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Team reportPremier League 2026

Arsenal

A possession-dominant side, aggressive high-press out of possession, with a high-volume attack. Currently #2 of 20 on 21 points (7-0-1, 13:5). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

possession-dominantaggressive high-presshigh-volume attack
L
L
W
W
W
W
W
W
W
W
W
L
W
W
W
21
points
#2 of 20 · 8 games
13:5
goals
+8 GD
7-0-1
record
W-D-L
2.62
points/game
#2 in the league
1.56
xG for/game
rank #6
0.82
xG against/game
rank #1
#5
press rank
of 20 · most aggressive
64%
field tilt
#2
Arsenal
League average
Expected goals for / game
1.561.33
Expected goals against / game
0.821.33
Field tilt
64%50%
Pass retention
85%80%
Overview

The team

Who they are and how the season went.

Who Are They? — Identity

The question
In one read, what kind of team is Arsenal and how good was the season?
Read. Arsenal currently sit #2 of 20 on 21 points (7W-0D-1L, 2.62 pts/game), scoring 13 and conceding 5 for a goal difference of +8. On the ball they are a possession-dominant team (64% field tilt, #2 in the league); off it they defend with a aggressive high-press (#5 of 20 for press intensity). Across the 8 matches of event data, they create 1.56 xG/game (#6) and concede 0.82 (#1), a net of +0.74 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

The question
Where did Arsenal actually finish, and against whom?

The authoritative final table (full season), centred on Arsenal.

#teamPWDLGFGAGDPts
1Man City8701209+1121
2Arsenal8701135+821
3Brighton8512237+1616
4Liverpool8431118+315
5Chelsea84131715+213

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Arsenal 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)
even0-15'16-30'31-45'46-60'61-75'76-90+'+1.75
Vision AI Model Insight
Arsenal tend to fade after a strong start — first-half net xG +3.72, second-half +2.21. Their strongest period is 0-15' (net +1.75 xG); their most dangerous period to face is 46-60' (net +0.18 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Arsenal 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 (+5.9 xG). Hover a point for that match.

0591412.56.6Coventry (H) 3-0 · xG 1.68 to 0.21Aston Villa (A) 1-0 · xG 1.16 to 0.41Chelsea (H) 2-1 · xG 1.88 to 0.59Sunderland (A) 2-0 · xG 1.64 to 1.81Brighton (A) 0-3 · xG 1.26 to 1.42Leeds (H) 2-1 · xG 1.96 to 0.78Nottingham Forest (A) 1-0 · xG 0.91 to 0.83Everton (H) 2-0 · xG 2.01 to 0.54M1M2M3M4M5M6M7M8
ArsenalOpponents against Arsenal

Tactical DNA

The football question
In five genes, what is Arsenal's footballing identity?

Each gene is a 0–100 score — the team's league percentile across the metrics that define that phase of play. It distils the whole report into an identity fingerprint: the taller the gene, the more that trait defines them.

88
Build-Up
possession control from the back
75
Progression
moving the ball upfield with threat
68
Creation
manufacturing chances
82
Press
winning the ball high & hard
95
Solidity
resisting the opponent's threat
Genetic identity
Arsenal are defined most by their Solidity DNA (95/100 · elite at resisting the opponent's threat), and least by their Creation DNA (68/100). 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).

Possess78Disrupt51Finish86Press90Defend90
Possess
Deep buildup
57%
Possession
87%
Field tilt
91%
Disrupt
Central progression ~proxy
65%
Dribble tendency
22%
Progressive passes
65%
Finish
Final-third patience
91%
Shot quality
87%
Open-play xG
78%
Press
Forward press ~proxy
91%
High regains
83%
Pressing efficiency ~proxy
96%
Defend
Def-mid press ~proxy
91%
High line ~proxy
96%
PAdj defensive actions
83%
Arsenal is defined most by Press (90% in the league) and weakest on Disrupt (51%). 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.

Keeping the ball6 sections

Field Tilt — Territorial Control

The question
How much of the pitch does Arsenal actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Arsenal'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; Arsenal highlighted. Hover any dot for the team.

Arsenal: 64% tilt, 2.62 pts/gMan City: 66% tilt, 2.62 pts/gBrighton: 61% tilt, 2.00 pts/gLiverpool: 56% tilt, 1.88 pts/gChelsea: 47% tilt, 1.62 pts/gBrentford: 47% tilt, 1.38 pts/gNewcastle: 48% tilt, 1.38 pts/gLeeds: 43% tilt, 1.38 pts/gAston Villa: 40% tilt, 1.38 pts/gIpswich: 43% tilt, 1.25 pts/gHull City: 33% tilt, 1.25 pts/gEverton: 49% tilt, 1.25 pts/gTottenham: 62% tilt, 1.12 pts/gBournemouth: 50% tilt, 1.12 pts/gFulham: 54% tilt, 1.00 pts/gMan Utd: 60% tilt, 0.88 pts/gCrystal Palace: 39% tilt, 0.88 pts/gCoventry: 39% tilt, 0.75 pts/gNottingham Forest: 48% tilt, 0.75 pts/gSunderland: 48% tilt, 0.62 pts/gArsenal33%44%55%66%0.61.32.02.6FIELD TILT %POINTS / GAME
Vision AI Model Insight
Arsenal post 64% field tilt, ranking #2 of 20 in the league — a genuinely territory-dominant side, and their 2.62 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 Arsenal has the ball, how much of that time is spent building, progressing and creating?

The share of Arsenal'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.

Build-up: 23.2% of the time on the ball23%Progression: 47.7% of the time on the ball48%Chance creation: 28.1% of the time on the ball28%Attacking transition: 1.0% of the time on the ball48%PROGRESSION
PhaseShare of the time
Build-up23.2%
Progression47.7%
Chance creation28.1%
Attacking transition1.0%
Vision AI Model Insight
Progression is where Arsenal spends most of its time on the ball (48% 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.

Martin Ødegaard ↔ Declan Rice: 114 passes, 1.2 combined xTDeclan Rice ↔ Myles Lewis-Skelly: 97 passes, 0.1 combined xTMartin Ødegaard ↔ Ben White: 92 passes, 1.7 combined xTEzri Konsa ↔ Declan Rice: 88 passes, -0.0 combined xTEzri Konsa ↔ Gabriel Magalhães: 80 passes, -0.5 combined xTBen White ↔ Declan Rice: 80 passes, 0.4 combined xTGabriel Magalhães ↔ Myles Lewis-Skelly: 75 passes, 0.2 combined xTDavid Raya ↔ Gabriel Magalhães: 74 passes, -0.4 combined xTMartin Ødegaard ↔ Bukayo Saka: 70 passes, 1.0 combined xTGabriel Magalhães ↔ Riccardo Calafiori: 69 passes, -0.7 combined xTDeclan Rice ↔ Gabriel Magalhães: 67 passes, 0.7 combined xTDavid Raya ↔ Ezri Konsa: 65 passes, -0.2 combined xTBen White ↔ Bukayo Saka: 61 passes, 1.2 combined xTDavid Raya ↔ Declan Rice: 57 passes, 1.0 combined xTMartin Ødegaard ↔ Gabriel Magalhães: 52 passes, 0.9 combined xTEzri Konsa ↔ Ben White: 52 passes, -0.5 combined xTMartin Ødegaard ↔ Ezri Konsa: 49 passes, -0.4 combined xTDeclan Rice ↔ Bukayo Saka: 48 passes, 0.5 combined xTMartin Ødegaard ↔ Bruno Guimarães: 45 passes, -0.0 combined xTMartin Ødegaard ↔ Myles Lewis-Skelly: 42 passes, 0.6 combined xTGabriel Magalhães ↔ Christos Tzolis: 41 passes, -0.2 combined xTRiccardo Calafiori ↔ Christos Tzolis: 38 passes, 0.3 combined xTMartin Ødegaard ↔ Kai Havertz: 37 passes, 1.3 combined xTKai Havertz ↔ Declan Rice: 37 passes, 1.5 combined xTMartin Ødegaard — isolate this player's connectionsØdegaardDavid Raya — isolate this player's connectionsRayaKai Havertz — isolate this player's connectionsHavertzDeclan Rice — isolate this player's connectionsRiceGabriel Magalhães — isolate this player's connectionsMagalhãesRiccardo Calafiori — isolate this player's connectionsCalafioriBukayo Saka — isolate this player's connectionsSakaMikel Merino — isolate this player's connectionsMerinoEzri Konsa — isolate this player's connectionsKonsaBen White — isolate this player's connectionsWhiteMartín Zubimendi — isolate this player's connectionsZubimendiBruno Guimarães — isolate this player's connectionsGuimarãesMyles Lewis-Skelly — isolate this player's connectionsLewis-SkelViktor Gyökeres — isolate this player's connectionsGyökeresNoni Madueke — isolate this player's connectionsMaduekeChristos Tzolis — isolate this player's connectionsTzolis
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Ødegaard ↔ Rice
114p · 1.2xT
Rice ↔ Lewis-Skelly
97p · 0.1xT
Ødegaard ↔ White
92p · 1.7xT
Konsa ↔ Rice
88p · -0.0xT
Konsa ↔ Magalhães
80p · -0.5xT
White ↔ Rice
80p · 0.4xT
Magalhães ↔ Lewis-Skelly
75p · 0.2xT
Raya ↔ Magalhães
74p · -0.4xT
Ødegaard ↔ Saka
70p · 1.0xT
Magalhães ↔ Calafiori
69p · -0.7xT
Vision AI Model Insight
Busiest connection: Martin Ødegaard ↔ Declan Rice (114 passes). Most dangerous per pass: Kai Havertz ↔ Declan Rice (0.04 xT/pass over 37 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Arsenal had the ball

Every touch across 80 matches. Brighter means more touches.

Which Zones Do They Attack Through?

The question
Across the whole pitch, where does Arsenal 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
4484
ACTIONS
3%4%10%4%3%8%11%13%10%5%9%7%3%5%6%PASSES
Carries
the ball moved with a player
1108
ACTIONS
2%6%11%4%9%12%15%9%7%9%4%5%7%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the middle third (13.1% 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: 24% defensive, 48% middle, 28% 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. Arsenal leaned on their right (45%). The bars under the pitch put the league’s share beside theirs.

32%Left side23%Middle45%Right sideATTACKING →
Arsenal
32%23%45%
League
39%24%37%

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. Arsenal made 408 this season (51.0 a match); 33% 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.

Left wing: 119 entries (29%)11929%LEFT WINGLeft half-space: 51 entries (12%)5112%LEFT HALF-SPACECentre: 30 entries (7%)307%CENTRERight half-space: 74 entries (18%)7418%RIGHT HALF-SPACERight wing: 134 entries (33%)13433%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing11914.929%31%
Left half-space516.412%16%
Centre303.87%13%
Right half-space749.218%14%
Right wing13416.833%27%
Build-up2 sections

Build-Up — the pass map

The football question
How does Arsenal 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.

1054build-up passes attempted
82%completed
28%reach the middle third
2%go long into the final third

Pass types

315CB · 36%
64Long Wide · 7%
7Long Central · 1%
355Wide → FB · 41%
127Central · 15%

Sequence success — build-up

99build-up sequences this season
7%succeed — reach the next third or a shot
47%turned over with nothing to show
CB315 · 36%
right: 166 passes, most from Konsa166left: 149 passes, most from Magalhães149
Long Wide64 · 7%
right: 40 passes, most from Raya40left: 24 passes, most from Raya24
Long Central7 · 1%
left: 4 passes, most from Raya4right: 3 passes, most from Raya3
Wide → FB355 · 41%
right: 196 passes, most from Raya196left: 159 passes, most from Raya159
Central127 · 15%
right: 64 passes, most from Raya64left: 63 passes, most from Raya63
◆ Vision AI Insight
Arsenal build predominantly down the right, with Raya as the fulcrum (211 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 → RHS def (64×).

Pass Explorer

Every pass of Arsenal’s last 8 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.

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. 351 progressive passes across 8 matches (43.9/game).

Origin lane

Right wing
33%
Right half-space
14%
Central
13%
Left half-space
13%
Left wing
27%
Progression is right-dominant: 47% right side · 13% central · 40% left.

Who generates it

Declan Rice
43 · 12%
Ben White
42 · 12%
Martin Ødegaard
38 · 11%
David Raya
36 · 10%
Bukayo Saka
28 · 8%
Top two — Declan Rice & Ben White — account for 24% of all progression.
PROGRESSION
43.9 prog passes/game
mostly right
→
PENETRATION
21% reach final third
27% reach the box
→
THREAT
the other 79% is recycled
progress ≠ danger
What came of it. 21% of progressive passes reached the final third and 27% the box; the rest was recycled in front of the block. 24% 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
Centralbalanced
Left half-spacebalanced
Left wingbalanced

Progression — the pass map

The football question
Once Arsenal 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.

2130progression passes attempted
90%completed
17%break into the final third
9%go backward into the defensive third

Pass types

478CB · 25%
56Long Wide · 3%
8Long Central · 0%
1041Wide → FB · 54%
335Central · 17%

Sequence success — progression

134progression sequences this season
19%succeed — reach the next third or a shot
39%turned over with nothing to show
CB478 · 25%
left: 267 passes, most from Magalhães267right: 211 passes, most from Konsa211
Long Wide56 · 3%
left: 35 passes, most from Rice35right: 21 passes, most from Rice21
Long Central8 · 0%
right: 5 passes, most from Rice5left: 3 passes, most from Calafiori3
Wide → FB1041 · 54%
right: 645 passes, most from Rice645left: 396 passes, most from Rice396
Central335 · 17%
right: 177 passes, most from Rice177left: 158 passes, most from Rice158
◆ Vision AI Insight
Arsenal progress predominantly down the right, with Rice the busiest midfield outlet (334 progression passes). Only 17% of passes that start in midfield actually break the final-third line — the rest (74%) is recycled back into midfield or (9%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is C mid → RHS mid (133×) — 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
2%
Neutral / sideways
48%
Safe / backward
38%
15% of passes are progressive-or-better; the remaining 85% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.

Carries Map — progressive ball-carries, squad-wide

The question
Where does Arsenal actually progress the ball with their feet, not a pass?

256 progressive carries this season across the whole squad (23% of 1108 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 63m. Most active carrier: Rice (49). Filter to one player below.

First (76)Second (69)Third (62)Fourth (49)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 Arsenal'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.

107shots
12.5xG
0.12xG per shot
5big chances (0.3+ xG)
13goals
#5key passes / game in the league
#1box entries / game in the league
Attacking transition: 23 shots (21%)21%23Settled attack: 61 shots (57%)57%61Set piece: 23 shots (21%)21%23107SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 21% of shots2332.680.12
Cross620.810.14
Cut-back200.120.06
Pass into the box / short pass1401.410.10
Own creation (carry, dribble, rebound)110.330.33
Settled attack 57% of shots6186.640.11
Cross500.660.13
Cut-back820.910.11
Long ball200.180.09
Pass into the box / short pass3863.680.10
Own creation (carry, dribble, rebound)801.220.15
Set piece 21% of shots2323.200.14
Corner2012.350.12
Free kick200.050.03
Penalty110.790.79

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

PlayerSet-upsxG createdGoals
Riccardo Calafiori61.442
Martin Ødegaard131.430
Christos Tzolis80.871
Viktor Gyökeres60.820
Ben White60.733

Who takes them

PlayerShotsxGGoals
Bukayo Saka173.503
Martin Ødegaard141.772
Kai Havertz141.542
Gabriel Magalhães91.131
Riccardo Calafiori90.951
Vision AI Model Insight
The biggest source of Arsenal's chances, by xG, is settled attack (6.6 of 12.5 xG, 61 of 107 shots), mostly pass into the box / short pass. 23 of the 107 shots (21%) came within 15 seconds of winning the ball. 23 of the 107 shots came from set pieces; 13 goals from 12.5 xG (+0.5).

Chance Creation — the pass map

The football question
How does Arsenal 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

3CB · 3%
5Long Central · 6%
29Wide → FB · 33%
51Central · 58%

Sequence success — final-third

122final-third sequences this season
20%succeed — produce a shot
34%turned over with nothing to show

Danger Funnel — which service carries threat

Every key pass pooled by where it was played FROM, then drawn with its arrow width set by total xT rather than by count. A zone that produces a lot of cheap balls shrinks; one that produces a few decisive ones dominates. Where this disagrees with the volume map, the volume map is the misleading one.

0 key passes shown● low threat● mid● high threatarrow width = total xT, not count
CB3 · 3%
right: 2 passes, most from Magalhães2
Long Central5 · 6%
left: 3 passes, most from Saka3right: 2 passes, most from Rice2
Wide → FB29 · 33%
right: 18 passes, most from Ødegaard18left: 11 passes, most from Tzolis11
Central51 · 58%
left: 31 passes, most from Rice31right: 20 passes, most from Madueke20

Who creates — volume × threat

15Rice
14Ødegaard
10Saka
8Tzolis
8Madueke
7White
6Gyökeres
88key passes #5 of 20
21.2box entries/game #1 of 20
42.0final-3rd entries/game #4 of 20
1.56xG/game #6 of 20
13goals #5 of 20
+0.5finishing vs xG #9 of 20
◆ Vision AI Insight
Arsenal lean right — 49% of their key passes come from that flank and its half-space (43 of 88), most often from Ødegaard (9). They funnel chances into the c of the final third, most often via RHS att → C att (15 key passes, most often from White). Rice is the primary source overall. They generate 1.56 xG a game and finish it clinical — they beat their xG, led by Bukayo Saka (3G), Martin Ødegaard (2G), Kai Havertz (2G).

Crosses & Cutbacks — squad-wide

The question
How does Arsenal deliver into the box from wide areas, and what comes of it?

94 crosses: 50 found a team-mate (53%), 10 led to a shot (11%). 48 cut-backs: 25 found a team-mate (52%), 12 led to a shot (25%). 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 Arsenal actually cross from?

94 crosses this season (the same crosses as the map above), split into fifteen territories — five channels (both wings, both half-spaces and the centre) by three depths from the halfway line to the byline. 26% come from one territory, the byline right wing; 7 come from the half-spaces and 0 from the centre.

deep right wing: 8 crosses (9%)9%8deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 1 crosses (1%)1%1deep left wing: 1 crosses (1%)1%1advanced right wing: 20 crosses (21%)21%20advanced right half-space: 0 crosses (0%)advanced centre: 0 crosses (0%)advanced left half-space: 1 crosses (1%)1%1advanced left wing: 12 crosses (13%)13%12byline right wing: 24 crosses (26%)26%24byline right half-space: 3 crosses (3%)3%3byline centre: 0 crosses (0%)byline left half-space: 2 crosses (2%)2%2byline left wing: 22 crosses (23%)23%22
TerritoryCrossesShareLed to a shot
byline · right wing2426%3
byline · left wing2223%3
advanced · right wing2021%1
advanced · left wing1213%2
deep · right wing89%0
byline · right half-space33%1
byline · left half-space22%0
deep · left half-space11%0
deep · left wing11%0
advanced · left half-space11%0
Finishing3 sections

Shot Map

107 shots for 12.5 xG (1.56/game, #6 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

High-volume attack. 13.4 shots/game at 0.117 xG/shot. Box entries 21/game (#1). Threat created 12.8 xT/game (#2).

Goal Sequences

The move behind each of Arsenal’s 13 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 — 13 goals traced.

How Do They Score?

The question
Where do the goals actually come from — open play, dead balls, which foot?

Every goal Arsenal scored across the loaded matches, broken down by how it was created and finished.

By situation

Open play
11 · 85%
Set pieces
1 · 8%
Penalties
1 · 8%

By finish

Right foot
6 · 46%
Left foot
6 · 46%
Header
1 · 8%
Vision AI Model Insight
13 goals scored. 85% come in open play; set pieces add 8%. Open play is clearly their main route to goal.
When they lose it1 section

Ball-Loss Map — where attacks die

Every turnover has a location and a cause. This is a rate, not a raw count — the share of pass attempts from each zone that end in a turnover, so a zone they simply play through more often doesn't automatically look riskier. Grey cells are real zones with too few attempts to trust a rate.

Loss rate by zone

25 of 138 pass attempts lost here (18%).18%25/138White21 of 187 pass attempts lost here (11%).11%21/187Raya78 of 450 pass attempts lost here (17%).17%78/450Raya26 of 165 pass attempts lost here (16%).16%26/165Magalhães36 of 114 pass attempts lost here (32%).32%36/114Magalhães53 of 378 pass attempts lost here (14%).14%53/378White51 of 510 pass attempts lost here (10%).10%51/510White37 of 567 pass attempts lost here (7%).7%37/567Rice44 of 433 pass attempts lost here (10%).10%44/433Magalhães27 of 242 pass attempts lost here (11%).11%27/242Calafiori65 of 398 pass attempts lost here (16%).16%65/398Saka74 of 301 pass attempts lost here (25%).25%74/301Saka22 of 122 pass attempts lost here (18%).18%22/122Havertz45 of 230 pass attempts lost here (20%).20%45/230Eze55 of 249 pass attempts lost here (22%).22%55/249Riceattacking →

How they lose it

Incomplete pass — attacking third
261
Failed forward pass
166
Failed take-on
64
Lost in the defensive third
186
Their weakest zone is the left wing in the defensive third: 32% of 114 pass attempts there are lost (36 times). Separately, 40% 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.

Pressing2 sections

Pressing — the full picture

The football question
How hard does Arsenal 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.

52
Pressing Index
/100 · average
Intensity58
PPDA, high-press share, high-zone actions
Height80
how high up the pitch they defend
Effectiveness30
high recoveries & high-regain share
Disruption48
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
18%
RHS
23%
C
25%
LHS
20%
LW
13%
By third (high / mid / low regain)
Def 44%
Mid 40%
Att 16%
Read
Ranked #5 of 20 for press intensity, this is a high press. 56% of defensive actions happen in the middle & attacking thirds, at an average height of 41. Of recoveries, 53% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#5/20lower = more intense; rank is what matters
Defensive actions / game138#19/20
High-press share25%#5/20def actions won high up
Defensive-action height (0–100)40.9#4/20avg pitch height of actions
High recoveries / game17.9#18/20ball won in mid+att third
High-recovery share53%#10/20share of recoveries won high
Opponent completion allowed76%#2/20lower = more disruptive
Opponent progressive allowed10.2%#19/20of 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 Arsenal win it back with a defensive action?

Counted over the 210 opposition possessions that Arsenal 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 Arsenal step in. Arsenal win it after 4.7 opponent passes in the first half-hour and after 4.4 after the hour mark (sooner).

PASSES THEY GET
4.4passes
median 2 · before Arsenal win it
TIME THEY KEEP IT
13sec
median 5s · 26.2 wins per game
How many passes the opponent got in before the ball was won
52%
23%
14%
11%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
3.9
11s
15–30′
5.7
17s
30–45+′
3.1
9s
45–60′
4.3
12s
60–75′
4.8
15s
75–90+′
4.2
11s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Arsenal 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 Arsenal 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) 1,054 passes

narrow, central, played inside

Width of use-1.0018.94
Wide-channel share-0.940.25
Side bias-0.48-1.65
Pass length-0.3721.36
Long-ball share-0.390.19
Forward gain per pass-0.2310.46
Backward-pass share-0.040.20
Deep-pass share-0.350.25
Completion+0.350.82
Seconds between passes+0.493.62
Side used

left 22% · central 51% · right 27%

Progression (middle third) 2,130 passes

narrow, central, played inside, less recycling

Width of use-1.2922.83
Wide-channel share-1.280.31
Side bias-0.89-3.45
Pass length-0.5616.44
Long-ball share-0.910.07
Forward gain per pass+0.023.64
Backward-pass share-1.050.29
Deep-pass share-0.420.14
Completion+0.820.90
Seconds between passes+0.123.25
Side used

left 28% · central 35% · right 37%

Final third 1,300 passes

safer, shorter passing, kept on the floor

Width of use-0.3330.79
Wide-channel share-0.640.53
Side bias-0.79-6.02
Pass length-1.0413.85
Long-ball share-0.910.06
Forward gain per pass-0.460.43
Backward-pass share+0.480.42
Deep-pass share-0.590.07
Completion+1.210.80
Seconds between passes-0.702.88
Side used

left 35% · central 14% · right 51%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Arsenal'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 Arsenal 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 share19%
#4 of 20 · reaches final third in ≤3 passes
Patient build-up share30%
#6 of 20 · spells of 6+ passes
Tempo (possession length)22.3s
#19 of 20 · shorter = faster tempo
Passes per possession5.2
#4 of 20
Counter-attack shots /game1.02
#11 of 20 · shot within 12s of a regain in own half
Press→shot /game2.98
#8 of 20 · shot within 8s of a high regain
Speed to final third after regain14.6s
#20 of 20 · lower = faster break

Sequence success — attacking transition

9attacking transition sequences this season
11%succeed — produce a shot
11%turned over with nothing to show

Sequence success — defensive transition

24defensive transition sequences this season
79%succeed — reach the next third or a shot
0%turned over with nothing to show
Vision AI Model Insight
Arsenal are balanced between tempo and patience: 19% of possessions reach the final third in 3 passes or fewer (#4 of 20), against 30% built patiently over 6+ passes (#6 of 20). Winning the ball back leads to a shot inside 12 seconds 1.02 times a game (#11), and a high regain converts to a shot within 8 seconds 2.98 times a game (#8 of 20) — a modest but real source of chances.
Defending the box2 sections

Vulnerability Map — how opponents hurt them

The report flipped: where do opponents create their threat against Arsenal? 294 opponent progressive passes and 86 shots faced (6.6 xG against) across the season.

Opponent threat by lane (attacking into Arsenal)

Right wing
22%
Right half-space
9%
Central
29%
Left half-space
13%
Left wing
27%
Where the danger came from. Opponents generated most of their threat through the central (29% of the danger conceded).

How Do They Concede?

The question
Where do the goals against Arsenal actually come from — open play, dead balls, and who supplies them?

Every goal Arsenal conceded across the loaded matches — the opponent's shots in Arsenal'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

← opponent shot at own goal

Every opponent key pass against them (55 total)

2%4%2%2%5%9%4%2%13%16%11%20%11%Ellis SimmsBobby ThomasVictor TorpEmiliano BuendíaRoss BarkleyRoss BarkleyJohn McGinnGranit XhakaKevin DansoEnzo Le FéeGranit XhakaDan BallardEnzo Le FéeGranit XhakaJorrel HatoPedro NetoWesley FofanaJoão PedroReece JamesJoão PedroPedro NetoCole PalmerCharalampos KostoulasDiego GómezFerdi KadiogluAnton StachGabriel GudmundssonJayden BogleEthan AmpaduJayden BogleEthan AmpaduGabriel GudmundssonDiego GómezPascal GroßPascal GroßMaxim De CuyperYasin AyariMalick YalcouyéLiam DelapDaniel MuñozJames McAteeJair CunhaJames McAteeMurilloXaver SchlagerCallum Hudson-OdoiNeco WilliamsMurilloThierno BarryKiernan Dewsbury-HallTyrique GeorgeJames GarnerTyrique GeorgeHarrison ArmstrongTyler Dibling← own goal

By situation

Open play
4 · 80%
Set pieces
1 · 20%
Penalties
0 · 0%
Vision AI Model Insight
5 goals conceded. 80% come in open play; set pieces account for only 20%, so dead-ball defending is not the main issue. 20% 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.

Premium
Tactical Phase Read
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.
Subscribe →

Set-Piece Threat

How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.

Open play
11 g · 9.3 xG
Set pieces
1 g · 2.4 xG
Penalties
1 g
8% of goals come from set pieces (1 of 13), worth 2.4 xG from 22 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Arsenal's corners go?

45 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 (24)

8%8%17%8%8%25%17%8%
Delivered into the box 100%Short 0%

Left side (21)

5%5%10%10%19%33%19%
Delivered into the box 100%Short 0%

Where opponents attack Arsenal from set pieces

13 shots from opponent corners against Arsenal, 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)

38%12%25%25%
Shot 8Goals 1

Left flag (5)

20%20%40%20%
Shot 5Goals 0

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • xG conceded /game — 0.82 (95th pct)
  • box entries /game — 21.25 (95th pct)
  • field tilt % — 64.13 (90th pct)
  • threat created /game — 12.76 (90th pct)
  • pass retention % — 85.30 (85th pct)
Weaknesses (bottom-third vs league)
  • none stand out

Style Archetype & Similar Teams

Team archetype: High-press possession side. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.

Man City
88%
Man Utd
77%
Fulham
74%
Brighton
64%
Tottenham
47%

Performance vs Opponent Styles

The question
Not just how Arsenal 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 Arsenal's own passing behaviour to the result.

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)1.002.001.50
vs mid-block opponents (2m)2.000.503.00
vs low-block opponents (4m)1.750.003.00

Behaviour — how Arsenal actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents83%11%4413.623.5
vs mid-block opponents84%11%3611.120.5
vs low-block opponents87%8%4713.120.5
Vision AI Model Insight
Facing a high press, retention drops to 83% vs 87% against a low block (4pt lower under pressure), and directness (long-ball share) sits at 11% when pressed vs 8% against a low block — a mild adjustment, not a wholesale change.

Scouting Summary — the team in brief

In brief. Arsenal are possession-dominant with a aggressive high-press. Their attack creates 1.56 xG a game and they concede 0.82 a game. [Event-data based — no tracking, so off-ball structure and marking scheme need video.]
Squad

Players

Who drives the numbers.

Against Their Own Norm

For each of ten match numbers, the one match this season that departed furthest from Arsenal’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.

Arsenal
across 8 matches this season
PPDAat Nottingham Forest · 1-0 · 2026-10-182.8avg 4.0
Defensive actionsvs Leeds · 2-1 · 2026-10-10162avg 138
Final-third entriesat Nottingham Forest · 1-0 · 2026-10-1871avg 51
Pass accuracyvs Coventry · 3-0 · 2026-08-2189%avg 85%
Threat from passingat Aston Villa · 1-0 · 2026-08-314.43avg 6.80
Field tiltat Nottingham Forest · 1-0 · 2026-10-1877%avg 64%
Passesat Sunderland · 2-0 · 2026-09-12420avg 560
Expected goalsat Nottingham Forest · 1-0 · 2026-10-180.91avg 1.56

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 Arsenal’s last 8 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).

+14.3on-ball value, 8 matches
Where the value came from
Passes4484 actions+5.43
Carries1108 actions+0.58
Dribbles107 actions-0.10
Shots107 actions+6.41
Ball wins375 actions+1.94
Most on-ball value (OBV)ActionsOBVper 100
Martin Ødegaard698+3.06+0.44
Bukayo Saka412+2.62+0.64
Declan Rice842+1.34+0.16
Riccardo Calafiori339+0.99+0.29
Noni Madueke190+0.96+0.51
Ben White436+0.88+0.20
Christos Tzolis236+0.72+0.31
Gabriel Magalhães601+0.70+0.12
123456
Biggest single movesOBV
1  Martin Ødegaard · shot+0.718
2  Bukayo Saka · shot+0.703
3  Riccardo Calafiori · pass+0.439
4  Ben White · pass+0.335
5  Riccardo Calafiori · pass+0.305
6  Bukayo Saka · shot+0.292

Set Pieces by Player

Who delivers Arsenal’s dead balls and who finishes them this season. 45 corners taken, most by Declan Rice (21); 22 shots from corners and free kicks, 1 goals, led by Ezri Konsa (1 goals, 0.84 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.

PlayerCorners takenInto the boxSet-piece shotsGoalsxGFree-kick shotsPenalties
Bukayo Saka1814 (78%)1—0.06—1/1
Declan Rice2120 (95%)1—0.03——
Martin Ødegaard55 (100%)3—0.081—
Gabriel Magalhães——4—0.51——
Riccardo Calafiori——3—0.17——
Ezri Konsa——310.84——
Christos Tzolis——2—0.10——
Kai Havertz——2—0.26——
Eberechi Eze——1—0.021—
Martín Zubimendi——1—0.08——
Mikel Merino——1—0.25——
Max Dowman11 (100%)——0.00——

Top Performers

Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 216 minutes). Coloured chips are that player's strongest capability blocks.

playerposminVision AI Scorecapability blocks
Declan RiceCM6888.1Progression 79%Ball-Carrying 77%Successful Dribble 58%Chance Creation 48%
Gabriel MagalhãesCB7676.8Ball-Carrying 45%Progression 44%Ball-Winning 34%Aerial & Box Defending 32%
Bukayo SakaW6216.1Box Threat 76%Chance Creation 46%Wide Delivery 43%Ball-Carrying 40%
Ben WhiteFB5575.8Ball-Winning 60%Wide Delivery 48%Ball-Carrying 26%
David RayaGK7675.6Shot-Stopping 56%
Riccardo CalafioriFB6445.6Ball-Winning 57%Ball-Carrying 57%Wide Delivery 22%
Martin ØdegaardAM6574.4Chance Creation 62%Ball-Carrying 59%Box Threat 18%
Kai HavertzST6223.9Ball-Carrying 43%Box Threat 35%Finishing 29%Aerial Threat 0%
Ezri KonsaCB5953.5Ball-Carrying 78%Progression 38%Ball-Winning 20%Aerial & Box Defending 7%

Top Creators

Chance creation leaders — key passes /90 and box entries.

playerposminkey P /90box entriesxT
Martin ØdegaardM6571.923212.7
Declan RiceM6881.962116.3
Bukayo SakaM6211.45226.2
Christos TzolisM3661.97144.0
Noni MaduekeM2732.64122.7
Ben WhiteD5571.13119.0
Kai HavertzF6220.72102.8
Riccardo CalafioriD6440.7074.7

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.

playerposmincrosses (completed)cutbacks (completed)
Ben WhiteFB5579 (33%)9 (78%)
Christos TzolisW3664 (75%)8 (75%)
Bukayo SakaW6211 (0%)7 (57%)
Riccardo CalafioriFB6441 (100%)6 (33%)

Defensive Volume Leaders

Who does the defensive work — tackles, interceptions, recoveries.

playerposmindef actionstacklesinterceptrecoveries
Gabriel MagalhãesD76714910924
Ezri KonsaD59510710821
Bukayo SakaM6219211423
Declan RiceM6889110827
Kai HavertzF62281138
Riccardo CalafioriD644789516
Ben WhiteD5577510319
Martin ØdegaardM657556222

Full Squad Data

Every player with 100+ minutes (19 players).

playerposappsmingoalsxGkey PprogdefxT
David RayaG876700.0036239.4
Gabriel MagalhãesD876711.12261498.9
Declan RiceM868800.315439116.3
Martin ØdegaardM865721.814385512.7
Riccardo CalafioriD864411.0518784.7
Kai HavertzF862221.556812.8
Bukayo SakaM762133.51028926.2
Ezri KonsaD759510.8171074.9
Ben WhiteD755700.1742759.0
Myles Lewis-SkellyM640400.2313515.2
Christos TzolisM536600.3825484.0
Noni MaduekeM527310.5813222.7
Bruno GuimarãesM627020.2110553.4
Eberechi EzeM623900.119271.3
Mikel MerinoM821800.7011452.6
Jurriën TimberD417300.0111233.1
Cristhian MosqueraD217200.001191.4
Viktor GyökeresF516900.163221.4
Martín ZubimendiM614400.204301.4

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.

David Raya
Goalkeeper · Goalkeeper
minutes767
goals · xG0 · 0.0
prog passes /904.2
key passes /900.00
def actions /902.7
pass accuracy73%
Gabriel Magalhães
Stopper / marker · Defender
minutes767
goals · xG1 · 1.1
prog passes /903.1
key passes /900.23
def actions /9017.5
pass accuracy89%
Declan Rice
Advanced creator · Attacking mid
minutes688
goals · xG0 · 0.3
prog passes /905.6
key passes /901.96
def actions /9011.9
pass accuracy88%
Martin Ødegaard
Advanced creator · Attacking mid
minutes657
goals · xG2 · 1.8
prog passes /905.2
key passes /901.92
def actions /907.5
pass accuracy88%
Riccardo Calafiori
Stopper / marker · Defender
minutes644
goals · xG1 · 1.0
prog passes /902.5
key passes /900.70
def actions /9010.9
pass accuracy83%
Kai Havertz
Ball-winner / destroyer · Midfielder
minutes622
goals · xG2 · 1.5
prog passes /900.9
key passes /900.72
def actions /9011.7
pass accuracy79%
Bukayo Saka
Poacher / finisher · Forward
minutes621
goals · xG3 · 3.5
prog passes /904.1
key passes /901.45
def actions /9013.3
pass accuracy76%
Ezri Konsa
Stopper / marker · Defender
minutes595
goals · xG1 · 0.8
prog passes /901.1
key passes /900.15
def actions /9016.2
pass accuracy96%
Ben White
Ball-playing defender · Defender
minutes557
goals · xG0 · 0.1
prog passes /906.8
key passes /901.13
def actions /9012.1
pass accuracy81%

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 — below-average: shots /game (40th pct)
Sign a shot-taking forward to raise shot volume. The data flags this because shot volume is low (13.38, 40th percentile vs the league).
Vision AI · building report