Combining every season — this one is larger, give it a moment.
Team reportLa Liga 2025/26
Villarreal
A balanced-territory side, aggressive high-press out of possession, with a high-volume attack. Finished #4 of 23 on 84 points (25-9-14, 87:60). Tactical profile below is built from 48 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 finished #4 of 23 on 84 points (25W-9D-14L, 1.75 pts/game), scoring 87 and conceding 60 for a goal difference of +27.
On the ball they are a balanced-territory team (47% field tilt, #13 in the league); off it they defend with a aggressive high-press (#21 of 23 for press intensity).
Across the 48 matches of event data, they create 1.58 xG/game (#3) and concede 1.20 (#8), a net of +0.38 xG/game — the underlying performance diverges from 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
1
Barcelona
48
40
1
7
135
47
+88
121
2
Real Madrid
48
35
5
8
102
45
+57
110
3
Atletico
48
29
7
12
82
52
+30
94
4
Villarreal
48
25
9
14
87
60
+27
84
5
Real Betis
48
21
17
10
75
62
+13
80
6
Celta Vigo
48
16
18
14
63
55
+8
66
7
Real Sociedad
48
17
14
17
78
79
-1
65
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 fade after a strong start — first-half net xG +10.73, second-half +7.51. Their strongest period is 0-15' (net +4.99 xG); their most dangerous period to face is 76-90+' (net -0.60 xG against them).
xG Race — the season, match by match
Expected goals piling up over 48 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 (+18.2 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.
52
Build-Up
possession control from the back
46
Progression
moving the ball upfield with threat
80
Creation
manufacturing chances
26
Press
winning the ball high & hard
65
Solidity
resisting the opponent's threat
Genetic identity
Villarreal are defined most by their Creation DNA (80/100 · strong at manufacturing chances), and least by their Press DNA (26/100). Percentiles vs the 23 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
43%
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 47% field tilt, ranking #13 of 23 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 1.75 points/game sits above 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
30.2%
Progression
44.8%
Chance creation
21.9%
Attacking transition
3.1%
Vision AI Model Insight
Progression is where Villarreal spends most of its time on the ball (45% 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
Pépé ↔ Mouriño
266p · 17.5xT
Comesaña ↔ Mouriño
254p · 8.4xT
Veiga ↔ Cardona
247p · 11.9xT
Júnior ↔ Veiga
210p · 8.2xT
Pépé ↔ Comesaña
203p · 10.5xT
Parejo ↔ Veiga
176p · 6.5xT
Gueye ↔ Mouriño
173p · 5.4xT
Gueye ↔ Veiga
169p · 7.1xT
Pépé ↔ Gueye
165p · 11.4xT
Buchanan ↔ Mouriño
160p · 11.1xT
Vision AI Model Insight
Busiest connection: Nicolas Pépé ↔ Santiago Mouriño (266 passes). Most dangerous per pass: Renato Veiga ↔ Alberto Moleiro (0.07 xT/pass over 122 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 479 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
23007
ACTIONS
Carries
the ball moved with a player
6114
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the middle third (12.6% of all actions). 65% of actions run through the inside lanes (centre + both half-spaces) versus 35% down the two wings — an inside-dominant, half-space build. By third: 30% defensive, 47% 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. Villarreal leaned on their right (40%). The bars under the pitch put the league’s share beside theirs.
Villarreal
35%25%40%
League
39%22%38%
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 2070 this season (43.1 a match); 28% 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
499
10.4
24%
30%
Left half-space
325
6.8
16%
15%
Centre
308
6.4
15%
12%
Right half-space
358
7.5
17%
14%
Right wing
580
12.1
28%
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.
7178build-up passes attempted
83%completed
26%reach the middle third
1%go long into the final third
Pass types
3006CB · 50%
287Long Wide · 5%
51Long Central · 1%
1887Wide → FB · 32%
734Central · 12%
Sequence success — build-up
1311build-up sequences this season
11%succeed — reach the next third or a shot
41%turned over with nothing to show
CB3006 · 50%
Long Wide287 · 5%
Long Central51 · 1%
Wide → FB1887 · 32%
Central734 · 12%
◆ Vision AI Insight
Villarreal build predominantly down the right, with Veiga as the fulcrum (996 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 (444×).
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. 2025 progressive passes across 48 matches (42.2/game).
Origin lane
Right wing
28%
Right half-space
16%
Central
17%
Left half-space
15%
Left wing
25%
Progression is right-dominant: 44% right side · 17% central · 40% left.
Who generates it
Sergi Cardona
189 · 9%
Santiago Mouriño
154 · 8%
Santi Comesaña
154 · 8%
Pape Gueye
138 · 7%
Alberto Moleiro
138 · 7%
Top two — Sergi Cardona & Santiago Mouriño — account for 17% of all progression.
PROGRESSION
42.2 prog passes/game
mostly right
→
PENETRATION
26% reach final third
21% reach the box
→
THREAT
the other 74% is recycled
progress ≠ danger
What came of it.26% of progressive passes reached the final third and 21% the box; the rest was recycled in front of the block. 17% 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.
10613progression passes attempted
87%completed
17%break into the final third
10%go backward into the defensive third
Pass types
3441CB · 37%
344Long Wide · 4%
50Long Central · 1%
4018Wide → FB · 43%
1422Central · 15%
Sequence success — progression
1681progression sequences this season
27%succeed — reach the next third or a shot
39%turned over with nothing to show
CB3441 · 37%
Long Wide344 · 4%
Long Central50 · 1%
Wide → FB4018 · 43%
Central1422 · 15%
◆ Vision AI Insight
Villarreal progress predominantly down the right, with Veiga the busiest midfield outlet (1003 progression passes). Only 17% of passes that start in midfield actually break the final-third line — the rest (73%) is recycled back into midfield or (10%) 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 (541×) — 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)
14%
Progressive
1%
Neutral / sideways
49%
Safe / backward
35%
15% of passes are progressive-or-better; the remaining 85% 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?
1315 progressive carries this season across the whole squad (25% of 5287 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 15m, longest 66m. Most active carrier: Veiga (158). Filter to one player below.
First (394)Second (380)Third (276)Fourth (265)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.
621shots
75.6xG
0.12xG per shot
56big chances (0.3+ xG)
85goals
#7key passes / game in the league
#4box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition23% of shots
141
27
18.83
0.13
Cross
8
0
1.04
0.13
Cut-back
5
1
0.70
0.14
Long ball
10
4
1.35
0.14
Pass into the box / short pass
90
15
12.04
0.13
Own creation (carry, dribble, rebound)
28
7
3.70
0.13
Settled attack61% of shots
377
41
42.23
0.11
Cross
48
2
4.93
0.10
Cut-back
44
8
6.78
0.15
Long ball
18
2
1.22
0.07
Pass into the box / short pass
178
20
19.77
0.11
Own creation (carry, dribble, rebound)
89
9
9.53
0.11
Set piece17% of shots
103
17
14.58
0.14
Corner
84
7
6.42
0.08
Free kick
9
0
0.22
0.02
Penalty
10
10
7.94
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
Nicolas Pépé
52
6.62
7
Alberto Moleiro
47
6.52
9
Georges Mikautadze
32
3.84
6
Pape Gueye
33
3.62
4
Sergi Cardona
24
3.61
6
Who takes them
Player
Shots
xG
Goals
Georges Mikautadze
87
14.31
16
Gerard Moreno
50
8.34
12
Nicolas Pépé
63
7.93
8
Alberto Moleiro
64
7.15
12
Ayoze Pérez
43
7.12
6
Vision AI Model Insight
The biggest source of Villarreal's chances, by xG, is settled attack (42.2 of 75.6 xG, 377 of 621 shots), mostly pass into the box / short pass. 141 of the 621 shots (23%) came within 15 seconds of winning the ball. 103 of the 621 shots came from set pieces; 85 goals from 75.6 xG (+9.4).
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
27CB · 6%
26Long Wide · 6%
19Long Central · 4%
155Wide → FB · 35%
220Central · 49%
Sequence success — final-third
1165final-third sequences this season
22%succeed — produce a shot
37%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
CB27 · 6%
Long Wide26 · 6%
Long Central19 · 4%
Wide → FB155 · 35%
Central220 · 49%
Who creates — volume × threat
56Moleiro
54Pépé
34Mikautadze
33Moreno
32Gueye
28Comesaña
26Buchanan
447key passes #7 of 23
13.8box entries/game #4 of 23
34.1final-3rd entries/game #8 of 23
1.58xG/game #3 of 23
85goals #3 of 23
+9.4finishing vs xG #5 of 23
◆ Vision AI Insight
Villarreal lean right — 40% of their key passes come from that flank and its half-space (181 of 447), most often from Pépé (39). They funnel chances into the c of the final third, most often via RHS att → C att (59 key passes, most often from Pépé). Moleiro is the primary source overall. They generate 1.58 xG a game and finish it clinical — they beat their xG, led by Georges Mikautadze (16G), Gerard Moreno (12G), Alberto Moleiro (12G).
Crosses & Cutbacks — squad-wide
The question
How does Villarreal deliver into the box from wide areas, and what comes of it?
556 crosses: 213 found a team-mate (38%), 62 led to a shot (11%). 175 cut-backs: 82 found a team-mate (47%), 47 led to a shot (27%). 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?
556 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. 26% come from one territory, the byline left wing; 41 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · left wing
147
26%
23
byline · right wing
123
22%
11
advanced · left wing
104
19%
11
advanced · right wing
93
17%
11
deep · right wing
26
5%
1
deep · left wing
22
4%
1
byline · right half-space
15
3%
3
advanced · left half-space
11
2%
0
advanced · right half-space
7
1%
0
byline · left half-space
5
1%
0
deep · right half-space
2
0%
0
deep · left half-space
1
0%
1
Finishing3 sections
Shot Map
621 shots for 75.6 xG (1.58/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. 12.9 shots/game at 0.122 xG/shot. Box entries 14/game (#4). Threat created 10.7 xT/game (#10).
Goal Sequences
The move behind each of Villarreal’s 87 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 — 87 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
68 · 80%
Set pieces
7 · 8%
Penalties
10 · 12%
By finish
Right foot
38 · 45%
Left foot
40 · 47%
Header
6 · 7%
Other
1 · 1%
Vision AI Model Insight
85 goals scored. 80% come in open play; set pieces add 8%. Open play is clearly their main route to goal.
When they lose it1 section
Ball-Loss Map — where attacks die
Every turnover has a location and a cause. This is a rate, not a raw count — the share of pass attempts from each zone that end in a turnover, so a zone they simply play through more often doesn't automatically look riskier. Grey cells are real zones with too few attempts to trust a rate.
Loss rate by zone
How they lose it
Incomplete pass — attacking third
1332
Failed forward pass
909
Failed take-on
602
Lost in the defensive third
1213
Their weakest zone is the right half-space in the attacking third: 31% of 1031 pass attempts there are lost (324 times). Separately, 34% 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.
22
Pressing Index /100 · passive
Intensity12
PPDA, high-press share, high-zone actions
Height4
how high up the pitch they defend
Effectiveness24
high recoveries & high-regain share
Disruption54
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
22%
RHS
22%
C
21%
LHS
19%
LW
16%
By third (high / mid / low regain)
Def 56%
Mid 33%
Att 12%
Read
Ranked #21 of 23 for press intensity, this is a high press. Note the tension: 56% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (17% high-press share) means that when they do defend, it is often deep. Of recoveries, 49% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#21/23
lower = more intense; rank is what matters
Defensive actions / game
133
#18/23
High-press share
17%
#20/23
def actions won high up
Defensive-action height (0–100)
34.5
#22/23
avg pitch height of actions
High recoveries / game
19.8
#15/23
ball won in mid+att third
High-recovery share
49%
#20/23
share of recoveries won high
Opponent completion allowed
83%
#19/23
lower = more disruptive
Opponent progressive allowed
8.2%
#2/23
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 1514 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 6.0 opponent passes in the first half-hour and after 4.7 after the hour mark (sooner).
PASSES THEY GET
5.4passes
median 3 · before Villarreal win it
TIME THEY KEEP IT
16sec
median 8s · 31.5 wins per game
How many passes the opponent got in before the ball was won
40%
27%
16%
17%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.2
18s
15–30′
5.8
18s
30–45+′
5.8
18s
45–60′
5.1
15s
60–75′
4.2
13s
75–90+′
5.1
15s
average passesaverage seconds
Phases of play
Every moment of the match read twice — what Villarreal were doing with the
ball, and what the opposition were doing about it at that exact moment. Built from the
real action sequence in time order, so one possession is split across the phases it
genuinely passed through rather than labelled once by where it began.
6,502phase segments analysed
9.0smedian time before the opposition engage
2.0their passes per defensive action when pressed
#20of 20 for share of defending spent pressing high
High press 4.9%Mid block 12.4%Low block 56.4%Unopposed 26.2%
What opponents do against Villarreal
The mirror image, and the part no other section can show: whether teams come
out to press Villarreal or sit in and invite them on. A side that is always faced with a low
block is playing a different sport from one that is pressed every week.
High press 9.6%Mid block 14.2%Low block 44.2%Unopposed 32.0%
Which phases actually produce
Phase
Segments
Avg length
Avg actions
Ends in shot
Turned over
Build-up
2,201
5.2s
3.1
0.3%
51.2%
Progression
2,543
6.6s
3.9
0.3%
47.6%
Chance creation
1,600
5.2s
3.3
25.8%
55.4%
Attacking transition
158
7.4s
4.5
0.6%
36.1%
Most common routes through the phases
How a possession actually travelled, in order. The chain is the tactical signature — a move that climbs all three thirds is a different thing from one that never leaves the first.
Route
Times
Ends in shot
build_up
960
0.2%
progression
628
0.3%
chance_creation
371
32.6%
build_up → progression
370
0.3%
progression → chance_creation
293
27.0%
build_up → progression → chance_creation
265
32.5%
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) 7,178 passes
nothing unusual in this zone
Width of use-0.3320.31
Wide-channel share-0.500.27
Side bias-0.28-0.89
Pass length-0.6720.27
Long-ball share-0.560.17
Forward gain per pass-0.429.61
Backward-pass share-0.380.18
Deep-pass share-0.510.24
Completion+0.370.83
Seconds between passes-0.572.98
Side used
left 26% · central 46% · right 28%
Progression (middle third) 10,613 passes
played inside, narrow, central
Width of use-1.0023.45
Wide-channel share-1.000.33
Side bias-0.37-1.41
Pass length+0.1617.45
Long-ball share-0.030.10
Forward gain per pass+0.223.93
Backward-pass share-0.300.32
Deep-pass share+0.040.16
Completion+0.320.86
Seconds between passes-0.403.02
Side used
left 30% · central 35% · right 34%
Final third 5,216 passes
nothing unusual in this zone
Width of use-0.7129.87
Wide-channel share-0.770.52
Side bias-0.29-2.54
Pass length-0.2815.03
Long-ball share-0.310.09
Forward gain per pass-0.180.80
Backward-pass share+0.100.39
Deep-pass share-0.320.08
Completion+0.340.73
Seconds between passes-0.003.40
Side used
left 37% · central 19% · right 44%
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%
#16 of 23 · reaches final third in ≤3 passes
Patient build-up share30%
#9 of 23 · spells of 6+ passes
Tempo (possession length)18.9s
#14 of 23 · shorter = faster tempo
Passes per possession4.8
#10 of 23
Counter-attack shots /game1.38
#3 of 23 · shot within 12s of a regain in own half
Press→shot /game2.65
#16 of 23 · shot within 8s of a high regain
Speed to final third after regain13.1s
#15 of 23 · lower = faster break
Sequence success — attacking transition
164attacking transition sequences this season
20%succeed — produce a shot
43%turned over with nothing to show
Sequence success — defensive transition
394defensive transition sequences this season
64%succeed — reach the next third or a shot
9%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 (#16 of 23), against 30% built patiently over 6+ passes (#9 of 23). 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 23) — 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? 2084 opponent progressive passes and 603 shots faced (57.4 xG against) across the season.
Opponent threat by lane (attacking into Villarreal)
Right wing
34%
Right half-space
10%
Central
16%
Left half-space
12%
Left wing
27%
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 (396 total)
By situation
Open play
43 · 74%
Set pieces
6 · 10%
Penalties
9 · 16%
Vision AI Model Insight
58 goals conceded. 74% come in open play; set pieces account for only 10%, so dead-ball defending is not the main issue. 16% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right half-space of the attacking third (18% 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
68 g · 61.1 xG
Set pieces
7 g · 6.6 xG
Penalties
10 g
8% of goals come from set pieces (7 of 85), worth 6.6 xG from 93 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Villarreal's corners go?
232 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 (112)
Delivered into the box 98%Short 2%
Left side (120)
Delivered into the box 88%Short 12%
Where opponents attack Villarreal from set pieces
83 shots from opponent corners against Villarreal, 5 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 (38)
Shot 38Goals 2
Left flag (45)
Shot 45Goals 3
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
xG created /game — 1.58 (87th pct)
box entries /game — 13.79 (83th pct)
shots /game — 12.94 (70th pct)
xG conceded /game — 1.20 (65th pct)
Weaknesses (bottom-third vs league)
press intensity (PPDA) — 8.53 (9th pct)
progression /game — 42.19 (35th pct)
Style Archetype & Similar Teams
Team archetype: Direct / counter high-press. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.
Real Betis
87%
Celta Vigo
59%
Girona
57%
Real Madrid
39%
Atletico
24%
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 (16m)
1.69
1.50
1.88
vs mid-block opponents (16m)
1.06
1.19
1.19
vs low-block opponents (16m)
2.69
1.06
2.19
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
78%
15%
36
8.9
11.1
vs mid-block opponents
82%
12%
40
10.6
13.3
vs low-block opponents
86%
9%
50
12.5
17.0
Vision AI Model Insight
Facing a high press, retention drops to 78% vs 86% against a low block (8pt lower under pressure), and directness (long-ball share) sits at 15% when pressed vs 9% against a low block — a real style switch: they go noticeably more direct when pressed rather than trying to play through it.
Scouting Summary — the team in brief
In brief. Villarreal are balanced-territory with a aggressive high-press.
Their attack creates 1.58 xG a game and they concede 1.20 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.
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 12 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).
+24.8on-ball value, 12 matches
Where the value came from
Passes7071 actions+7.53
Carries1717 actions+2.34
Dribbles297 actions+0.80
Shots191 actions+10.40
Ball wins714 actions+3.69
Most on-ball value (OBV)
Actions
OBV
per 100
Georges Mikautadze
321
+3.12
+0.97
Ayoze Pérez
310
+2.46
+0.79
Gerard Moreno
337
+2.00
+0.59
Pape Gueye
856
+1.89
+0.22
Alberto Moleiro
628
+1.80
+0.29
Nicolas Pépé
465
+1.66
+0.36
Renato Veiga
1047
+1.61
+0.15
Ilias Akhomach
304
+1.34
+0.44
Biggest single moves
OBV
1 Georges Mikautadze · shot
+0.849
2 Dani Parejo · shot
+0.840
3 Gerard Moreno · shot
+0.797
4 Pape Gueye · shot
+0.565
5 Ilias Akhomach · pass
+0.486
6 Alberto Moleiro · carry
+0.404
Set Pieces by Player
Who delivers Villarreal’s dead balls and who finishes them this season. 232 corners taken, most by Alberto Moleiro (53); 93 shots from corners and free kicks, 7 goals, led by Gerard Moreno (3 goals, 1.30 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
Nicolas Pépé
45
37 (82%)
6
—
0.17
1
1/1
Alberto Moleiro
53
38 (72%)
3
1
0.09
2
—
Dani Parejo
42
34 (81%)
2
—
0.06
2
1/1
Gerard Moreno
—
—
11
3
1.30
—
4/4
Georges Mikautadze
18
10 (56%)
7
—
0.41
1
1/1
Sergi Cardona
7
4 (57%)
8
—
0.40
—
—
Ayoze Pérez
3
2 (67%)
8
—
0.52
1
1/1
Tajon Buchanan
16
7 (44%)
3
—
0.07
—
—
Ilias Akhomach
16
13 (81%)
2
—
0.08
—
—
Pape Gueye
—
—
5
1
0.52
1
2/2
Santi Comesaña
—
—
6
—
0.44
—
—
Renato Veiga
—
—
6
—
0.42
—
—
Alfonso Pedraza
6
6 (100%)
2
—
0.05
—
—
Juan Foyth
—
—
4
—
0.32
—
—
Top Performers
Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 300 minutes). Coloured chips are that player's strongest capability blocks.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Nicolas Pépé
M
2950
1.89
123
31.9
Alberto Moleiro
M
3199
1.58
65
29.9
Gerard Moreno
F
1845
1.61
47
20.7
Pape Gueye
M
2981
0.97
46
44.7
Georges Mikautadze
F
2731
1.12
40
10.4
Tajon Buchanan
M
2395
0.98
42
16.3
Sergi Cardona
D
2579
0.87
43
31.9
Santi Comesaña
M
3035
0.83
39
34.4
Wide Delivery Leaders
Crosses and cutbacks — wingers and full-backs only (by real average position, not the raw D/M position code), ranked by combined volume.
player
pos
min
crosses (completed)
cutbacks (completed)
Nicolas Pépé
W
2950
34 (59%)
44 (75%)
Sergi Cardona
FB
2579
39 (18%)
37 (43%)
Gerard Moreno
W
1845
14 (29%)
12 (50%)
Ilias Akhomach
W
626
13 (54%)
10 (30%)
Carlos Romero
FB
456
2 (0%)
3 (67%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Santiago Mouriño
D
2946
662
117
33
171
Renato Veiga
D
3550
515
22
35
121
Santi Comesaña
M
3035
467
55
39
153
Pau Navarro
D
2386
433
71
19
78
Pape Gueye
M
2981
418
46
41
148
Sergi Cardona
D
2579
409
59
42
94
Rafa Marín
D
2085
352
37
18
62
Alberto Moleiro
M
3199
320
38
12
125
Full Squad Data
Every player with 100+ minutes (29 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Renato Veiga
D
41
3550
0
0.7
4
126
515
48.9
Alberto Moleiro
M
47
3199
12
7.2
56
138
320
29.9
Luiz Júnior
G
32
3042
0
0.0
0
70
91
18.7
Santi Comesaña
M
43
3035
3
4.0
28
154
467
34.4
Pape Gueye
M
40
2981
8
6.2
32
138
418
44.7
Nicolas Pépé
M
42
2950
10
8.7
62
166
306
31.9
Santiago Mouriño
D
35
2946
1
1.7
9
154
662
41.8
Georges Mikautadze
F
42
2731
16
14.3
34
38
147
10.4
Sergi Cardona
D
37
2579
1
1.2
25
189
409
31.9
Tajon Buchanan
M
42
2395
7
3.7
26
87
314
16.3
Pau Navarro
D
28
2386
0
0.1
4
50
433
20.6
Rafa Marín
D
23
2085
1
0.3
7
52
352
21.0
Gerard Moreno
F
31
1845
12
8.3
33
80
179
20.7
Ayoze Pérez
F
35
1798
6
7.1
24
25
183
8.6
Alfonso Pedraza
D
27
1787
1
1.2
20
100
235
17.2
Juan Foyth
D
19
1483
0
0.5
2
84
252
23.9
Dani Parejo
M
32
1478
1
0.9
25
79
170
22.0
Tani Oluwaseyi
F
32
1147
2
3.6
4
8
122
1.9
Thomas Partey
M
25
1039
0
0.9
8
21
150
8.9
Alex Freeman
D
18
1031
1
0.3
10
89
212
16.9
Arnau Tenas
G
10
951
0
0.0
0
30
21
7.0
Ilias Akhomach
M
18
626
0
2.5
13
41
68
7.5
Péter Gulácsi
G
6
575
0
0.0
0
10
18
2.6
Carlos Romero
D
6
456
6
3.6
4
25
76
5.9
Nathan Saliba
M
6
383
0
0.3
1
16
71
4.4
Carlos Macià
M
11
348
0
0.1
1
8
78
2.8
Logan Costa
D
4
215
0
0.2
1
12
18
4.5
Manor Solomon
M
6
181
1
0.3
2
8
17
1.7
Yéremy Pino
M
2
165
0
0.1
5
13
15
3.1
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.
Renato Veiga
Stopper / marker · Defender
minutes3550
goals · xG0 · 0.7
prog passes /903.2
key passes /900.10
def actions /9013.1
pass accuracy89%
Alberto Moleiro
Creative forward · Forward
minutes3199
goals · xG12 · 7.2
prog passes /903.9
key passes /901.58
def actions /909.0
pass accuracy79%
Luiz Júnior
Goalkeeper · Goalkeeper
minutes3042
goals · xG0 · 0.0
prog passes /902.1
key passes /900.00
def actions /902.7
pass accuracy77%
Santi Comesaña
Ball-winner / destroyer · Midfielder
minutes3035
goals · xG3 · 4.0
prog passes /904.6
key passes /900.83
def actions /9013.8
pass accuracy84%
Pape Gueye
Poacher / finisher · Forward
minutes2981
goals · xG8 · 6.2
prog passes /904.2
key passes /900.97
def actions /9012.6
pass accuracy82%
Nicolas Pépé
Creative forward · Forward
minutes2950
goals · xG10 · 8.7
prog passes /905.1
key passes /901.89
def actions /909.3
pass accuracy80%
Santiago Mouriño
Ball-playing defender · Defender
minutes2946
goals · xG1 · 1.7
prog passes /904.7
key passes /900.27
def actions /9020.2
pass accuracy84%
Georges Mikautadze
Poacher / finisher · Forward
minutes2731
goals · xG16 · 14.3
prog passes /901.3
key passes /901.12
def actions /904.8
pass accuracy75%
Sergi Cardona
Ball-playing defender · Defender
minutes2579
goals · xG1 · 1.2
prog passes /906.6
key passes /900.87
def actions /9014.3
pass accuracy79%
Recruitment Intelligence — profiles to sign
The question
If you were sporting director, which player profiles would move the needle most?
Each recruitment target is derived directly from the team's weakest areas vs the league — the gap, why it shows in the data, and the profile that closes it.
Need — bottom-third: press intensity (PPDA) (9th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (8.53, 9th percentile vs the league).
Need — bottom-third: progression /game (35th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (42.19, 35th percentile vs the league).
Need — below-average: field tilt % (43th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (46.84, 43th percentile vs the league).
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