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 20 on 65 points (19-8-11, 56:49). Tactical profile below is built from 38 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 20 on 65 points (19W-8D-11L, 1.71 pts/game), scoring 56 and conceding 49 for a goal difference of +7.
On the ball they are a balanced-territory team (51% field tilt, #7 in the league); off it they defend with a aggressive high-press (#15 of 20 for press intensity).
Across the 38 matches of event data, they create 1.30 xG/game (#12) and concede 1.28 (#6), a net of +0.03 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
38
26
7
5
71
27
+44
85
2
Man City
38
23
9
6
77
35
+42
78
3
Man Utd
38
20
11
7
69
50
+19
71
4
Aston Villa
38
19
8
11
56
49
+7
65
5
Liverpool
38
17
9
12
63
53
+10
60
6
Bournemouth
38
13
18
7
58
54
+4
57
7
Sunderland
38
14
12
12
42
48
-6
54
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 -5.42, second-half +6.46. Their strongest period is 76-90+' (net +4.13 xG); their most dangerous period to face is 0-15' (net -3.58 xG against them).
xG Race — the season, match by match
Expected goals piling up over 38 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 (+1.0 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.
72
Build-Up
possession control from the back
48
Progression
moving the ball upfield with threat
50
Creation
manufacturing chances
45
Press
winning the ball high & hard
70
Solidity
resisting the opponent's threat
Genetic identity
Aston Villa are defined most by their Build-Up DNA (72/100 · strong at possession control from the back), and least by their Press DNA (45/100). Percentiles vs the 20 teams in the league.
The Playstyle Wheel
Fifteen style metrics across five domains — Possess, Disrupt, Finish, Press, Defend — each a percentile against the rest of the league. Metrics marked ~proxy use the closest available event-data signal where the standard definition needs data this feed doesn't carry (explicit pressure events, offside/keeper-sweep incidents).
Possess
Deep buildup
78%
Possession
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 51% field tilt, ranking #7 of 20 in the league — comfortably above the league mid-point for territorial control, and their 1.71 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
McGinn ↔ Cash
258p · 19.9xT
Konsa ↔ Onana
198p · 5.3xT
Tielemans ↔ Konsa
193p · 6.5xT
Konsa ↔ Bogarde
189p · 5.4xT
Tielemans ↔ Rogers
165p · 9.6xT
Rogers ↔ Maatsen
163p · 10.5xT
Tielemans ↔ Maatsen
159p · 5.9xT
Konsa ↔ McGinn
154p · 11.7xT
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 380 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
18494
ACTIONS
Carries
the ball moved with a player
4762
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (12.9% of all actions). 66% of actions run through the inside lanes (centre + both half-spaces) versus 34% down the two wings — an inside-dominant, half-space build. By third: 33% defensive, 44% 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 1484 this season (39.1 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
414
10.9
28%
29%
Left half-space
240
6.3
16%
16%
Centre
231
6.1
16%
12%
Right half-space
212
5.6
14%
14%
Right wing
387
10.2
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.
6095build-up passes attempted
84%completed
22%reach the middle third
1%go long into the final third
Pass types
2142CB · 42%
292Long Wide · 6%
68Long Central · 1%
2062Wide → FB · 40%
550Central · 11%
Sequence success — build-up
1094build-up sequences this season
9%succeed — reach the next third or a shot
41%turned over with nothing to show
CB2142 · 42%
Long Wide292 · 6%
Long Central68 · 1%
Wide → FB2062 · 40%
Central550 · 11%
◆ Vision AI Insight
Aston Villa build predominantly down the right, with Martínez as the fulcrum (997 build-up passes). Only 23% 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 (413×).
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. 1565 progressive passes across 38 matches (41.2/game).
Origin lane
Right wing
26%
Right half-space
12%
Central
17%
Left half-space
14%
Left wing
31%
Progression is left-dominant: 38% right side · 17% central · 45% left.
Who generates it
Matty Cash
202 · 13%
Ollie Watkins
182 · 12%
Emiliano Martínez
141 · 9%
Morgan Rogers
131 · 8%
Youri Tielemans
106 · 7%
Top two — Matty Cash & Ollie Watkins — account for 25% of all progression.
PROGRESSION
41.2 prog passes/game
mostly left
→
PENETRATION
27% reach final third
22% reach the box
→
THREAT
the other 73% is recycled
progress ≠ danger
What came of it.27% of progressive passes reached the final third and 22% the box; the rest was recycled in front of the block. 25% 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.
8102progression passes attempted
87%completed
16%break into the final third
12%go backward into the defensive third
Pass types
2169CB · 31%
277Long Wide · 4%
42Long Central · 1%
3309Wide → FB · 47%
1250Central · 18%
Sequence success — progression
1582progression sequences this season
25%succeed — reach the next third or a shot
37%turned over with nothing to show
CB2169 · 31%
Long Wide277 · 4%
Long Central42 · 1%
Wide → FB3309 · 47%
Central1250 · 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 (73%) 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 (388×) — 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?
1175 progressive carries this season across the whole squad (25% of 4665 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 53m. Most active carrier: Konsa (170). Filter to one player below.
First (330)Second (328)Third (312)Fourth (205)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.
483shots
49.5xG
0.10xG per shot
32big chances (0.3+ xG)
53goals
#6key passes / game in the league
#8box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition21% of shots
101
14
12.00
0.12
Cross
5
2
0.84
0.17
Cut-back
6
2
0.75
0.12
Long ball
9
2
0.89
0.10
Pass into the box / short pass
54
6
6.24
0.12
Own creation (carry, dribble, rebound)
27
2
3.28
0.12
Settled attack56% of shots
269
24
28.24
0.10
Cross
38
2
4.57
0.12
Cut-back
16
2
1.83
0.11
Long ball
16
4
1.65
0.10
Pass into the box / short pass
144
11
14.28
0.10
Own creation (carry, dribble, rebound)
55
5
5.92
0.11
Set piece23% of shots
113
15
9.27
0.08
Corner
98
13
8.80
0.09
Free kick
15
2
0.46
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
Morgan Rogers
40
4.58
6
Ollie Watkins
34
4.33
6
John McGinn
37
3.87
3
Emiliano Buendía
31
3.05
2
Ian Maatsen
21
2.92
2
Who takes them
Player
Shots
xG
Goals
Ollie Watkins
97
15.19
16
Morgan Rogers
84
7.03
10
Donyell Malen
27
3.93
4
Emiliano Buendía
49
3.58
6
John McGinn
28
2.40
5
Vision AI Model Insight
The biggest source of Aston Villa's chances, by xG, is settled attack (28.2 of 49.5 xG, 269 of 483 shots), mostly pass into the box / short pass. 101 of the 483 shots (21%) came within 15 seconds of winning the ball. 113 of the 483 shots came from set pieces; 53 goals from 49.5 xG (+3.5).
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
11CB · 3%
20Long Wide · 6%
32Long Central · 9%
106Wide → FB · 31%
176Central · 51%
Sequence success — final-third
1262final-third sequences this season
22%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
CB11 · 3%
Long Wide20 · 6%
Long Central32 · 9%
Wide → FB106 · 31%
Central176 · 51%
Who creates — volume × threat
44Watkins
41Rogers
40McGinn
30Cash
30Tielemans
29Buendía
25Maatsen
345key passes #6 of 20
14.0box entries/game #8 of 20
31.1final-3rd entries/game #11 of 20
1.30xG/game #12 of 20
53goals #7 of 20
+3.5finishing vs xG #4 of 20
◆ Vision AI Insight
Aston Villa lean left — 40% of their key passes come from that flank and its half-space (138 of 345), most often from Watkins (25). They funnel chances into the c of the final third, most often via LW att → C att (39 key passes, most often from Watkins). Watkins is the primary source overall. They generate 1.30 xG a game and finish it clinical — they beat their xG, led by Ollie Watkins (16G), Morgan Rogers (10G), Emiliano Buendía (6G).
Crosses & Cutbacks — squad-wide
The question
How does Aston Villa deliver into the box from wide areas, and what comes of it?
516 crosses: 175 found a team-mate (34%), 49 led to a shot (9%). 120 cut-backs: 52 found a team-mate (43%), 23 led to a shot (19%). 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?
516 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. 27% come from one territory, the byline left wing; 23 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · left wing
137
27%
15
byline · right wing
128
25%
18
advanced · right wing
92
18%
6
advanced · left wing
81
16%
4
deep · right wing
38
7%
1
deep · left wing
17
3%
2
byline · right half-space
7
1%
1
byline · left half-space
7
1%
1
advanced · right half-space
5
1%
1
advanced · left half-space
4
1%
0
Finishing3 sections
Shot Map
483 shots for 49.5 xG (1.30/game, #12 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Moderate attack. 12.7 shots/game at 0.102 xG/shot. Box entries 14/game (#8). Threat created 10.7 xT/game (#8).
Goal Sequences
The move behind each of Aston Villa’s 56 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 — 56 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
38 · 72%
Set pieces
15 · 28%
Penalties
0 · 0%
By finish
Right foot
31 · 58%
Left foot
14 · 26%
Header
8 · 15%
Vision AI Model Insight
53 goals scored. 72% come in open play, but 28% 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
1101
Failed forward pass
727
Failed take-on
423
Lost in the defensive third
981
Their weakest zone is the right half-space in the attacking third: 29% of 684 pass attempts there are lost (199 times). Separately, 35% 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.
27
Pressing Index /100 · passive
Intensity10
PPDA, high-press share, high-zone actions
Height20
how high up the pitch they defend
Effectiveness28
high recoveries & high-regain share
Disruption58
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 #15 of 20 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, 52% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#15/20
lower = more intense; rank is what matters
Defensive actions / game
117
#20/20
High-press share
19%
#19/20
def actions won high up
Defensive-action height (0–100)
35.6
#16/20
avg pitch height of actions
High recoveries / game
19.0
#16/20
ball won in mid+att third
High-recovery share
52%
#13/20
share of recoveries won high
Opponent completion allowed
81%
#13/20
lower = more disruptive
Opponent progressive allowed
8.3%
#4/20
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 Aston Villa win it back with a defensive action?
Counted over the 1107 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 5.7 opponent passes in the first half-hour and after 3.8 after the hour mark (sooner).
PASSES THEY GET
4.4passes
median 3 · before Aston Villa win it
TIME THEY KEEP IT
13sec
median 6s · 29.1 wins per game
How many passes the opponent got in before the ball was won
47%
27%
13%
12%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
5.6
16s
15–30′
5.9
17s
30–45+′
4.4
12s
45–60′
3.7
11s
60–75′
3.7
11s
75–90+′
3.8
11s
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) 6,095 passes
nothing unusual in this zone
Width of use-0.3920.18
Wide-channel share-0.370.28
Side bias+0.050.33
Pass length-0.4321.15
Long-ball share-0.460.18
Forward gain per pass-0.539.17
Backward-pass share+0.800.24
Deep-pass share-0.510.24
Completion+0.470.83
Seconds between passes+0.113.39
Side used
left 27% · central 47% · right 27%
Progression (middle third) 8,102 passes
narrow, central, played inside
Width of use-1.2123.00
Wide-channel share-1.080.33
Side bias+0.040.22
Pass length-0.2016.94
Long-ball share-0.380.09
Forward gain per pass-0.143.40
Backward-pass share+0.120.34
Deep-pass share-0.190.15
Completion+0.300.86
Seconds between passes+0.573.45
Side used
left 32% · central 37% · right 31%
Final third 4,297 passes
nothing unusual in this zone
Width of use-0.4230.58
Wide-channel share-0.410.55
Side bias+0.221.12
Pass length-0.5114.68
Long-ball share-0.450.08
Forward gain per pass-0.080.94
Backward-pass share+0.200.40
Deep-pass share-0.060.09
Completion+0.380.73
Seconds between passes-0.572.97
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%
#16 of 20 · reaches final third in ≤3 passes
Patient build-up share30%
#5 of 20 · spells of 6+ passes
Tempo (possession length)21.0s
#17 of 20 · shorter = faster tempo
Passes per possession4.9
#6 of 20
Counter-attack shots /game1.20
#5 of 20 · shot within 12s of a regain in own half
Press→shot /game2.57
#16 of 20 · shot within 8s of a high regain
Speed to final third after regain14.4s
#19 of 20 · lower = faster break
Sequence success — attacking transition
76attacking transition sequences this season
16%succeed — produce a shot
46%turned over with nothing to show
Sequence success — defensive transition
346defensive transition sequences this season
59%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 (#16 of 20), against 30% built patiently over 6+ passes (#5 of 20). Winning the ball back leads to a shot inside 12 seconds 1.20 times a game (#5), and a high regain converts to a shot within 8 seconds 2.57 times a game (#16 of 20) — not yet a major source of chances.
Defending the box2 sections
Vulnerability Map — how opponents hurt them
The report flipped: where do opponents create their threat against Aston Villa? 1343 opponent progressive passes and 490 shots faced (48.5 xG against) across the season.
Opponent threat by lane (attacking into Aston Villa)
Right wing
31%
Right half-space
14%
Central
17%
Left half-space
13%
Left wing
25%
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 (324 total)
By situation
Open play
36 · 75%
Set pieces
11 · 23%
Penalties
1 · 2%
Vision AI Model Insight
48 goals conceded. 75% come in open play; set pieces account for only 23%, so dead-ball defending is not the main issue. 15% 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 (19% of key passes faced) — that is the zone to shut off.
Context
Shape and tactics
Set pieces, strengths and weaknesses, and who they resemble.
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.
Open play
38 g · 40.2 xG
Set pieces
15 g · 9.3 xG
Penalties
0 g
28% of goals come from set pieces (15 of 53), worth 9.3 xG from 113 shots. A genuine set-piece weapon — defend the box seriously.
Where do Aston Villa's corners go?
199 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 (102)
Delivered into the box 95%Short 5%
Left side (97)
Delivered into the box 96%Short 4%
Where opponents attack Aston Villa from set pieces
84 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 (37)
Shot 37Goals 6
Left flag (47)
Shot 47Goals 4
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
pass retention % — 83.04 (80th pct)
xG conceded /game — 1.28 (70th pct)
field tilt % — 51.32 (65th pct)
Weaknesses (bottom-third vs league)
press intensity (PPDA) — 7.06 (25th pct)
progression /game — 41.18 (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.
Fulham
86%
Chelsea
67%
Man City
58%
Liverpool
45%
Nottingham Forest
22%
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 (12m)
1.58
0.83
2.33
vs mid-block opponents (12m)
1.00
1.50
0.92
vs low-block opponents (14m)
1.79
1.50
1.86
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
79%
14%
36
9.4
11.4
vs mid-block opponents
84%
10%
44
11.1
15.5
vs low-block opponents
84%
11%
43
11.5
14.9
Vision AI Model Insight
Facing a high press, retention drops to 79% vs 84% against a low block (5pt lower under pressure), and directness (long-ball share) sits at 14% when pressed vs 11% against a low block — a mild adjustment, not a wholesale change.
Scouting Summary — the team in brief
In brief. Aston Villa are balanced-territory with a aggressive high-press.
Their attack creates 1.30 xG a game and they concede 1.28 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.
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).
+17.8on-ball value, 12 matches
Where the value came from
Passes6002 actions+9.23
Carries1513 actions-2.34
Dribbles178 actions+0.16
Shots157 actions+7.55
Ball wins627 actions+3.19
Most on-ball value (OBV)
Actions
OBV
per 100
Morgan Rogers
560
+2.69
+0.48
Ollie Watkins
264
+1.99
+0.76
Ross Barkley
515
+1.66
+0.32
John McGinn
329
+1.34
+0.41
Emiliano Buendía
336
+1.10
+0.33
Ian Maatsen
409
+1.00
+0.24
Youri Tielemans
451
+0.97
+0.21
Pau Torres
508
+0.95
+0.19
Biggest single moves
OBV
1 Tyrone Mings · shot
+0.651
2 John McGinn · pass
+0.579
3 Ross Barkley · pass
+0.473
4 Ollie Watkins · shot
+0.472
5 Ian Maatsen · pass
+0.455
6 Pau Torres · shot
+0.427
Set Pieces by Player
Who delivers Aston Villa’s dead balls and who finishes them this season. 199 corners taken, most by Matty Cash (47); 113 shots from corners and free kicks, 15 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
Ollie Watkins
38
30 (79%)
14
4
1.91
5
—
Matty Cash
47
43 (91%)
10
2
0.25
—
—
Youri Tielemans
25
17 (68%)
9
—
0.34
—
—
John McGinn
28
24 (86%)
7
—
0.37
—
—
Morgan Rogers
1
0 (0%)
13
2
1.45
4
—
Ian Maatsen
7
6 (86%)
9
—
0.35
—
—
Ezri Konsa
—
—
10
—
0.99
—
—
Emiliano Buendía
4
0 (0%)
8
1
0.25
6
—
Douglas Luiz
24
15 (62%)
—
—
0.00
—
—
Ross Barkley
1
0 (0%)
6
3
0.38
—
—
Leon Bailey
14
10 (71%)
1
—
0.04
—
—
Tyrone Mings
—
—
5
—
0.73
—
—
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
Morgan Rogers
M
3478
1.06
70
30.5
Matty Cash
D
3176
0.85
63
45.9
John McGinn
M
2191
1.64
46
22.8
Ollie Watkins
D
1977
1.18
55
30.2
Youri Tielemans
M
1960
1.38
44
29.8
Emiliano Buendía
M
1860
1.40
36
16.1
Jadon Sancho
M
950
1.99
35
11.7
Ian Maatsen
D
1728
1.30
31
18.4
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)
Matty Cash
FB
3176
71 (28%)
30 (23%)
Ian Maatsen
FB
1728
14 (43%)
19 (42%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Matty Cash
D
3176
395
66
22
88
Morgan Rogers
M
3478
361
42
13
139
Ezri Konsa
D
3268
348
22
23
108
Emiliano Buendía
M
1860
302
49
15
109
Amadou Onana
M
1858
294
48
25
72
Ian Maatsen
D
1728
286
43
19
82
Youri Tielemans
M
1960
275
58
18
94
Ollie Watkins
D
1977
262
36
15
63
Full Squad Data
Every player with 100+ minutes (25 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Morgan Rogers
M
37
3478
10
7.0
41
131
361
30.5
Ezri Konsa
D
34
3268
0
1.1
4
63
348
35.3
Matty Cash
D
35
3176
3
1.3
30
202
395
45.9
Emiliano Martínez
G
32
3027
0
0.0
2
141
73
33.5
Ollie Watkins
F
37
2945
16
14.6
18
16
198
5.2
John McGinn
M
30
2191
5
2.4
40
93
206
22.8
Ollie Watkins
D
31
1977
0
0.6
26
166
262
30.2
Youri Tielemans
M
25
1960
0
1.8
30
106
275
29.8
Emiliano Buendía
M
36
1860
6
3.6
29
67
302
16.1
Amadou Onana
M
25
1858
2
1.7
6
46
294
15.7
Pau Torres
D
21
1797
0
1.0
1
88
235
25.0
Ian Maatsen
D
30
1728
0
1.3
25
99
286
18.4
Boubacar Kamara
M
18
1475
1
0.7
14
52
229
17.8
Tyrone Mings
D
17
1423
0
1.2
5
56
216
17.3
Lamare Bogarde
M
28
1181
0
0.0
2
35
134
8.2
Victor Lindelöf
D
17
1032
0
0.2
1
24
93
9.4
Jadon Sancho
M
23
950
0
0.8
21
54
67
11.7
Ross Barkley
M
21
937
3
1.4
10
22
114
8.4
Donyell Malen
F
21
740
4
3.9
6
6
35
1.6
Douglas Luiz
M
13
648
1
0.8
14
42
92
10.2
Marco Bizot
G
7
627
0
0.0
0
16
16
4.2
Leon Bailey
M
13
534
0
0.6
12
19
70
4.0
Tammy Abraham
F
12
354
2
1.8
4
0
26
0.3
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.
Morgan Rogers
Poacher / finisher · Forward
minutes3478
goals · xG10 · 7.0
prog passes /903.4
key passes /901.06
def actions /909.3
pass accuracy72%
Ezri Konsa
Stopper / marker · Defender
minutes3268
goals · xG0 · 1.1
prog passes /901.7
key passes /900.11
def actions /909.6
pass accuracy95%
Matty Cash
Ball-playing defender · Defender
minutes3176
goals · xG3 · 1.3
prog passes /905.7
key passes /900.85
def actions /9011.2
pass accuracy78%
Emiliano Martínez
Goalkeeper · Goalkeeper
minutes3027
goals · xG0 · 0.0
prog passes /904.2
key passes /900.06
def actions /902.2
pass accuracy76%
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
Advanced creator · Attacking mid
minutes2191
goals · xG5 · 2.4
prog passes /903.8
key passes /901.64
def actions /908.5
pass accuracy77%
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%
Youri Tielemans
Ball-winner / destroyer · Midfielder
minutes1960
goals · xG0 · 1.8
prog passes /904.9
key passes /901.38
def actions /9012.6
pass accuracy83%
Emiliano Buendía
Ball-winner / destroyer · Midfielder
minutes1860
goals · xG6 · 3.6
prog passes /903.2
key passes /901.40
def actions /9014.6
pass accuracy80%
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) (25th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (7.06, 25th 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 (41.18, 35th percentile vs the league).
Need — below-average: xG created /game (40th pct)
Sign a higher-volume goalscorer or chance creator. The data flags this because the attack under-produces xG (1.30, 40th percentile vs the league).
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