198 entries (28%)19828%LEFT WINGLeft half-space: 105 entries (15%)10515%LEFT HALF-SPACECentre: 122 entries (17%)12217%CENTRERight half-space: 106 entries (15%)10615%RIGHT HALF-SPACERight wing: 176 entries (25%)17625%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing19819.828%29%
Left half-space10510.515%15%
Centre12212.217%12%
Right half-space10610.615%15%
Right wing17617.625%29%
Build-up2 sections

Build-Up — the pass map

The football question
How does Barcelona 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.

1405build-up passes attempted
91%completed
28%reach the middle third
0%go long into the final third

Pass types

713CB · 56%
54Long Wide · 4%
3Long Central · 0%
360Wide → FB · 28%
146Central · 11%

Sequence success — build-up

145build-up sequences this season
18%succeed — reach the next third or a shot
31%turned over with nothing to show
CB713 · 56%
right: 358 passes, most from Cubarsí358left: 355 passes, most from Martín355
Long Wide54 · 4%
right: 30 passes, most from García30left: 24 passes, most from García24
Long Central3 · 0%
left: 3 passes, most from García3
Wide → FB360 · 28%
right: 221 passes, most from García221left: 139 passes, most from García139
Central146 · 11%
right: 81 passes, most from García81left: 65 passes, most from García65
◆ Vision AI Insight
Barcelona build predominantly down the right, with Cubarsí as the fulcrum (220 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 (99×).

Pass Explorer

Every pass of Barcelona’s last 10 matches as an arrow, theirs first and the opponents’ with other team, each side attacking left to right (solid = completed, dashed grey = failed). Eight families per team — click any map to open it wide, then filter by channel or third, from one to another (or click a cell of the flow grids), by outcome, half, minute and passer. Channels: right wing, right half-space, centre, left half-space, left wing.

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. 536 progressive passes across 10 matches (53.6/game).

Origin lane

Right wing
27%
Right half-space
20%
Central
11%
Left half-space
18%
Left wing
24%
Progression is right-dominant: 47% right side · 11% central · 42% left.

Who generates it

Lamine Yamal
73 · 14%
Eric García
49 · 9%
Pedri
44 · 8%
Gerard Martín
42 · 8%
Xavi Espart
37 · 7%
Top two — Lamine Yamal & Eric García — account for 23% of all progression.
PROGRESSION
53.6 prog passes/game
mostly right
→
PENETRATION
29% reach final third
21% reach the box
→
THREAT
the other 71% is recycled
progress ≠ danger
What came of it. 29% of progressive passes reached the final third and 21% the box; the rest was recycled in front of the block. 23% 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
Centralbalanced
Left half-spacebalanced
Left wingbalanced

Progression — the pass map

The football question
Once Barcelona 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.

4200progression passes attempted
93%completed
15%break into the final third
7%go backward into the defensive third

Pass types

1792CB · 46%
79Long Wide · 2%
9Long Central · 0%
1488Wide → FB · 38%
536Central · 14%

Sequence success — progression

271progression sequences this season
28%succeed — reach the next third or a shot
31%turned over with nothing to show
CB1792 · 46%
left: 931 passes, most from Martín931right: 861 passes, most from García861
Long Wide79 · 2%
left: 40 passes, most from Rodri40right: 39 passes, most from Rodri39
Long Central9 · 0%
right: 7 passes, most from Yamal7left: 2 passes, most from Pedri2
Wide → FB1488 · 38%
right: 834 passes, most from Koundé834left: 654 passes, most from Rodri654
Central536 · 14%
right: 305 passes, most from Pedri305left: 231 passes, most from Rodri231
◆ Vision AI Insight
Barcelona progress predominantly down the right, with Rodri the busiest midfield outlet (496 progression passes). Only 15% of passes that start in midfield actually break the final-third line — the rest (78%) is recycled back into midfield or (7%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LHS mid → C mid (272×) — 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
47%
Safe / backward
38%
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 Barcelona actually progress the ball with their feet, not a pass?

392 progressive carries this season across the whole squad (22% of 1783 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: Martín (50). Filter to one player below.

First (130)Second (121)Third (77)Fourth (64)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 Barcelona's chances actually come from?

Every shot traced back to its source: set pieces, or the pass that set it up (a cross, a cut-back, a long ball, a pass into the box) or no pass at all (the player created it himself).

209shots
27.8xG
0.13xG per shot
20big chances (0.3+ xG)
38goals
#1key passes / game in the league
#3box entries / game in the league
Cross: 19 shots (9%)9%19Cut-back: 19 shots (9%)9%19Long ball: 7 shots (3%)Pass into the box / short pass: 97 shots (46%)46%97Own creation (carry, dribble, rebound): 28 shots (13%)13%28Corner: 24 shots (11%)11%24Free kick: 10 shots (5%)5%10Penalty: 5 shots (2%)209SHOTS
Source of the shotShotsGoalsxGxG / shot
Cross1922.140.11
Cut-back1952.510.13
Long ball700.990.14
Pass into the box / short pass971911.220.12
Own creation (carry, dribble, rebound)2853.530.13
Corner2433.130.13
Free kick1000.280.03
Penalty543.970.79

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
Lamine Yamal273.765
Dani Olmo132.153
Raphinha161.972
Anthony Gordon161.884
Fermín López81.482

Who takes them

PlayerShotsxGGoals
Raphinha326.9913
Lamine Yamal536.168
Karim Adeyemi162.992
Anthony Gordon212.351
Fermín López152.114
Vision AI Model Insight
The biggest source of Barcelona's chances, by xG, is pass into the box / short pass (11.2 of 27.8 xG, 97 of 209 shots). 39 of the 209 shots came from set pieces; 38 goals from 27.8 xG (+10.2).

Chance Creation — the pass map

The football question
How does Barcelona 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

20CB · 12%
9Long Wide · 5%
9Long Central · 5%
55Wide → FB · 34%
71Central · 43%

Sequence success — final-third

175final-third sequences this season
32%succeed — produce a shot
21%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
CB20 · 12%
left: 12 passes, most from Cancelo12right: 8 passes, most from Espart8
Long Wide9 · 5%
left: 5 passes, most from López5right: 4 passes, most from Adeyemi4
Long Central9 · 5%
left: 5 passes, most from Raphinha5right: 4 passes, most from Yamal4
Wide → FB55 · 34%
left: 28 passes, most from Gordon28right: 27 passes, most from Yamal27
Central71 · 43%
right: 37 passes, most from Yamal37left: 34 passes, most from Yamal34

Who creates — volume × threat

30Yamal
19Pedri
17Raphinha
15Olmo
14López
14Gordon
9Adeyemi
164key passes #1 of 20
18.6box entries/game #3 of 20
60.4final-3rd entries/game #1 of 20
2.78xG/game #1 of 20
38goals #1 of 20
+10.2finishing vs xG #1 of 20
◆ Vision AI Insight
Barcelona lean right — 38% of their key passes come from that flank and its half-space (63 of 164), most often from Yamal (21). They funnel chances into the c of the final third, most often via RHS att → C att (23 key passes, most often from Yamal). Yamal is the primary source overall. They generate 2.78 xG a game and finish it clinical — they beat their xG, led by Raphinha (13G), Lamine Yamal (8G), Fermín López (4G).

Crosses & Cutbacks — squad-wide

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

114 crosses: 51 found a team-mate (45%), 22 led to a shot (19%). 53 cut-backs: 35 found a team-mate (66%), 19 led to a shot (36%). 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 Barcelona actually cross from?

114 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. 29% come from one territory, the advanced right wing; 10 come from the half-spaces and 0 from the centre.

deep right wing: 10 crosses (9%)9%10deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 4 crosses (4%)4%4advanced right wing: 33 crosses (29%)29%33advanced right half-space: 2 crosses (2%)2%2advanced centre: 0 crosses (0%)advanced left half-space: 2 crosses (2%)2%2advanced left wing: 25 crosses (22%)22%25byline right wing: 13 crosses (11%)11%13byline right half-space: 2 crosses (2%)2%2byline centre: 0 crosses (0%)byline left half-space: 4 crosses (4%)4%4byline left wing: 19 crosses (17%)17%19
TerritoryCrossesShareLed to a shot
advanced · right wing3329%4
advanced · left wing2522%3
byline · left wing1917%6
byline · right wing1311%3
deep · right wing109%1
deep · left wing44%0
byline · left half-space44%1
advanced · right half-space22%1
advanced · left half-space22%1
byline · right half-space22%2
Finishing3 sections

Shot Map

209 shots for 27.8 xG (2.78/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. 20.9 shots/game at 0.133 xG/shot. Box entries 19/game (#3). Threat created 15.2 xT/game (#1).

Goal Sequences

The move behind each of Barcelona’s 40 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 — 40 goals traced.

How Do They Score?

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

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

By situation

Open play
31 · 82%
Set pieces
3 · 8%
Penalties
4 · 11%

By finish

Right foot
14 · 37%
Left foot
22 · 58%
Header
2 · 5%
Vision AI Model Insight
38 goals scored. 82% 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

30 of 186 pass attempts lost here (16%).16%30/186García22 of 270 pass attempts lost here (8%).8%22/270García31 of 517 pass attempts lost here (6%).6%31/517García13 of 233 pass attempts lost here (6%).6%13/233Martín33 of 199 pass attempts lost here (17%).17%33/199Espart69 of 712 pass attempts lost here (10%).10%69/712Yamal72 of 944 pass attempts lost here (8%).8%72/944García61 of 1036 pass attempts lost here (6%).6%61/1036Rodri47 of 919 pass attempts lost here (5%).5%47/919Martín47 of 589 pass attempts lost here (8%).8%47/589Espart60 of 386 pass attempts lost here (16%).16%60/386Yamal83 of 344 pass attempts lost here (24%).24%83/344Yamal53 of 260 pass attempts lost here (20%).20%53/260López86 of 332 pass attempts lost here (26%).26%86/332Gordon45 of 355 pass attempts lost here (13%).13%45/355Adeyemiattacking →

How they lose it

Incomplete pass — attacking third
327
Failed forward pass
228
Failed take-on
120
Lost in the defensive third
129
Their weakest zone is the left half-space in the attacking third: 26% of 332 pass attempts there are lost (86 times). Separately, 43% 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 Barcelona 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.

88
Pressing Index
/100 · elite
Intensity85
PPDA, high-press share, high-zone actions
Height95
how high up the pitch they defend
Effectiveness95
high recoveries & high-regain share
Disruption72
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
19%
RHS
23%
C
20%
LHS
19%
LW
18%
By third (high / mid / low regain)
Def 39%
Mid 45%
Att 16%
Read
Ranked #1 of 20 for press intensity, this is a high press. 61% of defensive actions happen in the middle & attacking thirds, at an average height of 42. Of recoveries, 64% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#1/20lower = more intense; rank is what matters
Defensive actions / game139#18/20
High-press share25%#3/20def actions won high up
Defensive-action height (0–100)42.7#1/20avg pitch height of actions
High recoveries / game26.6#1/20ball won in mid+att third
High-recovery share64%#1/20share of recoveries won high
Opponent completion allowed74%#1/20lower = more disruptive
Opponent progressive allowed9.1%#10/20of 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 Barcelona win it back with a defensive action?

Counted over the 328 opposition possessions that Barcelona 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 Barcelona step in. Barcelona win it after 3.7 opponent passes in the first half-hour and after 3.5 after the hour mark (about the same).

PASSES THEY GET
3.6passes
median 2 · before Barcelona win it
TIME THEY KEEP IT
10sec
median 5s · 32.8 wins per game
How many passes the opponent got in before the ball was won
51%
30%
13%
6%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
3.8
10s
15–30′
3.7
10s
30–45+′
3.8
11s
45–60′
3.4
10s
60–75′
3.4
9s
75–90+′
3.6
11s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Barcelona 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 Barcelona 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) 1,405 passes

shorter passing, safer, kept on the floor

Width of use-0.0620.88
Wide-channel share-0.230.29
Side bias-0.17-0.46
Pass length-1.3917.68
Long-ball share-1.370.10
Forward gain per pass-1.206.28
Backward-pass share-0.310.18
Deep-pass share-1.270.17
Completion+1.390.91
Seconds between passes-0.543.00
Side used

left 28% · central 43% · right 29%

Progression (middle third) 4,200 passes

safer, shorter passing, kept on the floor

Width of use-0.9323.60
Wide-channel share-0.970.34
Side bias-0.40-1.51
Pass length-1.3115.39
Long-ball share-1.270.05
Forward gain per pass-0.622.66
Backward-pass share-0.480.31
Deep-pass share-1.150.10
Completion+1.330.93
Seconds between passes-0.443.00
Side used

left 32% · central 33% · right 35%

Final third 1,677 passes

narrow, central, played inside, safer

Width of use-1.4328.07
Wide-channel share-1.410.47
Side bias-0.15-1.50
Pass length-1.1013.76
Long-ball share-1.050.05
Forward gain per pass-0.94-0.21
Backward-pass share+0.940.45
Deep-pass share-0.520.07
Completion+1.310.80
Seconds between passes-0.263.20
Side used

left 37% · central 21% · right 42%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Barcelona'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 Barcelona 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%
#18 of 20 · reaches final third in ≤3 passes
Patient build-up share43%
#1 of 20 · spells of 6+ passes
Tempo (possession length)25.3s
#20 of 20 · shorter = faster tempo
Passes per possession7.0
#1 of 20
Counter-attack shots /game1.06
#7 of 20 · shot within 12s of a regain in own half
Press→shot /game3.88
#2 of 20 · shot within 8s of a high regain
Speed to final third after regain15.6s
#20 of 20 · lower = faster break

Sequence success — attacking transition

10attacking transition sequences this season
20%succeed — produce a shot
40%turned over with nothing to show

Sequence success — defensive transition

65defensive transition sequences this season
51%succeed — reach the next third or a shot
11%turned over with nothing to show
Vision AI Model Insight
Barcelona are a patient build-up side: 15% of possessions reach the final third in 3 passes or fewer (#18 of 20), against 43% built patiently over 6+ passes (#1 of 20). Winning the ball back leads to a shot inside 12 seconds 1.06 times a game (#7), and a high regain converts to a shot within 8 seconds 3.88 times a game (#2 of 20) — a genuine transition weapon.
Defending the box2 sections

Vulnerability Map — how opponents hurt them

The report flipped: where do opponents create their threat against Barcelona? 297 opponent progressive passes and 71 shots faced (8.8 xG against) across the season.

Opponent threat by lane (attacking into Barcelona)

Right wing
27%
Right half-space
9%
Central
25%
Left half-space
10%
Left wing
29%
Where the danger came from. Opponents generated most of their threat through the left wing (29% of the danger conceded).

How Do They Concede?

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

Every goal Barcelona conceded across the loaded matches — the opponent's shots in Barcelona'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 (50 total)

2%2%8%2%2%20%8%20%22%14%Peio CanalesBeñat GerenabarrenaÁlex BerenguerOihan SancetÁlex BerenguerGonzalo VillarGonzalo VillarFederico RedondoGermán ValeraEzequiel PonceGermán ValeraLucas CepedaAurélien TchouaméniÁlvaro GarcíaSergio CamelloUnai LópezAdrià PedrosaPedro DíazPedro DíazAdrià PedrosaPedro DíazKylian MbappéArda GülerArda GülerDenzel DumfriesKylian MbappéEduardo CamavingaAdrián de la FuenteAïssa MandiVíctor GarcíaEnzo BardeliAïssa MandiFilip UgrinicRamón TerratsAndrés GarcíaMario MartínFélix CorreiaJuan IglesiasMiguel SierraGabriel SuazoIsaac RomeroJon GuridiAarón MartínÍñigo Sainz-MazaPablo FornalsPablo FornalsGiovani Lo CelsoGiovani Lo CelsoAbde EzzalzouliTroy Parrott← own goal

By situation

Open play
9 · 82%
Set pieces
2 · 18%
Penalties
0 · 0%
Vision AI Model Insight
11 goals conceded. 82% come in open play; set pieces account for only 18%, 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 left half-space of the attacking third (22% of key passes faced) — that is the zone to shut off.
Context

Shape and tactics

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

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
31 g · 20.4 xG
Set pieces
3 g · 3.4 xG
Penalties
4 g
8% of goals come from set pieces (3 of 38), worth 3.4 xG from 34 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Barcelona's corners go?

71 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 (32)

47%6%3%6%3%3%16%6%3%
Delivered into the box 94%Short 6%

Left side (39)

5%13%31%15%21%5%
Delivered into the box 90%Short 10%

Where opponents attack Barcelona from set pieces

8 shots from opponent corners against Barcelona, 2 conceded, split by the flag the corner came from — arrows from the flag, dots where the shot was taken (gold = goal), shaded by the % of that flag's shots in each zone. Tap or hover a shot for who took it, the minute and the match; filter to one match and the shading recomputes for just that game.

Right flag (3)

100%
Shot 3Goals 1

Left flag (5)

20%40%20%20%
Shot 5Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • xG created /game — 2.78 (95th pct)
  • xG conceded /game — 0.88 (95th pct)
  • press intensity (PPDA) — 3.72 (95th pct)
  • field tilt % — 72.97 (95th pct)
  • threat created /game — 15.23 (95th 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.

Villarreal
90%
Atletico
86%
Real Madrid
74%
Athletic Club
73%
Real Betis
13%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (3m)4.331.003.00
vs mid-block opponents (3m)4.002.002.00
vs low-block opponents (4m)3.750.503.00

Behaviour — how Barcelona actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents88%6%4813.015.7
vs mid-block opponents89%5%4914.519.0
vs low-block opponents91%6%6217.520.5
Vision AI Model Insight
Facing a high press, retention drops to 88% vs 91% against a low block (2pt lower under pressure), and directness (long-ball share) sits at 6% when pressed vs 6% 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. Barcelona are possession-dominant with a aggressive high-press. Their attack creates 2.78 xG a game and they concede 0.88 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 Barcelona’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.

Barcelona
across 10 matches this season
Expected goalsvs Racing Santander · 7-2 · 2026-09-165.85avg 2.78
Field tiltat Elche · 5-0 · 2026-08-2342%avg 73%
PPDAvs Getafe · 3-0 · 2026-10-101.8avg 3.7
Progressive carriesvs Real Madrid · 1-2 · 2026-10-25101avg 73
Final-third entriesat Elche · 5-0 · 2026-08-2337avg 71
Pass accuracyat Elche · 5-0 · 2026-08-2387%avg 90%
Passesvs Getafe · 3-0 · 2026-10-10897avg 728
Defensive actionsat Elche · 5-0 · 2026-08-23174avg 139

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 Barcelona’s last 10 matches added up: where the value came from, who produced it, and the six biggest single moves.

+29.9on-ball value, 10 matches
Where the value came from
Passes7282 actions+10.79
Carries1783 actions-0.39
Dribbles252 actions+2.06
Shots209 actions+14.05
Ball wins580 actions+3.42
Most valuable playersActionsOBVper 100
Lamine Yamal795+6.00+0.75
Raphinha378+3.57+0.94
Fermín López440+2.29+0.52
Anthony Gordon389+2.29+0.59
Pedri967+2.07+0.21
Rodri1001+2.01+0.20
Karim Adeyemi273+1.97+0.72
Pau Cubarsí908+1.72+0.19
123456
Biggest single movesOBV
1  Raphinha · shot+0.824
2  Raphinha · shot+0.810
3  Lamine Yamal · shot+0.800
4  Raphinha · shot+0.792
5  Lamine Yamal · shot+0.779
6  Fermín López · pass+0.562

Set Pieces by Player

Who delivers Barcelona’s dead balls and who finishes them this season. 71 corners taken, most by Dani Olmo (21); 34 shots from corners and free kicks, 3 goals, led by Rodri (1 goals, 0.71 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
Raphinha2012 (60%)710.2053/3
Dani Olmo219 (43%)3—0.082—
Lamine Yamal102 (20%)4—0.1331/2
Fermín López149 (64%)2—0.05——
Rodri——410.71——
Andreas Christensen——3—0.50——
Karim Adeyemi——3—0.74——
João Cancelo43 (75%)1—0.02——
Gerard Martín——2—0.20——
Pedri20 (0%)1—0.02——
Eric García——1—0.03——
Pau Cubarsí——1—0.07——
Gavi——1—0.03——
Jules Koundé——110.62——

Top Performers

Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 270 minutes). Coloured chips are that player's strongest capability blocks.

playerposminVision AI Scorecapability blocks
PedriCM7228.9Progression 94%Ball-Carrying 91%Successful Dribble 84%Chance Creation 65%
Lamine YamalW8588.5Box Threat 95%Ball-Carrying 90%Chance Creation 70%Wide Delivery 45%
RaphinhaST6718.0Box Threat 93%Finishing 90%Ball-Carrying 88%Aerial Threat 0%
Fermín LópezAM6307.8Box Threat 92%Ball-Carrying 62%Chance Creation 38%
Pau CubarsíCB6307.8Ball-Carrying 96%Progression 70%Ball-Winning 54%Aerial & Box Defending 20%
Eric GarcíaCB6267.7Progression 96%Ball-Winning 68%Ball-Carrying 58%Aerial & Box Defending 3%
Gerard MartínCB6916.7Ball-Carrying 97%Progression 76%Aerial & Box Defending 48%Ball-Winning 47%
Xavi EspartCB6696.6Ball-Winning 79%Progression 59%Ball-Carrying 16%Aerial & Box Defending 4%
RodriCM6355.8Progression 84%Ball-Carrying 60%Chance Creation 60%Successful Dribble 26%
Joan GarcíaGK8005.7Shot-Stopping 57%

Top Creators

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

playerposminkey P /90box entriesxT
Lamine YamalF8583.153814.0
RaphinhaF6712.28225.3
Dani OlmoM3813.54228.0
Anthony GordonF5822.16205.4
PedriM7222.371312.9
Fermín LópezM6302.00187.2
Karim AdeyemiF3702.19123.0
Xavi EspartD6690.8178.0

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)
Lamine YamalW85828 (39%)14 (71%)
Karim AdeyemiW3704 (50%)14 (50%)
Anthony GordonW5823 (100%)10 (60%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Xavi EspartD669141261040
PedriM72212414161
RodriM635111171139
Gerard MartínD6911116817
Pau CubarsíD63010691020
Eric GarcíaD62610516533
Andreas ChristensenD424822719
Fermín LópezM6307410218

Full Squad Data

Every player with 100+ minutes (19 players).

playerposappsmingoalsxGkey PprogdefxT
Lamine YamalF1085886.230736914.0
Joan GarcíaG980000.004414.2
PedriM1072210.5194412412.9
Gerard MartínD969100.214211114.5
RaphinhaF9671137.01717375.3
Xavi EspartD866910.46371418.0
RodriM963510.893611112.5
Fermín LópezM963042.11426747.2
Pau CubarsíD763000.422810613.2
Eric GarcíaD862610.954910515.2
Anthony GordonF958212.41430425.4
Andreas ChristensenD642400.6114826.1
Dani OlmoM938111.01533408.0
Jules KoundéD637510.7435587.7
Karim AdeyemiF1037023.0916423.0
Marc BernalM833600.3710693.9
João CanceloD732810.2527516.6
Gabriel JesusF622130.921250.5
GaviM415200.128322.0

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.

Lamine Yamal
Creative forward · Forward
minutes858
goals · xG8 · 6.2
prog passes /907.7
key passes /903.15
def actions /907.2
pass accuracy76%
Joan García
Goalkeeper · Goalkeeper
minutes800
goals · xG0 · 0.0
prog passes /900.5
key passes /900.00
def actions /904.6
pass accuracy91%
Pedri
Ball-winner / destroyer · Midfielder
minutes722
goals · xG1 · 0.5
prog passes /905.5
key passes /902.37
def actions /9015.5
pass accuracy91%
Gerard Martín
Ball-playing defender · Defender
minutes691
goals · xG0 · 0.2
prog passes /905.5
key passes /900.13
def actions /9014.5
pass accuracy92%
Raphinha
Creative forward · Forward
minutes671
goals · xG13 · 7.0
prog passes /902.3
key passes /902.28
def actions /905.0
pass accuracy80%
Xavi Espart
Ball-playing defender · Defender
minutes669
goals · xG1 · 0.4
prog passes /905.0
key passes /900.81
def actions /9019.0
pass accuracy89%
Rodri
Ball-winner / destroyer · Midfielder
minutes635
goals · xG1 · 0.8
prog passes /905.1
key passes /901.28
def actions /9015.7
pass accuracy94%
Fermín López
Advanced creator · Attacking mid
minutes630
goals · xG4 · 2.1
prog passes /903.7
key passes /902.00
def actions /9010.6
pass accuracy82%
Pau Cubarsí
Stopper / marker · Defender
minutes630
goals · xG0 · 0.4
prog passes /904.0
key passes /900.29
def actions /9015.1
pass accuracy95%
Vision AI · building report