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Team reportPremier League 2026

Sunderland

A balanced-territory side, aggressive high-press out of possession, with a moderate attack. Currently #20 of 20 on 5 points (1-2-5, 6:14). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

balanced-territoryaggressive high-pressmoderate attack
W
L
L
D
D
W
W
L
W
D
L
L
L
L
D
5
points
#20 of 20 · 8 games
6:14
goals
-8 GD
1-2-5
record
W-D-L
0.62
points/game
#20 in the league
1.41
xG for/game
rank #9
1.44
xG against/game
rank #15
#9
press rank
of 20 · most aggressive
48%
field tilt
#10
Sunderland
League average
Expected goals for / game
1.411.33
Expected goals against / game
1.441.33
Field tilt
48%50%
Pass retention
76%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 Sunderland and how good was the season?
Read. Sunderland currently sit #20 of 20 on 5 points (1W-2D-5L, 0.62 pts/game), scoring 6 and conceding 14 for a goal difference of -8. On the ball they are a balanced-territory team (48% field tilt, #10 in the league); off it they defend with a aggressive high-press (#9 of 20 for press intensity). Across the 8 matches of event data, they create 1.41 xG/game (#9) and concede 1.44 (#15), a net of -0.03 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

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

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

#teamPWDLGFGAGDPts
17Crystal Palace8215919-107
18Nottingham Forest8134610-46
19Coventry8206615-96
20Sunderland8125614-85

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Sunderland 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+'+1.74-1.80
Vision AI Model Insight
Sunderland tend to stay fairly even across both halves — first-half net xG -0.01, second-half -0.22. Their strongest period is 61-75' (net +1.74 xG); their most dangerous period to face is 76-90+' (net -1.80 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Sunderland 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 (-0.2 xG). Hover a point for that match.

0481211.311.5Ipswich (A) 1-2 · xG 0.82 to 1.10Fulham (H) 1-0 · xG 1.28 to 0.89Brentford (A) 1-1 · xG 2.11 to 1.13Arsenal (H) 0-2 · xG 1.81 to 1.64Man City (A) 3-5 · xG 3.06 to 2.44Brighton (H) 0-2 · xG 1.07 to 0.91Bournemouth (A) 0-2 · xG 0.12 to 2.67Leeds (H) 0-0 · xG 0.98 to 0.70M1M2M3M4M5M6M7M8
SunderlandOpponents against Sunderland

Tactical DNA

The football question
In five genes, what is Sunderland'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.

35
Build-Up
possession control from the back
42
Progression
moving the ball upfield with threat
42
Creation
manufacturing chances
52
Press
winning the ball high & hard
25
Solidity
resisting the opponent's threat
Genetic identity
Sunderland are defined most by their Press DNA (52/100 · average at winning the ball high & hard), and least by their Solidity DNA (25/100). 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).

Possess36Disrupt22Finish36Press26Defend35
Possess
Deep buildup
52%
Possession
30%
Field tilt
26%
Disrupt
Central progression ~proxy
22%
Dribble tendency
35%
Progressive passes
9%
Finish
Final-third patience
52%
Shot quality
35%
Open-play xG
22%
Press
Forward press ~proxy
43%
High regains
17%
Pressing efficiency ~proxy
17%
Defend
Def-mid press ~proxy
26%
High line ~proxy
35%
PAdj defensive actions
43%
Sunderland is defined most by Finish (36% in the league) and weakest on Disrupt (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.

Keeping the ball6 sections

Field Tilt — Territorial Control

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

Field tilt = share of final-third touches between the two sides across Sunderland'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; Sunderland 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/gSunderland33%44%55%66%0.61.32.02.6FIELD TILT %POINTS / GAME
Vision AI Model Insight
Sunderland post 48% field tilt, ranking #10 of 20 in the league — comfortably above the league mid-point for territorial control, and their 0.62 points/game sits below the league-average return — territory is genuinely converting into results.

Where the time goes — how long each phase lasts

The question
When Sunderland has the ball, how much of that time is spent building, progressing and creating?

The share of Sunderland'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: 30.3% of the time on the ball30%Progression: 43.7% of the time on the ball44%Chance creation: 23.9% of the time on the ball24%Attacking transition: 2.1% of the time on the ball44%PROGRESSION
PhaseShare of the time
Build-up30.3%
Progression43.7%
Chance creation23.9%
Attacking transition2.1%
Vision AI Model Insight
Progression is where Sunderland spends most of its time on the ball (44% 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.

Granit Xhaka ↔ Noah Sadiki: 80 passes, 0.1 combined xTGranit Xhaka ↔ Enzo Le Fée: 72 passes, 1.3 combined xTReinildo Mandava ↔ Noah Sadiki: 71 passes, -0.6 combined xTGranit Xhaka ↔ Reinildo Mandava: 69 passes, 0.1 combined xTKevin Danso ↔ Robin Roefs: 63 passes, -0.3 combined xTGranit Xhaka ↔ Robin Roefs: 59 passes, -0.1 combined xTEnzo Le Fée ↔ Noah Sadiki: 58 passes, 1.1 combined xTGranit Xhaka ↔ Nordi Mukiele: 53 passes, 1.8 combined xTReinildo Mandava ↔ Dan Ballard: 43 passes, -0.5 combined xTReinildo Mandava ↔ Nilson Angulo: 42 passes, 0.9 combined xTNoah Sadiki ↔ Nilson Angulo: 42 passes, -0.3 combined xTGranit Xhaka ↔ Thomas Meunier: 40 passes, 0.2 combined xTGranit Xhaka ↔ Kevin Danso: 40 passes, -0.1 combined xTGranit Xhaka ↔ Dan Ballard: 39 passes, 0.9 combined xTGranit Xhaka ↔ Trai Hume: 39 passes, 1.3 combined xTDan Ballard ↔ Robin Roefs: 39 passes, -0.4 combined xTNordi Mukiele ↔ Kevin Danso: 36 passes, 0.4 combined xTThomas Meunier ↔ Nordi Mukiele: 34 passes, -0.1 combined xTNordi Mukiele ↔ Robin Roefs: 31 passes, 0.1 combined xTThomas Meunier ↔ Dan Ballard: 29 passes, 0.2 combined xTLuke O'Nien ↔ Reinildo Mandava: 29 passes, 0.0 combined xTRobin Roefs ↔ Noah Sadiki: 29 passes, -1.3 combined xTThomas Meunier ↔ Enzo Le Fée: 28 passes, 0.1 combined xTNordi Mukiele ↔ Enzo Le Fée: 28 passes, 1.0 combined xTGranit Xhaka — isolate this player's connectionsXhakaEnzo Le Fée — isolate this player's connectionsFéeRobin Roefs — isolate this player's connectionsRoefsNoah Sadiki — isolate this player's connectionsSadikiNilson Angulo — isolate this player's connectionsAnguloTrai Hume — isolate this player's connectionsHumeReinildo Mandava — isolate this player's connectionsMandavaNordi Mukiele — isolate this player's connectionsMukieleThomas Meunier — isolate this player's connectionsMeunierBrian Brobbey — isolate this player's connectionsBrobbeyKevin Danso — isolate this player's connectionsDansoDan Ballard — isolate this player's connectionsBallardMalick Fofana — isolate this player's connectionsFofanaWilson Isidor — isolate this player's connectionsIsidorOmar Alderete — isolate this player's connectionsAldereteLuke O'Nien — isolate this player's connectionsO'Nien
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Xhaka ↔ Sadiki
80p · 0.1xT
Xhaka ↔ Fée
72p · 1.3xT
Mandava ↔ Sadiki
71p · -0.6xT
Xhaka ↔ Mandava
69p · 0.1xT
Danso ↔ Roefs
63p · -0.3xT
Xhaka ↔ Roefs
59p · -0.1xT
Fée ↔ Sadiki
58p · 1.1xT
Xhaka ↔ Mukiele
53p · 1.8xT
Mandava ↔ Ballard
43p · -0.5xT
Mandava ↔ Angulo
42p · 0.9xT
Vision AI Model Insight
Busiest connection: Granit Xhaka ↔ Noah Sadiki (80 passes). Most dangerous per pass: Nordi Mukiele ↔ Enzo Le Fée (0.04 xT/pass over 28 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Sunderland 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 Sunderland 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
3536
ACTIONS
4%5%11%5%6%8%8%10%9%11%7%4%3%3%6%PASSES
Carries
the ball moved with a player
708
ACTIONS
3%7%11%8%4%9%9%10%9%9%6%3%2%2%6%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (11.2% of all actions). 59% of actions run through the inside lanes (centre + both half-spaces) versus 41% down the two wings — an inside-dominant, half-space build. By third: 32% defensive, 46% 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. Sunderland leaned on their left (39%). The bars under the pitch put the league’s share beside theirs.

39%Left side23%Middle38%Right sideATTACKING →
Sunderland
39%23%38%
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. Sunderland made 309 this season (38.6 a match); 35% 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.

Left wing: 107 entries (35%)10735%LEFT WINGLeft half-space: 37 entries (12%)3712%LEFT HALF-SPACECentre: 41 entries (13%)4113%CENTRERight half-space: 44 entries (14%)4414%RIGHT HALF-SPACERight wing: 80 entries (26%)8026%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing10713.435%31%
Left half-space374.612%16%
Centre415.113%13%
Right half-space445.514%14%
Right wing8010.026%27%
Build-up2 sections

Build-Up — the pass map

The football question
How does Sunderland 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.

1121build-up passes attempted
74%completed
27%reach the middle third
2%go long into the final third

Pass types

366CB · 44%
57Long Wide · 7%
13Long Central · 2%
302Wide → FB · 36%
95Central · 11%

Sequence success — build-up

73build-up sequences this season
8%succeed — reach the next third or a shot
34%turned over with nothing to show
CB366 · 44%
left: 214 passes, most from Mandava214right: 152 passes, most from Mukiele152
Long Wide57 · 7%
right: 36 passes, most from Roefs36left: 21 passes, most from Roefs21
Long Central13 · 2%
right: 11 passes, most from Roefs11left: 2 passes, most from Roefs2
Wide → FB302 · 36%
left: 155 passes, most from Roefs155right: 147 passes, most from Roefs147
Central95 · 11%
left: 56 passes, most from Roefs56right: 39 passes, most from Roefs39
◆ Vision AI Insight
Sunderland build predominantly down the right, with Roefs as the fulcrum (213 build-up passes). Only 29% of their build-up passes actually advance a third — the rest is lateral circulation, the hallmark of a possession-controlling side that circulates patiently in midfield before progressing. Their single most-repeated pattern is C def → LHS def (44×).

Pass Explorer

Every pass of Sunderland’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. 318 progressive passes across 8 matches (39.8/game).

Origin lane

Right wing
32%
Right half-space
12%
Central
17%
Left half-space
12%
Left wing
27%
Progression is right-dominant: 44% right side · 17% central · 39% left.

Who generates it

Granit Xhaka
60 · 19%
Nordi Mukiele
42 · 13%
Robin Roefs
34 · 11%
Enzo Le Fée
33 · 10%
Reinildo Mandava
27 · 8%
Top two — Granit Xhaka & Nordi Mukiele — account for 32% of all progression.
PROGRESSION
39.8 prog passes/game
mostly right
→
PENETRATION
33% reach final third
25% reach the box
→
THREAT
the other 67% is recycled
progress ≠ danger
What came of it. 33% of progressive passes reached the final third and 25% the box; the rest was recycled in front of the block. 32% 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 wingsterile

Progression — the pass map

The football question
Once Sunderland 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.

1605progression passes attempted
81%completed
19%break into the final third
14%go backward into the defensive third

Pass types

486CB · 37%
62Long Wide · 5%
14Long Central · 1%
575Wide → FB · 44%
164Central · 13%

Sequence success — progression

97progression sequences this season
19%succeed — reach the next third or a shot
44%turned over with nothing to show
CB486 · 37%
left: 303 passes, most from Mandava303right: 183 passes, most from Mukiele183
Long Wide62 · 5%
right: 38 passes, most from Xhaka38left: 24 passes, most from Xhaka24
Long Central14 · 1%
left: 7 passes, most from Xhaka7right: 7 passes, most from Xhaka7
Wide → FB575 · 44%
left: 298 passes, most from Xhaka298right: 277 passes, most from Xhaka277
Central164 · 13%
left: 87 passes, most from Xhaka87right: 77 passes, most from Xhaka77
◆ Vision AI Insight
Sunderland progress predominantly down the left, with Xhaka the busiest midfield outlet (257 progression passes). Only 19% of passes that start in midfield actually break the final-third line — the rest (67%) is recycled back into midfield or (14%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LW mid → LHS mid (77×) — 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
50%
Safe / backward
36%
14% of passes are progressive-or-better; the remaining 86% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.

Carries Map — progressive ball-carries, squad-wide

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

163 progressive carries this season across the whole squad (23% of 708 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 16m, longest 43m. Most active carrier: Mukiele (24). Filter to one player below.

First (56)Second (48)Third (30)Fourth (29)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 Sunderland'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.

96shots
11.3xG
0.12xG per shot
9big chances (0.3+ xG)
6goals
#15key passes / game in the league
#12box entries / game in the league
Attacking transition: 13 shots (14%)14%13Settled attack: 62 shots (65%)65%62Set piece: 21 shots (22%)22%2196SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 14% of shots1301.780.14
Pass into the box / short pass801.430.18
Own creation (carry, dribble, rebound)500.350.07
Settled attack 65% of shots6246.500.10
Cross1011.080.11
Cut-back600.930.15
Long ball411.270.32
Pass into the box / short pass2822.160.08
Own creation (carry, dribble, rebound)1401.050.08
Set piece 22% of shots2122.970.14
Corner1401.250.09
Free kick510.130.03
Penalty211.590.79

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
Enzo Le Fée121.971
Granit Xhaka141.891
Brian Brobbey30.520
Noah Sadiki80.500
Thomas Meunier20.381

Who takes them

PlayerShotsxGGoals
Brian Brobbey133.033
Enzo Le Fée142.171
Wilson Isidor71.061
Nordi Mukiele90.870
Noah Sadiki70.740
Vision AI Model Insight
The biggest source of Sunderland's chances, by xG, is settled attack (6.5 of 11.3 xG, 62 of 96 shots), mostly pass into the box / short pass. 13 of the 96 shots (14%) came within 15 seconds of winning the ball. 21 of the 96 shots came from set pieces; 6 goals from 11.3 xG (-5.3).

Chance Creation — the pass map

The football question
How does Sunderland 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

13CB · 20%
1Long Wide · 2%
6Long Central · 9%
14Wide → FB · 22%
31Central · 48%

Sequence success — final-third

57final-third sequences this season
33%succeed — produce a shot
33%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
CB13 · 20%
left: 7 passes, most from Mandava7right: 6 passes, most from Danso6
Long Wide1 · 2%
Long Central6 · 9%
left: 4 passes, most from Xhaka4right: 2 passes, most from Xhaka2
Wide → FB14 · 22%
right: 10 passes, most from Xhaka10left: 4 passes, most from Brobbey4
Central31 · 48%
right: 16 passes, most from Xhaka16left: 15 passes, most from Fée15

Who creates — volume × threat

17Xhaka
15Fée
8Sadiki
5Danso
4Hume
4Mandava
3Brobbey
65key passes #15 of 20
12.1box entries/game #12 of 20
32.4final-3rd entries/game #12 of 20
1.41xG/game #9 of 20
6goals #18 of 20
-5.3finishing vs xG #19 of 20
◆ Vision AI Insight
Sunderland lean right — 38% of their key passes come from that flank and its half-space (25 of 65), most often from Xhaka (7). They funnel chances into the c of the final third, most often via LW att → C att (9 key passes, most often from Fée). Xhaka is the primary source overall. They generate 1.41 xG a game and finish it wasteful — they under-perform their xG, led by Brian Brobbey (3G), Nilson Angulo (1G), Wilson Isidor (1G).

Crosses & Cutbacks — squad-wide

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

132 crosses: 43 found a team-mate (33%), 11 led to a shot (8%). 15 cut-backs: 7 found a team-mate (47%), 7 led to a shot (47%). 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 Sunderland actually cross from?

132 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. 29% come from one territory, the advanced right wing; 9 come from the half-spaces and 0 from the centre.

deep right wing: 11 crosses (8%)8%11deep right half-space: 1 crosses (1%)1%1deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 10 crosses (8%)8%10advanced right wing: 38 crosses (29%)29%38advanced right half-space: 3 crosses (2%)2%3advanced centre: 0 crosses (0%)advanced left half-space: 0 crosses (0%)advanced left wing: 19 crosses (14%)14%19byline right wing: 28 crosses (21%)21%28byline right half-space: 2 crosses (2%)2%2byline centre: 0 crosses (0%)byline left half-space: 3 crosses (2%)2%3byline left wing: 17 crosses (13%)13%17
TerritoryCrossesShareLed to a shot
advanced · right wing3829%3
byline · right wing2821%2
advanced · left wing1914%3
byline · left wing1713%1
deep · right wing118%1
deep · left wing108%0
advanced · right half-space32%1
byline · left half-space32%0
byline · right half-space22%0
deep · right half-space11%0
Finishing3 sections

Shot Map

96 shots for 11.3 xG (1.41/game, #9 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

Moderate attack. 12.0 shots/game at 0.117 xG/shot. Box entries 12/game (#12). Threat created 10.0 xT/game (#11).

Goal Sequences

The move behind each of Sunderland’s 6 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 — 6 goals traced.

How Do They Score?

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

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

By situation

Open play
4 · 67%
Set pieces
1 · 17%
Penalties
1 · 17%

By finish

Right foot
6 · 100%
Left foot
0 · 0%
Header
0 · 0%
Vision AI Model Insight
6 goals scored. 67% come in open play; set pieces add 17%. 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

48 of 150 pass attempts lost here (32%).32%48/150Mukiele26 of 175 pass attempts lost here (15%).15%26/175Roefs97 of 396 pass attempts lost here (24%).24%97/396Roefs47 of 186 pass attempts lost here (25%).25%47/186Roefs70 of 214 pass attempts lost here (33%).33%70/214Mandava63 of 279 pass attempts lost here (23%).23%63/279Mukiele65 of 286 pass attempts lost here (23%).23%65/286Xhaka65 of 355 pass attempts lost here (18%).18%65/355Xhaka40 of 309 pass attempts lost here (13%).13%40/309Xhaka71 of 376 pass attempts lost here (19%).19%71/376Mandava88 of 249 pass attempts lost here (35%).35%88/249Mukiele49 of 124 pass attempts lost here (40%).40%49/124Hume27 of 100 pass attempts lost here (27%).27%27/100Fée42 of 123 pass attempts lost here (34%).34%42/123Angulo50 of 214 pass attempts lost here (23%).23%50/214Féeattacking →

How they lose it

Incomplete pass — attacking third
256
Failed forward pass
188
Failed take-on
72
Lost in the defensive third
288
Their weakest zone is the right half-space in the attacking third: 40% of 124 pass attempts there are lost (49 times). Separately, 30% 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 Sunderland 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.

46
Pressing Index
/100 · average
Intensity62
PPDA, high-press share, high-zone actions
Height60
how high up the pitch they defend
Effectiveness22
high recoveries & high-regain share
Disruption45
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
14%
RHS
23%
C
25%
LHS
21%
LW
17%
By third (high / mid / low regain)
Def 46%
Mid 37%
Att 17%
Read
Ranked #9 of 20 for press intensity, this is a high press. 54% of defensive actions happen in the middle & attacking thirds, at an average height of 40. Of recoveries, 50% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#9/20lower = more intense; rank is what matters
Defensive actions / game163#7/20
High-press share24%#8/20def actions won high up
Defensive-action height (0–100)39.7#8/20avg pitch height of actions
High recoveries / game18.5#15/20ball won in mid+att third
High-recovery share50%#16/20share of recoveries won high
Opponent completion allowed78%#7/20lower = more disruptive
Opponent progressive allowed9.4%#15/20of 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 Sunderland win it back with a defensive action?

Counted over the 239 opposition possessions that Sunderland 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 Sunderland step in. Sunderland win it after 6.2 opponent passes in the first half-hour and after 3.9 after the hour mark (sooner).

PASSES THEY GET
4.8passes
median 3 · before Sunderland win it
TIME THEY KEEP IT
15sec
median 7s · 29.9 wins per game
How many passes the opponent got in before the ball was won
45%
27%
11%
17%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.3
20s
15–30′
6.0
18s
30–45+′
5.1
18s
45–60′
3.8
10s
60–75′
4.3
13s
75–90+′
3.7
10s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Sunderland 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 Sunderland 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) 1,121 passes

nothing unusual in this zone

Width of use+0.6522.34
Wide-channel share+0.430.33
Side bias+0.682.70
Pass length+0.2923.76
Long-ball share+0.420.27
Forward gain per pass+0.2612.59
Backward-pass share+0.330.21
Deep-pass share+0.340.32
Completion-0.740.73
Seconds between passes+0.083.38
Side used

left 33% · central 42% · right 25%

Progression (middle third) 1,605 passes

slower, more direct

Width of use+0.2826.16
Wide-channel share+0.210.42
Side bias+0.682.75
Pass length+0.6018.06
Long-ball share+0.930.14
Forward gain per pass+0.614.53
Backward-pass share+0.120.34
Deep-pass share+0.820.20
Completion-0.670.80
Seconds between passes+0.973.62
Side used

left 38% · central 31% · right 31%

Final third 810 passes

nothing unusual in this zone

Width of use-0.0031.60
Wide-channel share-0.030.58
Side bias-0.27-2.38
Pass length+0.3315.97
Long-ball share+0.580.13
Forward gain per pass-0.250.70
Backward-pass share+0.260.40
Deep-pass share+0.010.09
Completion-0.200.68
Seconds between passes+0.143.50
Side used

left 39% · central 16% · right 44%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Sunderland'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 Sunderland win or lose the ball, what actually happens in the seconds after?

Reconstructed from the full timestamped event stream: real possession spells (not zone-clustered), and shots that follow a regain within a fixed window. This phase of play needs ordered, per-event timestamps — which every match here carries.

Direct play share17%
#11 of 20 · reaches final third in ≤3 passes
Patient build-up share23%
#14 of 20 · spells of 6+ passes
Tempo (possession length)17.4s
#10 of 20 · shorter = faster tempo
Passes per possession4.0
#15 of 20
Counter-attack shots /game0.67
#17 of 20 · shot within 12s of a regain in own half
Press→shot /game2.57
#17 of 20 · shot within 8s of a high regain
Speed to final third after regain13.4s
#14 of 20 · lower = faster break

Sequence success — attacking transition

7attacking transition sequences this season
29%succeed — produce a shot
57%turned over with nothing to show

Sequence success — defensive transition

28defensive transition sequences this season
71%succeed — reach the next third or a shot
4%turned over with nothing to show
Vision AI Model Insight
Sunderland are a direct, fast-break side: 17% of possessions reach the final third in 3 passes or fewer (#11 of 20), against 23% built patiently over 6+ passes (#14 of 20). Winning the ball back leads to a shot inside 12 seconds 0.67 times a game (#17), and a high regain converts to a shot within 8 seconds 2.57 times a game (#17 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 Sunderland? 350 opponent progressive passes and 113 shots faced (11.5 xG against) across the season.

Opponent threat by lane (attacking into Sunderland)

Right wing
29%
Right half-space
10%
Central
17%
Left half-space
14%
Left wing
30%
Where the danger came from. Opponents generated most of their threat through the left wing (30% of the danger conceded).

How Do They Concede?

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

Every goal Sunderland conceded across the loaded matches — the opponent's shots in Sunderland'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 (73 total)

3%4%4%3%15%22%23%16%10%EmersonnDara O'SheaJulio EncisoDara O'SheaEmersonnAbdul FatawuAbdul FatawuSamuel AmissahAbdoul OuattaraSaša LukicSander BergeOscar BobbSander BergeEmile Smith RoweSaša LukicJoachim AndersenMartin ØdegaardDeclan RiceDeclan RiceMartin ØdegaardMartin ØdegaardDeclan RiceMartin ØdegaardMartin ØdegaardBukayo SakaKai HavertzMikkel DamsgaardKeane Lewis-PotterDango OuattaraKeane Lewis-PotterMikkel DamsgaardKevin SchadeKeane Lewis-PotterIliman NdiayeAntoine SemenyoIliman NdiayeRayan CherkiEnzo FernándezAntoine SemenyoRayan CherkiAntoine SemenyoJosko GvardiolJérémy DokuPascal GroßCharalampos KostoulasOlivier BoscagliPascal GroßDiego GómezGeorginio RutterHarry WilsonHarry WilsonBrenden AaronsonJayden BogleEthan AmpaduNoah OkaforJames JustinLewis CookEvanilsonAntónio SilvaMarcus TavernierRyan ChristieJames HillLewis CookAdam SmithMarcus TavernierAdam SmithAdrien TruffertRyan ChristieRyan ChristieLewis CookRyan ChristieRayanBen Gannon-Doak← own goal

By situation

Open play
11 · 79%
Set pieces
2 · 14%
Penalties
1 · 7%
Vision AI Model Insight
14 goals conceded. 79% come in open play; set pieces account for only 14%, so dead-ball defending is not the main issue. 7% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre of the attacking third (23% 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
4 g · 8.3 xG
Set pieces
1 g · 1.4 xG
Penalties
1 g
17% of goals come from set pieces (1 of 6), worth 1.4 xG from 19 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Sunderland's corners go?

34 corners taken this season, split by which flag they were taken from — arrows from the flag, dots at the delivery point, shaded by % of that side's corners landing in each zone (same treatment as the concede map below). No swing-direction (inswinger/outswinger) data is recorded here, only a start and end point per pass, which cannot show how the ball curved — so this shows what is genuinely knowable: where it lands, and short vs actually delivered. Tap or hover a dot for who took it and the match; filter to one match below and the shading recomputes for just that game.

Right side (17)

6%6%6%35%24%6%
Delivered into the box 82%Short 18%

Left side (17)

6%18%18%12%12%12%12%
Delivered into the box 88%Short 12%

Where opponents attack Sunderland from set pieces

21 shots from opponent corners against Sunderland, 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 (6)

17%17%33%33%
Shot 6Goals 0

Left flag (15)

7%7%7%47%13%20%
Shot 15Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • none stand out
Weaknesses (bottom-third vs league)
  • pass retention % — 76.02 (20th pct)
  • xG conceded /game — 1.44 (25th pct)
  • shots /game — 12.00 (30th 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.

Leeds
80%
Hull City
60%
Brentford
50%
Coventry
44%
Crystal Palace
39%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)0.501.500.50
vs mid-block opponents (2m)0.501.001.50
vs low-block opponents (4m)1.002.250.25

Behaviour — how Sunderland actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents68%21%399.613.0
vs mid-block opponents78%19%369.813.5
vs low-block opponents78%15%4210.411.0
Vision AI Model Insight
Facing a high press, retention drops to 68% vs 78% against a low block (10pt lower under pressure), and directness (long-ball share) sits at 21% when pressed vs 15% 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. Sunderland are balanced-territory with a aggressive high-press. Their attack creates 1.41 xG a game and they concede 1.44 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 Sunderland’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.

Sunderland
across 8 matches this season
PPDAat Brentford · 1-1 · 2026-09-052.9avg 4.5
Pass accuracyat Bournemouth · 0-2 · 2026-10-1862%avg 75%
Expected goalsat Man City · 3-5 · 2026-09-203.06avg 1.41
Defensive actionsat Brentford · 1-1 · 2026-09-05195avg 163
Progressive carriesat Ipswich · 1-2 · 2026-08-2257avg 33
Passesat Ipswich · 1-2 · 2026-08-22613avg 442
Field tiltvs Brighton · 0-2 · 2026-10-1071%avg 48%
Threat from passingat Brentford · 1-1 · 2026-09-057.27avg 5.30

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 Sunderland’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).

+11.7on-ball value, 8 matches
Where the value came from
Passes3536 actions+3.19
Carries708 actions+0.36
Dribbles131 actions+0.00
Shots96 actions+6.26
Ball wins435 actions+1.85
Most on-ball value (OBV)ActionsOBVper 100
Enzo Le Fée376+3.08+0.82
Granit Xhaka689+1.44+0.21
Brian Brobbey124+1.00+0.81
Dan Ballard287+0.86+0.30
Robin Roefs413+0.83+0.20
Noah Sadiki453+0.81+0.18
Nilson Angulo218+0.71+0.32
Nordi Mukiele422+0.69+0.16
123456
Biggest single movesOBV
1  Enzo Le Fée · shot+0.798
2  Enzo Le Fée · shot+0.756
3  Enzo Le Fée · pass_fail+0.437
4  Brian Brobbey · shot+0.416
5  Enzo Le Fée · pass+0.386
6  Dan Ballard · shot+0.386

Set Pieces by Player

Who delivers Sunderland’s dead balls and who finishes them this season. 34 corners taken, most by Granit Xhaka (19); 19 shots from corners and free kicks, 1 goals, led by Nilson Angulo (1 goals, 0.19 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
Granit Xhaka1914 (74%)2—0.052—
Enzo Le Fée1210 (83%)2—0.0511/2
Luke O'Nien——3—0.15——
Nilson Angulo——310.191—
Trai Hume21 (50%)2—0.10——
Nordi Mukiele——2—0.36——
Kevin Danso——2—0.39——
Noah Sadiki——1—0.04——
Brian Brobbey——1—0.04——
Wilson Isidor——1—0.031—
Chemsdine Talbi11 (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
Nordi MukieleCB6276.6Ball-Winning 83%Ball-Carrying 78%Progression 56%Aerial & Box Defending 48%
Robin RoefsGK7666.5Shot-Stopping 65%
Granit XhakaCM7665.8Progression 73%Chance Creation 65%Successful Dribble 48%Ball-Carrying 48%
Dan BallardCB4775.8Ball-Carrying 64%Ball-Winning 46%Aerial & Box Defending 41%Progression 22%
Enzo Le FéeAM7114.8Box Threat 77%Chance Creation 46%Ball-Carrying 20%
Reinildo MandavaCB6463.8Ball-Winning 72%Aerial & Box Defending 38%Progression 25%Ball-Carrying 19%
Kevin DansoCB4823.4Ball-Carrying 57%Ball-Winning 56%Progression 53%Aerial & Box Defending 37%
Noah SadikiCM7153.3Successful Dribble 92%Ball-Carrying 72%Progression 29%Chance Creation 9%
Brian BrobbeyST4822.4Finishing 63%Box Threat 32%Ball-Carrying 8%Aerial Threat 0%
Nilson AnguloW4631.9Ball-Carrying 46%Box Threat 14%Chance Creation 12%Wide Delivery 4%

Top Creators

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

playerposminkey P /90box entriesxT
Granit XhakaM7662.002517.1
Enzo Le FéeM7111.90176.9
Noah SadikiM7151.0164.6
Kevin DansoD4820.9386.6
Nordi MukieleD6270.29109.0
Reinildo MandavaD6460.5666.4
Trai HumeM5120.7054.8
Thomas MeunierM4370.4153.2

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)
Nilson AnguloW4633 (33%)1 (0%)
Malick FofanaW1461 (0%)1 (0%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Nordi MukieleD627158191330
Reinildo MandavaD646134111226
Dan BallardD47712810412
Granit XhakaM76612013846
Trai HumeM5129414324
Enzo Le FéeM7118910624
Noah SadikiM7158410520
Nilson AnguloM463719715

Full Squad Data

Every player with 100+ minutes (18 players).

playerposappsmingoalsxGkey PprogdefxT
Granit XhakaM876600.1176012017.1
Robin RoefsG876600.0034179.0
Noah SadikiM871500.7819844.6
Enzo Le FéeM871112.21533896.9
Reinildo MandavaD764600.04271346.4
Nordi MukieleD762700.92421589.0
Trai HumeM751200.2421944.8
Brian BrobbeyF648233.031600.8
Kevin DansoD548200.4520666.6
Dan BallardD547700.5261282.9
Nilson AnguloM746310.7115712.7
Thomas MeunierM643700.5211593.2
Wilson IsidorF624611.100370.2
Luke O'NienD320000.208501.7
Chris RiggM418700.113340.5
Malick FofanaM414600.305130.7
Omar AldereteD313100.004221.2
Dayann MéthalieD212000.004201.1

Player Role Architecture

The question
Who does what — and what tactical job does each key player actually perform?

The nine most-used players (450+ minutes), each with the role their event fingerprint points to — not just their listed position.

Granit Xhaka
Advanced creator · Attacking mid
minutes766
goals · xG0 · 0.1
prog passes /907.0
key passes /902.00
def actions /9014.1
pass accuracy78%
Robin Roefs
Goalkeeper · Goalkeeper
minutes766
goals · xG0 · 0.0
prog passes /904.0
key passes /900.00
def actions /902.0
pass accuracy67%
Noah Sadiki
Ball-winner / destroyer · Midfielder
minutes715
goals · xG0 · 0.7
prog passes /902.4
key passes /901.01
def actions /9010.6
pass accuracy86%
Enzo Le Fée
Ball-winner / destroyer · Midfielder
minutes711
goals · xG1 · 2.2
prog passes /904.2
key passes /901.90
def actions /9011.3
pass accuracy73%
Reinildo Mandava
Stopper / marker · Defender
minutes646
goals · xG0 · 0.0
prog passes /903.8
key passes /900.56
def actions /9018.7
pass accuracy79%
Nordi Mukiele
Ball-playing defender · Defender
minutes627
goals · xG0 · 0.9
prog passes /906.0
key passes /900.29
def actions /9022.7
pass accuracy72%
Trai Hume
Ball-winner / destroyer · Midfielder
minutes512
goals · xG0 · 0.2
prog passes /903.7
key passes /900.70
def actions /9016.5
pass accuracy67%
Kevin Danso
Stopper / marker · Defender
minutes482
goals · xG0 · 0.4
prog passes /903.7
key passes /900.93
def actions /9012.3
pass accuracy78%
Brian Brobbey
Poacher / finisher · Forward
minutes482
goals · xG3 · 3.0
prog passes /900.2
key passes /900.56
def actions /9011.2
pass accuracy77%

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: pass retention % (20th pct)
Sign a secure ball-retaining midfielder. The data flags this because possession is turned over cheaply (76.02, 20th percentile vs the league).
Need — bottom-third: xG conceded /game (25th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.44, 25th percentile vs the league).
Need — bottom-third: shots /game (30th pct)
Sign a shot-taking forward to raise shot volume. The data flags this because shot volume is low (12.00, 30th percentile vs the league).
Vision AI · building report