Combining every season — this one is larger, give it a moment.
Team reportPremier League 2025/26
Aston Villa
A balanced-territory side, aggressive high-press out of possession, with a moderate attack. Finished #4 of 23 on 76 points (22-10-14, 65:61). Tactical profile below is built from 46 matches of ball-by-ball event data, contextualised against the league.
In one read, what kind of team is Aston Villa and how good was the season?
Read. Aston Villa finished #4 of 23 on 76 points (22W-10D-14L, 1.65 pts/game), scoring 65 and conceding 61 for a goal difference of +4.
On the ball they are a balanced-territory team (49% field tilt, #11 in the league); off it they defend with a aggressive high-press (#19 of 23 for press intensity).
Across the 46 matches of event data, they create 1.26 xG/game (#13) and concede 1.31 (#9), a net of -0.05 xG/game — the underlying performance matches the actual goal difference.
Season Context — the league table
The question
Where did Aston Villa actually finish, and against whom?
The authoritative final table (full season), centred on Aston Villa.
#
team
P
W
D
L
GF
GA
GD
Pts
1
Arsenal
46
33
7
6
84
32
+52
106
2
Man City
46
30
9
7
97
44
+53
99
3
Man Utd
46
21
15
10
79
63
+16
78
4
Aston Villa
46
22
10
14
65
61
+4
76
5
Liverpool
46
21
12
13
74
61
+13
75
6
Brighton
46
19
12
15
75
53
+22
69
7
Bournemouth
46
15
21
10
70
67
+3
66
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Aston Villa 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
Aston Villa tend to come alive after the break — first-half net xG -6.08, second-half +3.79. Their strongest period is 76-90+' (net +2.64 xG); their most dangerous period to face is 16-30' (net -3.35 xG against them).
xG Race — the season, match by match
Expected goals piling up over 46 matches: Aston Villa 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 (-2.3 xG). Hover a point for that match.
Aston VillaOpponents against Aston Villa
Tactical DNA
The football question
In five genes, what is Aston Villa'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.
65
Build-Up
possession control from the back
50
Progression
moving the ball upfield with threat
51
Creation
manufacturing chances
35
Press
winning the ball high & hard
61
Solidity
resisting the opponent's threat
Genetic identity
Aston Villa are defined most by their Build-Up DNA (65/100 · average at possession control from the back), and least by their Press DNA (35/100). 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
61%
Field tilt
52%
Disrupt
Central progression ~proxy
70%
Dribble tendency
43%
Progressive passes
39%
Finish
Final-third patience
43%
Shot quality
57%
Open-play xG
57%
Press
Forward press ~proxy
17%
High regains
22%
Pressing efficiency ~proxy
30%
Defend
Def-mid press ~proxy
22%
High line ~proxy
17%
PAdj defensive actions
26%
Aston Villa is defined most by Possess (64% in the league) and weakest on Defend (22%). 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 Aston Villa actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Aston Villa'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; Aston Villa highlighted. Hover any dot for the team.
Vision AI Model Insight
Aston Villa post 49% field tilt, ranking #11 of 23 in the league — comfortably above the league mid-point for territorial control, and their 1.65 points/game sits above the league-average return — territory is genuinely converting into results.
Where the time goes — how long each phase lasts
The question
When Aston Villa has the ball, how much of that time is spent building, progressing and creating?
The share of Aston Villa'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
34.9%
Progression
41.0%
Chance creation
22.5%
Attacking transition
1.6%
Vision AI Model Insight
Progression is where Aston Villa spends most of its time on the ball (41% 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
Konsa ↔ Cash
798p · 30.4xT
Martínez ↔ Konsa
621p · 15.9xT
Konsa ↔ Torres
333p · 7.1xT
Martínez ↔ Torres
318p · 11.3xT
Konsa ↔ Kamara
265p · 9.1xT
McGinn ↔ Cash
258p · 19.9xT
Watkins ↔ Torres
245p · 14.5xT
Cash ↔ Kamara
233p · 8.2xT
Tielemans ↔ Konsa
193p · 6.5xT
Konsa ↔ Bogarde
189p · 5.4xT
Vision AI Model Insight
Busiest connection: Ezri Konsa ↔ Matty Cash (798 passes). Most dangerous per pass: Matty Cash ↔ Morgan Rogers (0.11 xT/pass over 122 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Aston Villa had the ball
Every touch across 460 matches. Brighter means more touches.
Which Zones Do They Attack Through?
The question
Across the whole pitch, where does Aston Villa 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
21895
ACTIONS
Carries
the ball moved with a player
6666
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (12.8% 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: 33% defensive, 45% middle, 22% 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. Aston Villa leaned on their left (37%). The bars under the pitch put the league’s share beside theirs.
Aston Villa
37%26%36%
League
39%23%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. Aston Villa made 1769 this season (38.5 a match); 28% came into the left wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.
Channel
Entries
Per match
Share
League share
Left wing
489
10.6
28%
29%
Left half-space
286
6.2
16%
16%
Centre
274
6.0
15%
12%
Right half-space
255
5.5
14%
14%
Right wing
465
10.1
26%
29%
Build-up2 sections
Build-Up — the pass map
The football question
How does Aston Villa 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.
7270build-up passes attempted
83%completed
22%reach the middle third
1%go long into the final third
Pass types
2526CB · 42%
378Long Wide · 6%
75Long Central · 1%
2379Wide → FB · 40%
661Central · 11%
Sequence success — build-up
1212build-up sequences this season
9%succeed — reach the next third or a shot
42%turned over with nothing to show
CB2526 · 42%
Long Wide378 · 6%
Long Central75 · 1%
Wide → FB2379 · 40%
Central661 · 11%
◆ Vision AI Insight
Aston Villa build predominantly down the right, with Martínez as the fulcrum (997 build-up passes). Only 24% of their build-up passes actually advance a third — the rest is lateral circulation, the hallmark of a possession-controlling side that circulates patiently in midfield before progressing. Their single most-repeated pattern is C def → RHS def (477×).
Pass Explorer
Every pass of Aston Villa’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. 1856 progressive passes across 46 matches (40.3/game).
Origin lane
Right wing
26%
Right half-space
12%
Central
18%
Left half-space
14%
Left wing
30%
Progression is left-dominant: 38% right side · 18% central · 44% left.
Who generates it
Matty Cash
227 · 12%
Ollie Watkins
182 · 10%
Emiliano Martínez
141 · 8%
Morgan Rogers
131 · 7%
John McGinn
125 · 7%
Top two — Matty Cash & Ollie Watkins — account for 22% of all progression.
PROGRESSION
40.3 prog passes/game
mostly left
→
PENETRATION
27% reach final third
21% reach the box
→
THREAT
the other 73% is recycled
progress ≠ danger
What came of it.27% of progressive passes reached the final third and 21% the box; the rest was recycled in front of the block. 22% of the progression ran through two players, mostly down the left side.
Which lanes actually create the threat
Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.
Per lane — volume vs threat
Right wingbalanced
Right half-spacebalanced
Centralbalanced
Left half-spacebalanced
Left wingefficient
Progression — the pass map
The football question
Once Aston Villa 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.
9609progression passes attempted
87%completed
16%break into the final third
12%go backward into the defensive third
Pass types
2581CB · 31%
330Long Wide · 4%
49Long Central · 1%
3909Wide → FB · 47%
1469Central · 18%
Sequence success — progression
1734progression sequences this season
25%succeed — reach the next third or a shot
37%turned over with nothing to show
CB2581 · 31%
Long Wide330 · 4%
Long Central49 · 1%
Wide → FB3909 · 47%
Central1469 · 18%
◆ Vision AI Insight
Aston Villa progress predominantly down the right, with Konsa the busiest midfield outlet (1015 progression passes). Only 16% of passes that start in midfield actually break the final-third line — the rest (72%) is recycled back into midfield or (12%) 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 (459×) — press that lane and midfield progression stalls.
Decision Quality — not all completed passes are equal
A 90% pass completion can hide a sideways habit. Grading every pass by the threat it adds separates value creation from safe circulation.
Excellent (high xT gain)
13%
Progressive
1%
Neutral / sideways
48%
Safe / backward
38%
14% of passes are progressive-or-better; the remaining 86% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Aston Villa actually progress the ball with their feet, not a pass?
1381 progressive carries this season across the whole squad (25% of 5526 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 58m. Most active carrier: Konsa (170). Filter to one player below.
First (402)Second (383)Third (354)Fourth (242)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 Aston Villa'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.
574shots
57.8xG
0.10xG per shot
35big chances (0.3+ xG)
62goals
#10key passes / game in the league
#9box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition22% of shots
127
15
14.63
0.12
Cross
7
3
1.02
0.15
Cut-back
11
2
1.26
0.11
Long ball
10
2
0.95
0.10
Pass into the box / short pass
68
6
7.80
0.11
Own creation (carry, dribble, rebound)
31
2
3.59
0.12
Settled attack56% of shots
323
31
33.41
0.10
Cross
43
3
5.55
0.13
Cut-back
22
4
2.38
0.11
Long ball
19
4
1.82
0.10
Pass into the box / short pass
169
15
15.95
0.09
Own creation (carry, dribble, rebound)
70
5
7.71
0.11
Set piece22% of shots
124
16
9.76
0.08
Corner
106
14
9.21
0.09
Free kick
18
2
0.55
0.03
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
John McGinn
48
5.25
7
Morgan Rogers
40
4.58
6
Ollie Watkins
34
4.33
6
Emiliano Buendía
38
3.58
2
Ian Maatsen
22
3.17
2
Who takes them
Player
Shots
xG
Goals
Ollie Watkins
97
15.19
16
Morgan Rogers
84
7.03
10
Emiliano Buendía
63
4.63
7
Donyell Malen
27
3.93
4
John McGinn
35
3.32
6
Vision AI Model Insight
The biggest source of Aston Villa's chances, by xG, is settled attack (33.4 of 57.8 xG, 323 of 574 shots), mostly pass into the box / short pass. 127 of the 574 shots (22%) came within 15 seconds of winning the ball. 124 of the 574 shots came from set pieces; 62 goals from 57.8 xG (+4.2).
Chance Creation — the pass map
The football question
How does Aston Villa 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
17CB · 4%
25Long Wide · 6%
33Long Central · 8%
136Wide → FB · 33%
200Central · 49%
Sequence success — final-third
1354final-third sequences this season
21%succeed — produce a shot
38%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
CB17 · 4%
Long Wide25 · 6%
Long Central33 · 8%
Wide → FB136 · 33%
Central200 · 49%
Who creates — volume × threat
53McGinn
44Watkins
41Rogers
36Buendía
32Cash
30Tielemans
26Maatsen
411key passes #10 of 23
13.3box entries/game #9 of 23
30.5final-3rd entries/game #14 of 23
1.26xG/game #13 of 23
62goals #9 of 23
+4.2finishing vs xG #3 of 23
◆ Vision AI Insight
Aston Villa lean left — 39% of their key passes come from that flank and its half-space (161 of 411), most often from Watkins (25). They funnel chances into the c of the final third, most often via LW att → C att (43 key passes, most often from Watkins). McGinn is the primary source overall. They generate 1.26 xG a game and finish it clinical — they beat their xG, led by Ollie Watkins (16G), Morgan Rogers (10G), Emiliano Buendía (7G).
Crosses & Cutbacks — squad-wide
The question
How does Aston Villa deliver into the box from wide areas, and what comes of it?
593 crosses: 198 found a team-mate (33%), 57 led to a shot (10%). 145 cut-backs: 66 found a team-mate (46%), 32 led to a shot (22%). 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 Aston Villa actually cross from?
593 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. 25% come from one territory, the byline left wing; 27 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · left wing
149
25%
16
byline · right wing
142
24%
19
advanced · right wing
114
19%
7
advanced · left wing
96
16%
9
deep · right wing
44
7%
1
deep · left wing
21
4%
2
byline · right half-space
8
1%
1
advanced · right half-space
7
1%
1
byline · left half-space
7
1%
1
advanced · left half-space
5
1%
0
Finishing3 sections
Shot Map
574 shots for 57.8 xG (1.26/game, #13 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Moderate attack. 12.5 shots/game at 0.101 xG/shot. Box entries 13/game (#9). Threat created 10.4 xT/game (#9).
Goal Sequences
The move behind each of Aston Villa’s 65 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 — 65 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Aston Villa scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
46 · 74%
Set pieces
16 · 26%
Penalties
0 · 0%
By finish
Right foot
37 · 60%
Left foot
15 · 24%
Header
10 · 16%
Vision AI Model Insight
62 goals scored. 74% come in open play, but 26% from set pieces — a genuine dead-ball weapon that bypasses the open-play build-up.
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
1265
Failed forward pass
838
Failed take-on
518
Lost in the defensive third
1251
Their weakest zone is the right half-space in the attacking third: 29% of 804 pass attempts there are lost (237 times). Separately, 33% 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 Aston Villa 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
Intensity7
PPDA, high-press share, high-zone actions
Height17
how high up the pitch they defend
Effectiveness20
high recoveries & high-regain share
Disruption52
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
15%
RHS
20%
C
21%
LHS
24%
LW
20%
By third (high / mid / low regain)
Def 53%
Mid 34%
Att 13%
Read
Ranked #19 of 23 for press intensity, this is a high press. Note the tension: 53% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (19% high-press share) means that when they do defend, it is often deep. Of recoveries, 51% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#19/23
lower = more intense; rank is what matters
Defensive actions / game
123
#22/23
High-press share
19%
#22/23
def actions won high up
Defensive-action height (0–100)
35.6
#19/23
avg pitch height of actions
High recoveries / game
18.3
#21/23
ball won in mid+att third
High-recovery share
51%
#16/23
share of recoveries won high
Opponent completion allowed
81%
#16/23
lower = more disruptive
Opponent progressive allowed
8.4%
#6/23
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 Aston Villa win it back with a defensive action?
Counted over the 1318 opposition possessions that Aston Villa 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 Aston Villa step in. Aston Villa win it after 5.6 opponent passes in the first half-hour and after 4.1 after the hour mark (sooner).
PASSES THEY GET
4.5passes
median 3 · before Aston Villa win it
TIME THEY KEEP IT
13sec
median 6s · 28.7 wins per game
How many passes the opponent got in before the ball was won
47%
26%
14%
13%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
5.5
16s
15–30′
5.7
16s
30–45+′
4.3
12s
45–60′
4.0
12s
60–75′
4.1
12s
75–90+′
4.1
12s
average passesaverage seconds
Phases of play
Every moment of the match read twice — what Aston Villa 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.
6,705phase segments analysed
9.0smedian time before the opposition engage
2.0their passes per defensive action when pressed
#14of 20 for share of defending spent pressing high
High press 7.0%Mid block 11.0%Low block 50.2%Unopposed 31.9%
What opponents do against Aston Villa
The mirror image, and the part no other section can show: whether teams come
out to press Aston Villa 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 7.5%Mid block 13.6%Low block 48.3%Unopposed 30.6%
Which phases actually produce
Phase
Segments
Avg length
Avg actions
Ends in shot
Turned over
Build-up
2,249
7.2s
3.6
0.3%
49.5%
Progression
2,741
6.9s
4.0
0.6%
45.1%
Chance creation
1,613
6.5s
3.7
27.5%
50.0%
Attacking transition
102
7.2s
4.4
1.0%
34.3%
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
883
0.1%
progression
608
0.3%
build_up → progression
389
0.5%
chance_creation
362
39.2%
progression → chance_creation
307
27.0%
build_up → progression → chance_creation
194
37.6%
Attitude in each third
Every other style number here says how much Aston Villa 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 Aston Villa 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) 7,270 passes
nothing unusual in this zone
Width of use-0.4120.15
Wide-channel share-0.360.28
Side bias-0.010.13
Pass length-0.2621.74
Long-ball share-0.320.20
Forward gain per pass-0.369.90
Backward-pass share+0.730.23
Deep-pass share-0.330.26
Completion+0.320.82
Seconds between passes+0.223.46
Side used
left 26% · central 47% · right 27%
Progression (middle third) 9,609 passes
narrow, central, played inside
Width of use-1.1723.09
Wide-channel share-1.020.33
Side bias-0.04-0.09
Pass length-0.1816.98
Long-ball share-0.380.09
Forward gain per pass-0.203.31
Backward-pass share+0.170.34
Deep-pass share-0.130.15
Completion+0.250.86
Seconds between passes+0.593.46
Side used
left 32% · central 36% · right 32%
Final third 5,016 passes
nothing unusual in this zone
Width of use-0.3630.73
Wide-channel share-0.360.56
Side bias+0.301.67
Pass length-0.4714.73
Long-ball share-0.480.08
Forward gain per pass-0.160.83
Backward-pass share+0.260.40
Deep-pass share-0.030.09
Completion+0.440.73
Seconds between passes-0.413.09
Side used
left 43% · central 18% · right 39%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Aston Villa'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 Aston Villa 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 share16%
#19 of 23 · reaches final third in ≤3 passes
Patient build-up share30%
#5 of 23 · spells of 6+ passes
Tempo (possession length)21.0s
#20 of 23 · shorter = faster tempo
Passes per possession4.9
#6 of 23
Counter-attack shots /game1.20
#6 of 23 · shot within 12s of a regain in own half
Press→shot /game2.57
#18 of 23 · shot within 8s of a high regain
Speed to final third after regain14.4s
#22 of 23 · lower = faster break
Sequence success — attacking transition
86attacking transition sequences this season
16%succeed — produce a shot
48%turned over with nothing to show
Sequence success — defensive transition
376defensive transition sequences this season
60%succeed — reach the next third or a shot
12%turned over with nothing to show
Vision AI Model Insight
Aston Villa are a patient build-up side: 16% of possessions reach the final third in 3 passes or fewer (#19 of 23), against 30% built patiently over 6+ passes (#5 of 23). Winning the ball back leads to a shot inside 12 seconds 1.20 times a game (#6), and a high regain converts to a shot within 8 seconds 2.57 times a game (#18 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 Aston Villa? 1681 opponent progressive passes and 616 shots faced (60.1 xG against) across the season.
Opponent threat by lane (attacking into Aston Villa)
Right wing
31%
Right half-space
14%
Central
16%
Left half-space
13%
Left wing
26%
Where the danger came from. Opponents generated most of their threat through the right wing (31% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Aston Villa actually come from — open play, dead balls, and who supplies them?
Every goal Aston Villa conceded across the loaded matches — the opponent's shots in Aston Villa'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 (412 total)
By situation
Open play
47 · 80%
Set pieces
11 · 19%
Penalties
1 · 2%
Vision AI Model Insight
59 goals conceded. 80% come in open play; set pieces account for only 19%, so dead-ball defending is not the main issue. 17% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the left half-space of the attacking third (20% 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
46 g · 48.0 xG
Set pieces
16 g · 9.8 xG
Penalties
0 g
26% of goals come from set pieces (16 of 62), worth 9.8 xG from 124 shots. A genuine set-piece weapon — defend the box seriously.
Where do Aston Villa's corners go?
225 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 (114)
Delivered into the box 96%Short 4%
Left side (111)
Delivered into the box 95%Short 5%
Where opponents attack Aston Villa from set pieces
102 shots from opponent corners against Aston Villa, 10 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 (46)
Shot 46Goals 6
Left flag (56)
Shot 56Goals 4
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
pass retention % — 82.70 (78th pct)
Weaknesses (bottom-third vs league)
press intensity (PPDA) — 6.85 (17th 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.
Fulham
83%
Chelsea
66%
Man City
46%
Nottingham Forest
43%
Liverpool
33%
Performance vs Opponent Styles
The question
Not just how Aston Villa 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 Aston Villa's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (15m)
1.53
1.20
2.07
vs mid-block opponents (15m)
0.87
1.33
1.00
vs low-block opponents (16m)
1.81
1.44
1.88
Behaviour — how Aston Villa actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
78%
16%
32
8.3
9.3
vs mid-block opponents
84%
10%
45
11.4
16.1
vs low-block opponents
84%
11%
43
11.5
14.6
Vision AI Model Insight
Facing a high press, retention drops to 78% vs 84% against a low block (6pt lower under pressure), and directness (long-ball share) sits at 16% when pressed vs 11% 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. Aston Villa are balanced-territory with a aggressive high-press.
Their attack creates 1.26 xG a game and they concede 1.31 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 Aston Villa’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.
Aston Villa
across 46 matches this season
Progressive carriesat Hull City · 0-0 · 2026-09-05102avg 49
Threat from passingvs Nottingham Forest · 3-1 · 2026-01-0310.28avg 5.64
Passesat Hull City · 0-0 · 2026-09-05730avg 476
Expected goalsat Arsenal · 1-4 · 2025-12-302.90avg 1.26
Final-third entriesat Hull City · 0-0 · 2026-09-0569avg 38
On-Ball Value — who moved the game
Every pass, carry, take-on, shot and ball win is worth the change it made to the chance of scoring minus the chance of conceding in the next 10 seconds. This is Aston Villa’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).
+16.0on-ball value, 12 matches
Where the value came from
Passes5249 actions+5.11
Carries1363 actions-0.55
Dribbles213 actions+0.74
Shots140 actions+7.46
Ball wins611 actions+3.21
Most on-ball value (OBV)
Actions
OBV
per 100
Nicolas Jackson
212
+1.85
+0.87
Johan Manzambi
157
+1.57
+1.00
Emiliano Buendía
431
+1.57
+0.36
Victor Lindelöf
853
+1.24
+0.15
Ollie Watkins
88
+1.05
+1.19
Boubacar Kamara
490
+0.97
+0.20
Ross Barkley
492
+0.89
+0.18
Zion Suzuki
387
+0.83
+0.21
Biggest single moves
OBV
1 Tyrone Mings · shot
+0.651
2 Pau Torres · shot
+0.427
3 Victor Lindelöf · shot
+0.426
4 Johan Manzambi · shot
+0.382
5 Pau Torres · shot
+0.319
6 Leon Bailey · pass
+0.296
Set Pieces by Player
Who delivers Aston Villa’s dead balls and who finishes them this season. 225 corners taken, most by Matty Cash (49); 124 shots from corners and free kicks, 16 goals, led by Ollie Watkins (4 goals, 1.91 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
Matty Cash
49
44 (90%)
11
2
0.27
—
—
Ollie Watkins
38
30 (79%)
14
4
1.91
5
—
John McGinn
40
34 (85%)
7
—
0.37
—
—
Youri Tielemans
25
17 (68%)
9
—
0.34
—
—
Morgan Rogers
1
0 (0%)
13
2
1.45
4
—
Emiliano Buendía
10
3 (30%)
9
1
0.28
7
—
Ian Maatsen
7
6 (86%)
10
—
0.39
—
—
Ezri Konsa
—
—
10
—
0.99
—
—
Ross Barkley
2
1 (50%)
8
3
0.50
—
—
Douglas Luiz
24
15 (62%)
—
—
0.00
—
—
Tyrone Mings
—
—
6
—
0.80
—
—
Leon Bailey
14
10 (71%)
1
—
0.04
—
—
Pau Torres
—
—
5
—
0.43
—
—
Amadou Onana
—
—
5
1
0.83
—
—
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
John McGinn
M
2855
1.67
63
30.4
Matty Cash
D
3771
0.76
67
51.7
Ollie Watkins
D
1977
1.18
55
30.2
Emiliano Buendía
M
2441
1.33
42
19.5
Ian Maatsen
D
2172
1.08
35
21.8
Jadon Sancho
M
950
1.99
35
11.7
Ollie Watkins
F
2945
0.55
29
5.2
Boubacar Kamara
M
2227
0.69
24
24.8
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)
Matty Cash
FB
3771
81 (26%)
34 (21%)
Ian Maatsen
FB
2172
15 (40%)
22 (45%)
Aaron Wan-Bissaka
FB
299
4 (25%)
2 (0%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Matty Cash
D
3771
493
88
25
96
Emiliano Buendía
M
2441
428
70
20
139
Boubacar Kamara
M
2227
373
58
24
96
Ian Maatsen
D
2172
348
54
27
97
John McGinn
M
2855
302
40
17
117
Amadou Onana
M
1858
294
48
25
72
Tyrone Mings
D
1900
289
9
12
60
Pau Torres
D
2107
277
23
13
93
Full Squad Data
Every player with 100+ minutes (30 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Matty Cash
D
42
3771
3
1.4
32
227
493
51.7
Ollie Watkins
F
37
2945
16
14.6
18
16
198
5.2
John McGinn
M
38
2855
6
3.3
53
125
302
30.4
Emiliano Buendía
M
44
2441
7
4.6
36
85
428
19.5
Boubacar Kamara
M
26
2227
1
0.8
17
73
373
24.8
Ian Maatsen
D
35
2172
0
1.7
26
116
348
21.8
Pau Torres
D
26
2107
0
1.0
1
103
277
27.9
Ollie Watkins
D
31
1977
0
0.6
26
166
262
30.2
Tyrone Mings
D
23
1900
0
1.5
6
74
289
21.4
Amadou Onana
M
25
1858
2
1.7
6
46
294
15.7
Victor Lindelöf
D
25
1799
0
0.9
4
50
182
17.4
Ross Barkley
M
29
1322
3
1.9
17
33
174
12.7
Lamare Bogarde
M
29
1203
0
0.0
2
36
137
8.3
Jadon Sancho
M
23
950
0
0.8
21
54
67
11.7
Donyell Malen
F
21
740
4
3.9
6
6
35
1.6
Marco Bizot
G
8
722
0
0.0
0
23
17
5.4
Zion Suzuki
G
7
672
0
0.0
0
32
28
8.8
Douglas Luiz
M
13
648
1
0.8
14
42
92
10.2
Nicolas Jackson
F
7
559
4
1.8
6
9
56
2.5
Leon Bailey
M
13
534
0
0.6
12
19
70
4.0
Tammy Abraham
F
16
454
2
1.8
4
0
33
0.3
João Gomes
M
5
430
1
1.1
4
8
73
3.3
George Hemmings
M
7
350
0
0.1
3
3
51
0.7
Johan Manzambi
M
5
326
2
1.6
7
8
42
3.4
Aaron Wan-Bissaka
D
6
299
0
0.0
2
22
46
3.9
Alysson
M
10
297
1
0.3
1
6
48
1.1
Matteo Ruggeri
D
4
176
0
0.0
2
10
42
1.7
Ibrahim Mbaye
F
5
143
0
0.3
4
5
23
1.3
Harvey Elliott
M
4
132
0
0.3
1
4
10
1.3
Andrés García
D
6
117
0
0.0
0
2
15
0.6
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.
Matty Cash
Ball-playing defender · Defender
minutes3771
goals · xG3 · 1.4
prog passes /905.4
key passes /900.76
def actions /9011.8
pass accuracy78%
Ollie Watkins
Poacher / finisher · Forward
minutes2945
goals · xG16 · 14.6
prog passes /900.5
key passes /900.55
def actions /906.1
pass accuracy72%
John McGinn
Ball-winner / destroyer · Midfielder
minutes2855
goals · xG6 · 3.3
prog passes /903.9
key passes /901.67
def actions /909.5
pass accuracy74%
Emiliano Buendía
Ball-winner / destroyer · Midfielder
minutes2441
goals · xG7 · 4.6
prog passes /903.1
key passes /901.33
def actions /9015.8
pass accuracy78%
Boubacar Kamara
Ball-winner / destroyer · Midfielder
minutes2227
goals · xG1 · 0.8
prog passes /903.0
key passes /900.69
def actions /9015.1
pass accuracy88%
Ian Maatsen
Ball-playing defender · Defender
minutes2172
goals · xG0 · 1.7
prog passes /904.8
key passes /901.08
def actions /9014.4
pass accuracy81%
Pau Torres
Stopper / marker · Defender
minutes2107
goals · xG0 · 1.0
prog passes /904.4
key passes /900.04
def actions /9011.8
pass accuracy88%
Ollie Watkins
Ball-playing defender · Defender
minutes1977
goals · xG0 · 0.6
prog passes /907.6
key passes /901.18
def actions /9011.9
pass accuracy75%
Tyrone Mings
Stopper / marker · Defender
minutes1900
goals · xG0 · 1.5
prog passes /903.5
key passes /900.28
def actions /9013.7
pass accuracy89%
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) (17th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (6.85, 17th percentile vs the league).
Need — below-average: progression /game (39th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (40.35, 39th percentile vs the league).
Need — below-average: xG created /game (43th pct)
Sign a higher-volume goalscorer or chance creator. The data flags this because the attack under-produces xG (1.26, 43th percentile vs the league).
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