Combining every season — this one is larger, give it a moment.
Team reportLa Liga 2026
Valencia
A territorially-dominated side, aggressive high-press out of possession, with a low-output attack. Currently #19 of 20 on 6 points (1-3-6, 7:17). 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 Valencia and how good was the season?
Read. Valencia currently sit #19 of 20 on 6 points (1W-3D-6L, 0.60 pts/game), scoring 7 and conceding 17 for a goal difference of -10.
On the ball they are a territorially-dominated team (39% field tilt, #20 in the league); off it they defend with a aggressive high-press (#20 of 20 for press intensity).
Across the 10 matches of event data, they create 0.97 xG/game (#17) and concede 1.35 (#13), a net of -0.38 xG/game — the underlying performance matches the actual goal difference.
Season Context — the league table
The question
Where did Valencia actually finish, and against whom?
The authoritative final table (full season), centred on Valencia.
#
team
P
W
D
L
GF
GA
GD
Pts
16
Rayo Vallecano
9
2
3
4
12
20
-8
9
17
Getafe
10
2
3
5
5
15
-10
9
18
Espanyol
10
2
2
6
12
14
-2
8
19
Valencia
10
1
3
6
7
17
-10
6
20
Malaga
10
0
5
5
7
19
-12
5
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Valencia 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
Valencia tend to fade after a strong start — first-half net xG -1.43, second-half -2.36. Their strongest period is 0-15' (net +0.10 xG); their most dangerous period to face is 46-60' (net -1.62 xG against them).
xG Race — the season, match by match
Expected goals piling up over 10 matches: Valencia 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 (-3.8 xG). Hover a point for that match.
ValenciaOpponents against Valencia
Tactical DNA
The football question
In five genes, what is Valencia'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.
12
Build-Up
possession control from the back
10
Progression
moving the ball upfield with threat
12
Creation
manufacturing chances
0
Press
winning the ball high & hard
35
Solidity
resisting the opponent's threat
Genetic identity
Valencia are defined most by their Solidity DNA (35/100 · limited at resisting the opponent's threat), and least by their Press DNA (0/100). 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
35%
Possession
30%
Field tilt
17%
Disrupt
Central progression ~proxy
30%
Dribble tendency
52%
Progressive passes
30%
Finish
Final-third patience
35%
Shot quality
52%
Open-play xG
30%
Press
Forward press ~proxy
30%
High regains
65%
Pressing efficiency ~proxy
26%
Defend
Def-mid press ~proxy
13%
High line ~proxy
35%
PAdj defensive actions
30%
Valencia is defined most by Press (41% in the league) and weakest on Defend (26%). 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 Valencia actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Valencia'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; Valencia highlighted. Hover any dot for the team.
Vision AI Model Insight
Valencia post 39% field tilt, ranking #20 of 20 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 0.60 points/game sits below the league-average return — territory is genuinely converting into results.
Where the time goes — how long each phase lasts
The question
When Valencia has the ball, how much of that time is spent building, progressing and creating?
The share of Valencia'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
27.6%
Progression
45.8%
Chance creation
24.2%
Attacking transition
2.4%
Vision AI Model Insight
Progression is where Valencia 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
Maffeo ↔ Gayà
71p · 0.2xT
Gayà ↔ Tárrega
67p · -0.4xT
Gayà ↔ Ugrinic
56p · 0.0xT
Gayà ↔ Rodríguez
53p · 0.0xT
Gayà ↔ Rodríguez
50p · -0.0xT
Dimitrievski ↔ Gayà
48p · -0.0xT
Rodríguez ↔ Tárrega
43p · -0.3xT
Gayà ↔ Gayà
43p · -0.2xT
Maffeo ↔ Rodríguez
40p · 0.8xT
Dimitrievski ↔ Rodríguez
40p · 0.1xT
Vision AI Model Insight
Busiest connection: Pablo Maffeo ↔ José Luis Gayà (71 passes). Most dangerous per pass: José Gayà ↔ Arnaut Danjuma (0.05 xT/pass over 31 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Valencia had the ball
Every touch across 99 matches. Brighter means more touches.
Which Zones Do They Attack Through?
The question
Across the whole pitch, where does Valencia 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
4542
ACTIONS
Carries
the ball moved with a player
1132
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (13.3% of all actions). 62% of actions run through the inside lanes (centre + both half-spaces) versus 38% down the two wings — an inside-dominant, half-space build. By third: 33% defensive, 47% middle, 20% attacking.
Attack Sides
Which channel they attacked through this season: the share of every action made in the opponent’s half, down the left, through the middle and down the right. Valencia leaned on their right (43%). The bars under the pitch put the league’s share beside theirs.
Valencia
36%21%43%
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. Valencia made 326 this season (32.6 a match); 36% 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
87
8.7
27%
29%
Left half-space
49
4.9
15%
15%
Centre
31
3.1
10%
12%
Right half-space
43
4.3
13%
15%
Right wing
116
11.6
36%
29%
Build-up2 sections
Build-Up — the pass map
The football question
How does Valencia 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.
1541build-up passes attempted
77%completed
28%reach the middle third
1%go long into the final third
Pass types
462CB · 39%
71Long Wide · 6%
11Long Central · 1%
460Wide → FB · 39%
178Central · 15%
Sequence success — build-up
102build-up sequences this season
13%succeed — reach the next third or a shot
44%turned over with nothing to show
CB462 · 39%
Long Wide71 · 6%
Long Central11 · 1%
Wide → FB460 · 39%
Central178 · 15%
◆ Vision AI Insight
Valencia build predominantly down the left, with Dimitrievski as the fulcrum (240 build-up passes). Only 29% 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 (76×).
Pass Explorer
Every pass of Valencia’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. 388 progressive passes across 10 matches (38.8/game).
Origin lane
Right wing
35%
Right half-space
12%
Central
14%
Left half-space
10%
Left wing
29%
Progression is right-dominant: 47% right side · 14% central · 39% left.
Who generates it
José Luis Gayà
37 · 10%
Pablo Maffeo
34 · 9%
Stole Dimitrievski
32 · 8%
Arnaut Danjuma
28 · 7%
Filip Ugrinic
28 · 7%
Top two — José Luis Gayà & Pablo Maffeo — account for 18% of all progression.
PROGRESSION
38.8 prog passes/game
mostly right
→
PENETRATION
26% reach final third
19% reach the box
→
THREAT
the other 74% is recycled
progress ≠ danger
What came of it.26% of progressive passes reached the final third and 19% the box; the rest was recycled in front of the block. 18% 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 wingefficient
Right half-spacebalanced
Centralsterile
Left half-spacesterile
Left wingefficient
Progression — the pass map
The football question
Once Valencia 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.
2092progression passes attempted
85%completed
14%break into the final third
13%go backward into the defensive third
Pass types
596CB · 34%
80Long Wide · 5%
9Long Central · 1%
841Wide → FB · 47%
249Central · 14%
Sequence success — progression
176progression sequences this season
25%succeed — reach the next third or a shot
44%turned over with nothing to show
CB596 · 34%
Long Wide80 · 5%
Long Central9 · 1%
Wide → FB841 · 47%
Central249 · 14%
◆ Vision AI Insight
Valencia progress predominantly down the left, with Gayà the busiest midfield outlet (258 progression passes). Only 14% of passes that start in midfield actually break the final-third line — the rest (73%) is recycled back into midfield or (13%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is RW mid → RHS mid (101×) — press that lane and midfield progression stalls.
Decision Quality — not all completed passes are equal
A 90% pass completion can hide a sideways habit. Grading every pass by the threat it adds separates value creation from safe circulation.
Excellent (high xT gain)
12%
Progressive
1%
Neutral / sideways
50%
Safe / backward
36%
14% of passes are progressive-or-better; the remaining 86% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Valencia actually progress the ball with their feet, not a pass?
238 progressive carries this season across the whole squad (22% of 1079 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 43m. Most active carrier: Danjuma (29). Filter to one player below.
First (72)Second (67)Third (57)Fourth (42)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 Valencia'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.
109shots
9.7xG
0.09xG per shot
3big chances (0.3+ xG)
6goals
#17key passes / game in the league
#19box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition22% of shots
24
3
2.72
0.11
Cross
1
0
0.06
0.06
Cut-back
1
0
0.26
0.26
Long ball
7
1
0.78
0.11
Pass into the box / short pass
11
1
0.97
0.09
Own creation (carry, dribble, rebound)
4
1
0.64
0.16
Settled attack56% of shots
61
2
5.00
0.08
Cross
13
0
1.09
0.08
Cut-back
5
1
0.53
0.11
Long ball
1
0
0.03
0.03
Pass into the box / short pass
20
1
1.74
0.09
Own creation (carry, dribble, rebound)
22
0
1.62
0.07
Set piece22% of shots
24
1
1.96
0.08
Corner
21
0
1.12
0.05
Free kick
2
0
0.05
0.02
Penalty
1
1
0.79
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
Javi Guerra
7
1.15
2
David Otorbi
5
0.73
0
Luis Rioja
7
0.60
0
José Gayà
7
0.50
0
Arnaut Danjuma
7
0.49
0
Who takes them
Player
Shots
xG
Goals
Arnaut Danjuma
18
1.43
0
Javi Guerra
17
1.19
0
Hugo Duro
10
1.14
0
José Luis Gayà
3
0.88
1
David Otorbi
8
0.87
1
Vision AI Model Insight
The biggest source of Valencia's chances, by xG, is settled attack (5.0 of 9.7 xG, 61 of 109 shots), mostly pass into the box / short pass. 24 of the 109 shots (22%) came within 15 seconds of winning the ball. 24 of the 109 shots came from set pieces; 6 goals from 9.7 xG (-3.7).
Chance Creation — the pass map
The football question
How does Valencia 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 · 9%
6Long Wide · 9%
10Long Central · 14%
24Wide → FB · 35%
23Central · 33%
Sequence success — final-third
115final-third sequences this season
23%succeed — produce a shot
46%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 · 9%
Long Wide6 · 9%
Long Central10 · 14%
Wide → FB24 · 35%
Central23 · 33%
Who creates — volume × threat
12Guerra
9Danjuma
8Gayà
6Rioja
5Elliott
5Ugrinic
5Otorbi
69key passes #17 of 20
8.8box entries/game #19 of 20
25.9final-3rd entries/game #18 of 20
0.97xG/game #17 of 20
6goals #18 of 20
-3.7finishing vs xG #18 of 20
◆ Vision AI Insight
Valencia lean left — 43% of their key passes come from that flank and its half-space (30 of 69), most often from Gayà (8). They funnel chances into the c of the final third, most often via RW att → C att (10 key passes, most often from Rioja). Guerra is the primary source overall. They generate 0.97 xG a game and finish it wasteful — they under-perform their xG, led by Umar Sadiq (1G), José Luis Gayà (1G), Dani Raba (1G).
Crosses & Cutbacks — squad-wide
The question
How does Valencia deliver into the box from wide areas, and what comes of it?
141 crosses: 43 found a team-mate (30%), 12 led to a shot (9%). 23 cut-backs: 10 found a team-mate (43%), 6 led to a shot (26%). 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 Valencia actually cross from?
141 crosses this season (the same crosses as the map above), split into fifteen territories — five channels (both wings, both half-spaces and the centre) by three depths from the halfway line to the byline. 24% come from one territory, the byline right wing; 7 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · right wing
34
24%
1
advanced · right wing
33
23%
5
byline · left wing
28
20%
3
advanced · left wing
23
16%
2
deep · right wing
8
6%
0
deep · left wing
8
6%
1
byline · left half-space
3
2%
0
advanced · left half-space
2
1%
0
advanced · right half-space
1
1%
0
byline · right half-space
1
1%
0
Finishing3 sections
Shot Map
109 shots for 9.7 xG (0.97/game, #17 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Low-output attack. 10.9 shots/game at 0.089 xG/shot. Box entries 9/game (#19). Threat created 9.3 xT/game (#18).
Goal Sequences
The move behind each of Valencia’s 7 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 — 7 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Valencia scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
5 · 83%
Set pieces
0 · 0%
Penalties
1 · 17%
By finish
Right foot
6 · 100%
Left foot
0 · 0%
Header
0 · 0%
Vision AI Model Insight
6 goals scored. 83% come in open play; set pieces add 0%. 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
259
Failed forward pass
170
Failed take-on
96
Lost in the defensive third
359
Their weakest zone is the right wing in the defensive third: 35% of 195 pass attempts there are lost (69 times). Separately, 28% 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 Valencia 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.
7
Pressing Index /100 · passive
Intensity0
PPDA, high-press share, high-zone actions
Height0
how high up the pitch they defend
Effectiveness0
high recoveries & high-regain share
Disruption35
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
18%
RHS
21%
C
26%
LHS
20%
LW
16%
By third (high / mid / low regain)
Def 55%
Mid 34%
Att 12%
Read
Ranked #20 of 20 for press intensity, this is a high press. Note the tension: 55% 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, 43% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#20/20
lower = more intense; rank is what matters
Defensive actions / game
152
#8/20
High-press share
17%
#20/20
def actions won high up
Defensive-action height (0–100)
34.7
#20/20
avg pitch height of actions
High recoveries / game
17.3
#20/20
ball won in mid+att third
High-recovery share
43%
#20/20
share of recoveries won high
Opponent completion allowed
84%
#12/20
lower = more disruptive
Opponent progressive allowed
9.8%
#14/20
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 Valencia win it back with a defensive action?
Counted over the 333 opposition possessions that Valencia 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 Valencia step in. Valencia win it after 7.2 opponent passes in the first half-hour and after 6.4 after the hour mark (sooner).
PASSES THEY GET
6.5passes
median 4 · before Valencia win it
TIME THEY KEEP IT
19sec
median 9s · 33.3 wins per game
How many passes the opponent got in before the ball was won
33%
29%
16%
23%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
7.5
22s
15–30′
6.8
20s
30–45+′
5.9
16s
45–60′
5.6
17s
60–75′
7.6
22s
75–90+′
5.7
16s
average passesaverage seconds
Attitude in each third
Every other style number here says how much Valencia 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 Valencia 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) 1,541 passes
nothing unusual in this zone
Width of use-0.5819.81
Wide-channel share-0.510.27
Side bias+0.060.37
Pass length+0.0222.78
Long-ball share+0.010.23
Forward gain per pass+0.0911.85
Backward-pass share+0.260.21
Deep-pass share+0.280.31
Completion-0.340.77
Seconds between passes+0.123.40
Side used
left 27% · central 48% · right 25%
Progression (middle third) 2,092 passes
nothing unusual in this zone
Width of use-0.3924.75
Wide-channel share-0.470.37
Side bias-0.70-2.71
Pass length+0.3917.77
Long-ball share+0.360.12
Forward gain per pass+0.073.71
Backward-pass share+0.110.34
Deep-pass share+0.190.17
Completion-0.120.84
Seconds between passes+0.013.20
Side used
left 31% · central 32% · right 38%
Final third 909 passes
nothing unusual in this zone
Width of use+0.6833.28
Wide-channel share+0.710.65
Side bias-0.38-3.16
Pass length+0.3716.04
Long-ball share+0.240.11
Forward gain per pass+0.031.08
Backward-pass share+0.380.41
Deep-pass share+0.240.10
Completion+0.080.70
Seconds between passes+0.273.60
Side used
left 40% · central 12% · right 48%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Valencia'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 Valencia 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 share18%
#10 of 20 · reaches final third in ≤3 passes
Patient build-up share26%
#13 of 20 · spells of 6+ passes
Tempo (possession length)17.8s
#10 of 20 · shorter = faster tempo
Passes per possession4.3
#13 of 20
Counter-attack shots /game1.10
#6 of 20 · shot within 12s of a regain in own half
Press→shot /game2.67
#14 of 20 · shot within 8s of a high regain
Speed to final third after regain11.9s
#6 of 20 · lower = faster break
Sequence success — attacking transition
16attacking transition sequences this season
19%succeed — produce a shot
50%turned over with nothing to show
Sequence success — defensive transition
34defensive transition sequences this season
50%succeed — reach the next third or a shot
12%turned over with nothing to show
Vision AI Model Insight
Valencia are a direct, fast-break side: 18% of possessions reach the final third in 3 passes or fewer (#10 of 20), against 26% built patiently over 6+ passes (#13 of 20). Winning the ball back leads to a shot inside 12 seconds 1.10 times a game (#6), and a high regain converts to a shot within 8 seconds 2.67 times a game (#14 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 Valencia? 539 opponent progressive passes and 155 shots faced (13.5 xG against) across the season.
Opponent threat by lane (attacking into Valencia)
Right wing
28%
Right half-space
15%
Central
15%
Left half-space
13%
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 Valencia actually come from — open play, dead balls, and who supplies them?
Every goal Valencia conceded across the loaded matches — the opponent's shots in Valencia'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 (113 total)
By situation
Open play
13 · 87%
Set pieces
1 · 7%
Penalties
1 · 7%
Vision AI Model Insight
15 goals conceded. 87% come in open play; set pieces account for only 7%, so dead-ball defending is not the main issue. 13% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre of the attacking third (25% of key passes faced) — that is the zone to shut off.
Context
Shape and tactics
Set pieces, strengths and weaknesses, and who they resemble.
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
5 g · 7.7 xG
Set pieces
0 g · 1.2 xG
Penalties
1 g
0% of goals come from set pieces (0 of 6), worth 1.2 xG from 23 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Valencia's corners go?
42 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 (17)
Delivered into the box 88%Short 12%
Left side (25)
Delivered into the box 100%Short 0%
Where opponents attack Valencia from set pieces
17 shots from opponent corners against Valencia, 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 (8)
Shot 8Goals 1
Left flag (9)
Shot 9Goals 0
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
none stand out
Weaknesses (bottom-third vs league)
press intensity (PPDA) — 6.88 (0th pct)
field tilt % — 38.55 (0th pct)
box entries /game — 8.80 (5th pct)
progression /game — 38.80 (10th pct)
threat created /game — 9.30 (10th 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.
Getafe
80%
Deportivo
79%
Levante
67%
Espanyol
66%
Malaga
64%
Performance vs Opponent Styles
The question
Not just how Valencia 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 Valencia's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (3m)
1.00
1.67
0.33
vs mid-block opponents (3m)
0.67
2.67
0.33
vs low-block opponents (4m)
0.50
1.00
1.00
Behaviour — how Valencia actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
78%
16%
40
10.2
15.0
vs mid-block opponents
75%
18%
36
8.1
6.3
vs low-block opponents
82%
13%
40
9.5
6.0
Vision AI Model Insight
Facing a high press, retention drops to 78% vs 82% against a low block (4pt lower under pressure), and directness (long-ball share) sits at 16% when pressed vs 13% against a low block — a mild adjustment, not a wholesale change.
Scouting Summary — the team in brief
In brief. Valencia are territorially-dominated with a aggressive high-press.
Their attack creates 0.97 xG a game and they concede 1.35 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 Valencia’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 Valencia’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).
+12.5on-ball value, 10 matches
Where the value came from
Passes4542 actions+3.30
Carries1079 actions+0.62
Dribbles180 actions+0.46
Shots109 actions+4.64
Ball wins582 actions+3.49
Most on-ball value (OBV)
Actions
OBV
per 100
José Luis Gayà
705
+1.83
+0.26
Stole Dimitrievski
457
+1.41
+0.31
Javi Guerra
455
+1.40
+0.31
Arnaut Danjuma
322
+1.28
+0.40
David Otorbi
204
+1.12
+0.55
José Gayà
423
+0.76
+0.18
Luis Rioja
168
+0.68
+0.41
Guido Rodríguez
467
+0.63
+0.13
Biggest single moves
OBV
1 José Luis Gayà · shot
+0.845
2 Umar Sadiq · ball win
+0.561
3 Dani Raba · shot
+0.278
4 Stole Dimitrievski · pass_fail
+0.251
5 Luis Rioja · pass
+0.216
6 Arnaut Danjuma · shot
+0.215
Set Pieces by Player
Who delivers Valencia’s dead balls and who finishes them this season. 42 corners taken, most by Filip Ugrinic (12); 23 shots from corners and free kicks, 0 goals. “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
Arnaut Danjuma
11
9 (82%)
3
—
0.08
—
—
Javi Guerra
11
9 (82%)
2
—
0.05
1
—
César Tárrega
—
—
5
—
0.29
—
—
Filip Ugrinic
12
12 (100%)
—
—
0.00
—
—
Hugo Duro
—
—
4
—
0.33
—
—
Dani Raba
1
0 (0%)
2
—
0.10
—
—
Luis Rioja
3
3 (100%)
1
—
0.03
—
—
Mouctar Diakhaby
—
—
2
—
0.14
—
—
José Luis Gayà
—
—
1
—
0.02
1
1/1
Pablo Maffeo
—
—
2
—
0.08
—
—
Ryunosuke Sato
3
3 (100%)
—
—
0.00
—
—
Aaron Mayol
—
—
1
—
0.05
—
—
Harvey Elliott
1
1 (100%)
—
—
0.00
—
—
Top Performers
Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 270 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
Arnaut Danjuma
M
785
1.03
16
5.5
Javi Guerra
M
831
1.30
10
6.7
José Gayà
D
644
1.12
8
5.7
Filip Ugrinic
M
623
0.72
10
6.3
David Otorbi
M
384
1.17
8
2.3
Pablo Maffeo
D
603
0.45
5
6.3
Hugo Duro
F
449
0.60
2
0.7
José Luis Gayà
D
875
0.31
2
11.0
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.
player
pos
min
crosses (completed)
cutbacks (completed)
Pablo Maffeo
FB
603
11 (18%)
6 (17%)
José Gayà
FB
644
5 (0%)
8 (50%)
David Otorbi
W
384
4 (50%)
8 (50%)
Arnaut Danjuma
W
785
3 (100%)
5 (60%)
Jesús Vázquez
FB
392
1 (0%)
3 (100%)
Arnau Martínez
FB
289
1 (100%)
0
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
José Luis Gayà
D
875
163
17
12
43
Guido Rodríguez
M
596
152
24
11
44
Pablo Maffeo
D
603
121
10
13
28
César Tárrega
D
540
117
11
10
19
José Gayà
D
644
103
17
2
30
Javi Guerra
M
831
100
13
3
36
Filip Ugrinic
M
623
93
16
5
23
Justin de Haas
D
466
79
5
6
14
Full Squad Data
Every player with 100+ minutes (23 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Stole Dimitrievski
G
10
954
0
0.0
1
32
24
9.3
José Luis Gayà
D
10
875
1
0.9
3
37
163
11.0
Javi Guerra
M
10
831
0
1.2
12
22
100
6.7
Arnaut Danjuma
M
10
785
0
1.4
9
28
43
5.5
José Gayà
D
8
644
0
0.3
8
25
103
5.7
Filip Ugrinic
M
10
623
0
0.4
5
28
93
6.3
Pablo Maffeo
D
9
603
0
0.1
3
34
121
6.3
Guido Rodríguez
M
7
596
0
0.1
1
11
152
5.1
César Tárrega
D
7
540
0
0.3
0
15
117
4.1
Justin de Haas
D
6
466
0
0.0
3
10
79
4.2
Hugo Duro
F
10
449
0
1.1
3
3
64
0.7
Jesús Vázquez
D
8
392
0
0.1
0
22
67
3.7
David Otorbi
M
9
384
1
0.9
5
18
45
2.3
Mouctar Diakhaby
D
5
345
0
0.1
0
14
63
3.3
Ryunosuke Sato
M
5
306
0
0.4
0
10
37
1.6
Arnau Martínez
D
6
289
0
0.0
0
20
30
3.7
Luis Rioja
M
6
268
1
0.4
6
28
24
4.7
Aliou Dieng
M
6
267
0
0.0
1
8
52
2.1
Harvey Elliott
M
6
194
0
0.1
5
9
11
2.3
Aaron Mayol
M
2
192
1
0.1
1
4
34
1.6
Dani Raba
M
4
178
1
0.4
2
7
42
1.6
Umar Sadiq
F
3
174
1
0.9
1
1
24
0.2
Iker Córdoba
D
3
123
0
0.0
0
2
26
1.0
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.
Stole Dimitrievski
Goalkeeper · Goalkeeper
minutes954
goals · xG0 · 0.0
prog passes /903.0
key passes /900.09
def actions /902.3
pass accuracy64%
José Luis Gayà
Stopper / marker · Defender
minutes875
goals · xG1 · 0.9
prog passes /903.8
key passes /900.31
def actions /9016.8
pass accuracy88%
Javi Guerra
Ball-winner / destroyer · Midfielder
minutes831
goals · xG0 · 1.2
prog passes /902.4
key passes /901.30
def actions /9010.8
pass accuracy70%
Arnaut Danjuma
Box-to-box midfielder · Midfielder
minutes785
goals · xG0 · 1.4
prog passes /903.2
key passes /901.03
def actions /904.9
pass accuracy73%
José Gayà
Stopper / marker · Defender
minutes644
goals · xG0 · 0.3
prog passes /903.5
key passes /901.12
def actions /9014.4
pass accuracy87%
Filip Ugrinic
Ball-winner / destroyer · Midfielder
minutes623
goals · xG0 · 0.4
prog passes /904.0
key passes /900.72
def actions /9013.4
pass accuracy84%
Pablo Maffeo
Ball-playing defender · Defender
minutes603
goals · xG0 · 0.1
prog passes /905.1
key passes /900.45
def actions /9018.1
pass accuracy71%
Guido Rodríguez
Ball-winner / destroyer · Midfielder
minutes596
goals · xG0 · 0.1
prog passes /901.7
key passes /900.15
def actions /9023.0
pass accuracy83%
César Tárrega
Stopper / marker · Defender
minutes540
goals · xG0 · 0.3
prog passes /902.5
key passes /900.00
def actions /9019.5
pass accuracy86%
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) (0th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (6.88, 0th percentile vs the league).
Need — bottom-third: field tilt % (0th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (38.55, 0th percentile vs the league).
Need — bottom-third: box entries /game (5th pct)
Sign a penetrative wide player or runner to create box entries. The data flags this because few entries into the box (8.80, 5th percentile vs the league).