Combining every season — this one is larger, give it a moment.
Team reportLa Liga 2026
Villarreal
A possession-dominant side, aggressive high-press out of possession, with a high-volume attack. Currently #10 of 20 on 12 points (3-3-4, 15:14). Tactical profile below is built from 10 matches of ball-by-ball event data, contextualised against the league.
In one read, what kind of team is Villarreal and how good was the season?
Read. Villarreal currently sit #10 of 20 on 12 points (3W-3D-4L, 1.20 pts/game), scoring 15 and conceding 14 for a goal difference of +1.
On the ball they are a possession-dominant team (64% field tilt, #2 in the league); off it they defend with a aggressive high-press (#3 of 20 for press intensity).
Across the 10 matches of event data, they create 1.86 xG/game (#3) and concede 1.10 (#5), a net of +0.76 xG/game — the underlying performance matches the actual goal difference.
Season Context — the league table
The question
Where did Villarreal actually finish, and against whom?
The authoritative final table (full season), centred on Villarreal.
#
team
P
W
D
L
GF
GA
GD
Pts
7
Alaves
10
3
3
4
14
11
+3
12
8
Athletic Club
9
3
3
3
12
9
+3
12
9
Celta Vigo
10
2
6
2
10
7
+3
12
10
Villarreal
10
3
3
4
15
14
+1
12
11
Deportivo
10
2
5
3
13
13
+0
11
12
Osasuna
9
3
2
4
10
18
-8
11
13
Racing Santander
10
3
2
5
15
26
-11
11
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Villarreal actually dominate for chances — and which periods hurt them?
Net xG (created minus conceded) in each 15-minute window, summed across the whole season's matches — above the line is time they dominate for chances, below is time it hurts them. Real on-clock shot timing.
dominant (net xG for)conceding (net xG against)
Vision AI Model Insight
Villarreal tend to come alive after the break — first-half net xG +2.25, second-half +5.36. Their strongest period is 76-90+' (net +2.27 xG); their most dangerous period to face is 16-30' (net -0.00 xG against them).
xG Race — the season, match by match
Expected goals piling up over 10 matches: Villarreal 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 (+7.6 xG). Hover a point for that match.
VillarrealOpponents against Villarreal
Tactical DNA
The football question
In five genes, what is Villarreal'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.
88
Build-Up
possession control from the back
90
Progression
moving the ball upfield with threat
87
Creation
manufacturing chances
88
Press
winning the ball high & hard
75
Solidity
resisting the opponent's threat
Genetic identity
Villarreal are defined most by their Progression DNA (90/100 · elite at moving the ball upfield with threat), and least by their Solidity DNA (75/100). 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).
Possess
Deep buildup
78%
Possession
39%
Field tilt
39%
Disrupt
Central progression ~proxy
43%
Dribble tendency
78%
Progressive passes
35%
Finish
Final-third patience
43%
Shot quality
96%
Open-play xG
87%
Press
Forward press ~proxy
9%
High regains
43%
Pressing efficiency ~proxy
13%
Defend
Def-mid press ~proxy
9%
High line ~proxy
4%
PAdj defensive actions
13%
Villarreal is defined most by Finish (75% in the league) and weakest on Defend (9%). 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.
How much of the pitch does Villarreal actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Villarreal'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; Villarreal highlighted. Hover any dot for the team.
Vision AI Model Insight
Villarreal post 64% field tilt, ranking #2 of 20 in the league — a genuinely territory-dominant side, and their 1.20 points/game sits below the league-average return — a real disconnect: their territorial control isn't showing up on the scoreboard the way it should.
Where the time goes — how long each phase lasts
The question
When Villarreal has the ball, how much of that time is spent building, progressing and creating?
The share of Villarreal's time on the ball spent in each phase of play, in the order the phases happen. A phase is where the ball is on the pitch (own third, middle third, final third); a transition or a set piece skips the build-up and is counted on its own.
Phase
Share of the time
Build-up
22.1%
Progression
45.9%
Chance creation
29.2%
Attacking transition
2.8%
Vision AI Model Insight
Progression is where Villarreal spends most of its time on the ball (46% of its time on the ball).
Passing Network
The question
Who actually plays with whom — the real on-pitch connections, not just average positions?
Every pass linked to its likely receiver (the next same-team touch), aggregated into player-pair combinations at each player's average position. Line width = how often the pair combines; colour = threat generated per pass (blue low → red high). Hover a line for the pair, or click a player to isolate their connections.
width = passes between the paircolour = xT per pass: low → high
Top 10 combinations
Veiga ↔ Cardona
130p · -0.7xT
Gueye ↔ Veiga
126p · 0.2xT
Veiga ↔ Romero
82p · -0.1xT
Gulácsi ↔ Veiga
80p · 0.3xT
Akhomach ↔ Freeman
66p · 1.3xT
Veiga ↔ Freeman
64p · -0.0xT
Comesaña ↔ Veiga
61p · 0.1xT
Cardona ↔ Moleiro
55p · 1.2xT
Gueye ↔ Moleiro
51p · 1.2xT
Gueye ↔ Freeman
51p · 0.8xT
Vision AI Model Insight
Busiest connection: Renato Veiga ↔ Sergi Cardona (130 passes). Most dangerous per pass: Pape Gueye ↔ Alberto Moleiro (0.02 xT/pass over 51 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Villarreal 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 Villarreal 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
6090
ACTIONS
Carries
the ball moved with a player
1486
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the middle third (13.5% 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: 24% defensive, 49% 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. Villarreal leaned on their right (41%). The bars under the pitch put the league’s share beside theirs.
Villarreal
34%25%41%
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. Villarreal made 644 this season (64.4 a match); 29% came into the right wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.
Channel
Entries
Per match
Share
League share
Left wing
167
16.7
26%
29%
Left half-space
93
9.3
14%
15%
Centre
88
8.8
14%
12%
Right half-space
109
10.9
17%
15%
Right wing
187
18.7
29%
29%
Build-up2 sections
Build-Up — the pass map
The football question
How does Villarreal 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.
1477build-up passes attempted
89%completed
26%reach the middle third
1%go long into the final third
Pass types
652CB · 49%
50Long Wide · 4%
11Long Central · 1%
448Wide → FB · 34%
160Central · 12%
Sequence success — build-up
125build-up sequences this season
18%succeed — reach the next third or a shot
30%turned over with nothing to show
CB652 · 49%
Long Wide50 · 4%
Long Central11 · 1%
Wide → FB448 · 34%
Central160 · 12%
◆ Vision AI Insight
Villarreal build predominantly down the left, with Veiga as the fulcrum (293 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 → LHS def (112×).
Pass Explorer
Every pass of Villarreal’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.
From channel
To channel
From third
To third
Outcome
Minutes
Channel to channel · click a cell
Third to third · click a cell
Progression4 sections
How They Progress — the mechanism
Not just how many progressive passes, but where they start, who plays them, and whether they actually penetrate. 573 progressive passes across 10 matches (57.3/game).
Origin lane
Right wing
29%
Right half-space
19%
Central
13%
Left half-space
15%
Left wing
24%
Progression is right-dominant: 48% right side · 13% central · 38% left.
Who generates it
Alex Freeman
63 · 11%
Alberto Moleiro
58 · 10%
Renato Veiga
48 · 8%
Pape Gueye
46 · 8%
Sergi Cardona
39 · 7%
Top two — Alex Freeman & Alberto Moleiro — account for 21% of all progression.
PROGRESSION
57.3 prog passes/game
mostly right
→
PENETRATION
28% reach final third
22% reach the box
→
THREAT
the other 72% is recycled
progress ≠ danger
What came of it.28% of progressive passes reached the final third and 22% the box; the rest was recycled in front of the block. 21% 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 Villarreal 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.
2989progression passes attempted
91%completed
19%break into the final third
9%go backward into the defensive third
Pass types
969CB · 36%
92Long Wide · 3%
17Long Central · 1%
1224Wide → FB · 45%
417Central · 15%
Sequence success — progression
174progression sequences this season
40%succeed — reach the next third or a shot
28%turned over with nothing to show
CB969 · 36%
Long Wide92 · 3%
Long Central17 · 1%
Wide → FB1224 · 45%
Central417 · 15%
◆ Vision AI Insight
Villarreal progress predominantly down the right, with Veiga the busiest midfield outlet (378 progression passes). Only 19% of passes that start in midfield actually break the final-third line — the rest (72%) 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 (169×) — 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)
15%
Progressive
2%
Neutral / sideways
46%
Safe / backward
37%
17% of passes are progressive-or-better; the remaining 83% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Villarreal actually progress the ball with their feet, not a pass?
334 progressive carries this season across the whole squad (22% of 1486 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: Veiga (47). Filter to one player below.
First (104)Second (95)Third (83)Fourth (52)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 Villarreal'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.
166shots
18.6xG
0.11xG per shot
13big chances (0.3+ xG)
14goals
#4key passes / game in the league
#1box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition19% of shots
32
7
3.98
0.12
Cut-back
3
1
0.50
0.17
Long ball
4
1
0.51
0.13
Pass into the box / short pass
19
5
2.30
0.12
Own creation (carry, dribble, rebound)
6
0
0.68
0.11
Settled attack58% of shots
96
3
9.86
0.10
Cross
11
0
1.09
0.10
Cut-back
17
2
2.29
0.13
Long ball
5
0
0.25
0.05
Pass into the box / short pass
46
1
4.48
0.10
Own creation (carry, dribble, rebound)
17
0
1.75
0.10
Set piece23% of shots
38
4
4.80
0.13
Corner
31
1
2.32
0.07
Free kick
4
0
0.10
0.02
Penalty
3
3
2.38
0.79
Every attempt to create — and what came of it
Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.
Who sets the shots up
Player
Set-ups
xG created
Goals
Alberto Moleiro
14
1.85
4
Ilias Akhomach
8
1.66
2
Sergi Cardona
5
1.04
1
Gerard Moreno
10
1.03
0
Georges Mikautadze
9
1.01
1
Who takes them
Player
Shots
xG
Goals
Georges Mikautadze
22
3.42
3
Ayoze Pérez
19
2.94
1
Alberto Moleiro
18
2.71
2
Gerard Moreno
11
2.23
2
Pape Gueye
16
1.77
3
Vision AI Model Insight
The biggest source of Villarreal's chances, by xG, is settled attack (9.9 of 18.6 xG, 96 of 166 shots), mostly pass into the box / short pass. 32 of the 166 shots (19%) came within 15 seconds of winning the ball. 38 of the 166 shots came from set pieces; 14 goals from 18.6 xG (-4.6).
Chance Creation — the pass map
The football question
How does Villarreal 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
6CB · 5%
10Long Wide · 8%
4Long Central · 3%
44Wide → FB · 36%
59Central · 48%
Sequence success — final-third
211final-third sequences this season
21%succeed — produce a shot
34%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
CB6 · 5%
Long Wide10 · 8%
Long Central4 · 3%
Wide → FB44 · 36%
Central59 · 48%
Who creates — volume × threat
23Moleiro
12Buchanan
11Moreno
10Gueye
9Freeman
9Pérez
9Mikautadze
123key passes #4 of 20
20.3box entries/game #1 of 20
53.8final-3rd entries/game #2 of 20
1.86xG/game #3 of 20
14goals #7 of 20
-4.6finishing vs xG #20 of 20
◆ Vision AI Insight
Villarreal lean right — 50% of their key passes come from that flank and its half-space (61 of 123), most often from Moleiro (10). They funnel chances into the c of the final third, most often via RHS att → C att (18 key passes, most often from Akhomach). Moleiro is the primary source overall. They generate 1.86 xG a game and finish it wasteful — they under-perform their xG, led by Georges Mikautadze (3G), Pape Gueye (3G), Gerard Moreno (2G).
Crosses & Cutbacks — squad-wide
The question
How does Villarreal deliver into the box from wide areas, and what comes of it?
133 crosses: 64 found a team-mate (48%), 15 led to a shot (11%). 60 cut-backs: 30 found a team-mate (50%), 18 led to a shot (30%). 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 Villarreal actually cross from?
133 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; 14 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · right wing
31
23%
4
advanced · right wing
30
23%
4
advanced · left wing
28
21%
3
byline · left wing
21
16%
4
deep · left wing
5
4%
0
advanced · left half-space
5
4%
0
deep · right wing
4
3%
0
byline · right half-space
4
3%
0
advanced · right half-space
3
2%
0
deep · right half-space
1
1%
0
byline · left half-space
1
1%
0
Finishing3 sections
Shot Map
166 shots for 18.6 xG (1.86/game, #3 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
High-volume attack. 16.6 shots/game at 0.112 xG/shot. Box entries 20/game (#1). Threat created 14.3 xT/game (#3).
Goal Sequences
The move behind each of Villarreal’s 15 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 — 15 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Villarreal scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
10 · 71%
Set pieces
1 · 7%
Penalties
3 · 21%
By finish
Right foot
3 · 21%
Left foot
10 · 71%
Header
1 · 7%
Vision AI Model Insight
14 goals scored. 71% come in open play; set pieces add 7%. Open play is clearly their main route to goal.
When they lose it1 section
Ball-Loss Map — where attacks die
Every turnover has a location and a cause. This is a rate, not a raw count — the share of pass attempts from each zone that end in a turnover, so a zone they simply play through more often doesn't automatically look riskier. Grey cells are real zones with too few attempts to trust a rate.
Loss rate by zone
How they lose it
Incomplete pass — attacking third
359
Failed forward pass
245
Failed take-on
151
Lost in the defensive third
156
Their weakest zone is the right half-space in the attacking third: 30% of 350 pass attempts there are lost (106 times). Separately, 46% of all losses happen in the attacking third — a fair share happen deeper, which invites transitions.
Out of possession
Out of possession
How they press, where they win the ball back, and how they concede.
How hard does Villarreal 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.
73
Pressing Index /100 · strong
Intensity73
PPDA, high-press share, high-zone actions
Height70
how high up the pitch they defend
Effectiveness80
high recoveries & high-regain share
Disruption65
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
20%
RHS
24%
C
23%
LHS
18%
LW
16%
By third (high / mid / low regain)
Def 45%
Mid 39%
Att 16%
Read
Ranked #3 of 20 for press intensity, this is a high press. 55% of defensive actions happen in the middle & attacking thirds, at an average height of 39. Of recoveries, 57% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#3/20
lower = more intense; rank is what matters
Defensive actions / game
143
#16/20
High-press share
24%
#5/20
def actions won high up
Defensive-action height (0–100)
39.6
#6/20
avg pitch height of actions
High recoveries / game
24.6
#4/20
ball won in mid+att third
High-recovery share
57%
#4/20
share of recoveries won high
Opponent completion allowed
80%
#3/20
lower = more disruptive
Opponent progressive allowed
9.2%
#11/20
of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.
How long they keep it — passes and seconds until the ball is won
The question
Once the opponent has the ball, how many passes and how many seconds pass before Villarreal win it back with a defensive action?
Counted over the 324 opposition possessions that Villarreal 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 Villarreal step in. Villarreal win it after 4.4 opponent passes in the first half-hour and after 4.7 after the hour mark (about the same).
PASSES THEY GET
4.4passes
median 3 · before Villarreal win it
TIME THEY KEEP IT
13sec
median 7s · 32.4 wins per game
How many passes the opponent got in before the ball was won
45%
29%
16%
10%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
3.7
10s
15–30′
5.1
16s
30–45+′
4.3
15s
45–60′
3.8
11s
60–75′
4.7
13s
75–90+′
4.7
13s
average passesaverage seconds
Attitude in each third
Every other style number here says how much Villarreal 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 Villarreal 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) 1,477 passes
shorter passing, safer, kept on the floor
Width of use-0.5619.85
Wide-channel share-1.090.24
Side bias-0.34-1.13
Pass length-1.1918.42
Long-ball share-1.110.12
Forward gain per pass-0.907.55
Backward-pass share-0.290.19
Deep-pass share-0.980.19
Completion+1.180.89
Seconds between passes-0.872.80
Side used
left 26% · central 46% · right 28%
Progression (middle third) 2,989 passes
played inside, narrow, central, safer
Width of use-1.4522.49
Wide-channel share-1.510.30
Side bias-0.13-0.46
Pass length-0.2716.85
Long-ball share-0.600.08
Forward gain per pass+0.023.64
Backward-pass share-0.470.31
Deep-pass share-0.380.14
Completion+1.040.91
Seconds between passes-0.443.00
Side used
left 31% · central 36% · right 33%
Final third 1,624 passes
safer, narrow, central, played inside
Width of use-0.9829.19
Wide-channel share-0.940.51
Side bias-0.35-2.91
Pass length-0.7614.30
Long-ball share-0.800.06
Forward gain per pass-0.730.06
Backward-pass share+0.760.44
Deep-pass share-0.600.07
Completion+1.020.78
Seconds between passes+0.003.40
Side used
left 36% · central 19% · right 45%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Villarreal'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 Villarreal 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 share17%
#14 of 20 · reaches final third in ≤3 passes
Patient build-up share30%
#8 of 20 · spells of 6+ passes
Tempo (possession length)18.9s
#12 of 20 · shorter = faster tempo
Passes per possession4.8
#9 of 20
Counter-attack shots /game1.38
#3 of 20 · shot within 12s of a regain in own half
Press→shot /game2.65
#16 of 20 · shot within 8s of a high regain
Speed to final third after regain13.1s
#13 of 20 · lower = faster break
Sequence success — attacking transition
15attacking transition sequences this season
7%succeed — produce a shot
47%turned over with nothing to show
Sequence success — defensive transition
46defensive transition sequences this season
65%succeed — reach the next third or a shot
7%turned over with nothing to show
Vision AI Model Insight
Villarreal are a patient build-up side: 17% of possessions reach the final third in 3 passes or fewer (#14 of 20), against 30% built patiently over 6+ passes (#8 of 20). Winning the ball back leads to a shot inside 12 seconds 1.38 times a game (#3), and a high regain converts to a shot within 8 seconds 2.65 times a game (#16 of 20) — not yet a major source of chances.
Defending the box2 sections
Vulnerability Map — how opponents hurt them
The report flipped: where do opponents create their threat against Villarreal? 374 opponent progressive passes and 117 shots faced (11.0 xG against) across the season.
Opponent threat by lane (attacking into Villarreal)
Right wing
34%
Right half-space
10%
Central
18%
Left half-space
15%
Left wing
22%
Where the danger came from. Opponents generated most of their threat through the right wing (34% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Villarreal actually come from — open play, dead balls, and who supplies them?
Every goal Villarreal conceded across the loaded matches — the opponent's shots in Villarreal's own matches — plus every individual opponent key pass faced, each drawn as its own real arrow (not zone-clustered) with the % share of each zone behind it.
Where the goals go in
Every opponent key pass against them (77 total)
By situation
Open play
11 · 79%
Set pieces
1 · 7%
Penalties
2 · 14%
Vision AI Model Insight
14 goals conceded. 79% come in open play; set pieces account for only 7%, so dead-ball defending is not the main issue. 0% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre of the attacking third (19% of key passes faced) — that is the zone to shut off.
Context
Shape and tactics
Set pieces, strengths and weaknesses, and who they resemble.
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.
Open play
10 g · 13.8 xG
Set pieces
1 g · 2.4 xG
Penalties
3 g
7% of goals come from set pieces (1 of 14), worth 2.4 xG from 35 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Villarreal's corners go?
73 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 (41)
Delivered into the box 100%Short 0%
Left side (32)
Delivered into the box 91%Short 9%
Where opponents attack Villarreal from set pieces
22 shots from opponent corners against Villarreal, 1 conceded, split by the flag the corner came from — arrows from the flag, dots where the shot was taken (gold = goal), shaded by the % of that flag's shots in each zone. Tap or hover a shot for who took it, the minute and the match; filter to one match and the shading recomputes for just that game.
Right flag (11)
Shot 11Goals 0
Left flag (11)
Shot 11Goals 1
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
progression /game — 57.30 (95th pct)
box entries /game — 20.30 (95th pct)
field tilt % — 64.08 (90th pct)
xG created /game — 1.86 (85th pct)
press intensity (PPDA) — 4.74 (85th 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.
Atletico
98%
Barcelona
90%
Real Madrid
78%
Athletic Club
76%
Real Betis
28%
Performance vs Opponent Styles
The question
Not just how Villarreal 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 Villarreal's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (3m)
1.33
1.67
0.67
vs mid-block opponents (3m)
1.67
1.00
2.00
vs low-block opponents (4m)
1.50
1.50
1.00
Behaviour — how Villarreal actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
88%
8%
47
12.1
18.7
vs mid-block opponents
86%
9%
51
14.3
22.7
vs low-block opponents
87%
8%
70
15.9
19.8
Vision AI Model Insight
Facing a high press, retention drops to 88% vs 87% against a low block (0pt higher under pressure), and directness (long-ball share) sits at 8% 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. Villarreal are possession-dominant with a aggressive high-press.
Their attack creates 1.86 xG a game and they concede 1.10 a game.
[Event-data based — no tracking, so off-ball structure and marking scheme need video.]
For each of ten match numbers, the one match this season that departed furthest from Villarreal’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.
Villarreal
across 10 matches this season
PPDAat Real Madrid · 0-1 · 2026-10-109.0avg 4.7
Defensive actionsat Racing Santander · 2-2 · 2026-08-16173avg 143
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 Villarreal’s last 10 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).
+20.7on-ball value, 10 matches
Where the value came from
Passes6090 actions+7.53
Carries1486 actions+2.01
Dribbles256 actions+0.26
Shots166 actions+7.73
Ball wins603 actions+3.17
Most on-ball value (OBV)
Actions
OBV
per 100
Georges Mikautadze
282
+2.49
+0.88
Pape Gueye
736
+1.85
+0.25
Gerard Moreno
312
+1.76
+0.56
Renato Veiga
1047
+1.61
+0.15
Ayoze Pérez
238
+1.53
+0.64
Alberto Moleiro
504
+1.44
+0.29
Ilias Akhomach
304
+1.34
+0.44
Juan Foyth
549
+1.25
+0.23
Biggest single moves
OBV
1 Georges Mikautadze · shot
+0.849
2 Gerard Moreno · shot
+0.797
3 Pape Gueye · shot
+0.565
4 Ilias Akhomach · pass
+0.486
5 Alberto Moleiro · carry
+0.404
6 Renato Veiga · pass
+0.393
Set Pieces by Player
Who delivers Villarreal’s dead balls and who finishes them this season. 73 corners taken, most by Alberto Moleiro (37); 35 shots from corners and free kicks, 1 goals, led by Gerard Moreno (1 goals, 0.69 xG). “Into the box” counts corners that landed inside the penalty area; free-kick takers are the players who shot from one, because this feed does not mark who delivers the others.
Player
Corners taken
Into the box
Set-piece shots
Goals
xG
Free-kick shots
Penalties
Alberto Moleiro
37
25 (68%)
1
—
0.02
1
—
Ilias Akhomach
13
11 (85%)
2
—
0.08
—
—
Tajon Buchanan
13
6 (46%)
1
—
0.02
—
—
Gerard Moreno
—
—
4
1
0.69
—
1/1
Ayoze Pérez
—
—
5
—
0.28
1
—
Georges Mikautadze
2
0 (0%)
3
—
0.24
1
1/1
Logan Costa
—
—
4
—
0.22
—
—
Nicolas Pepe
8
6 (75%)
1
—
0.02
1
—
Renato Veiga
—
—
3
—
0.19
—
—
Pape Gueye
—
—
2
—
0.09
—
1/1
Juan Foyth
—
—
2
—
0.19
—
—
Nathan Saliba
—
—
2
—
0.06
—
—
Santiago Mouriño
—
—
1
—
0.11
—
—
Alex Freeman
—
—
1
—
0.02
—
—
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.