Combining every season — this one is larger, give it a moment.
Team reportPremier League 2025/26
Newcastle
A balanced-territory side, aggressive high-press out of possession, with a moderate attack. Finished #12 of 20 on 49 points (14-7-17, 53:55). Tactical profile below is built from 38 matches of ball-by-ball event data, contextualised against the league.
In one read, what kind of team is Newcastle and how good was the season?
Read. Newcastle finished #12 of 20 on 49 points (14W-7D-17L, 1.29 pts/game), scoring 53 and conceding 55 for a goal difference of -2.
On the ball they are a balanced-territory team (53% field tilt, #6 in the league); off it they defend with a aggressive high-press (#5 of 20 for press intensity).
Across the 38 matches of event data, they create 1.44 xG/game (#8) and concede 1.36 (#11), a net of +0.08 xG/game — the underlying performance matches the actual goal difference.
Season Context — the league table
The question
Where did Newcastle actually finish, and against whom?
The authoritative final table (full season), centred on Newcastle.
#
team
P
W
D
L
GF
GA
GD
Pts
9
Brentford
38
14
11
13
55
52
+3
53
10
Chelsea
38
14
10
14
58
52
+6
52
11
Fulham
38
15
7
16
47
51
-4
52
12
Newcastle
38
14
7
17
53
55
-2
49
13
Everton
38
13
10
15
47
50
-3
49
14
Leeds
38
11
14
13
49
56
-7
47
15
Crystal Palace
38
11
12
15
41
51
-10
45
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Newcastle actually dominate for chances — and which periods hurt them?
Net xG (created minus conceded) in each 15-minute window, summed across the whole season's matches — above the line is time they dominate for chances, below is time it hurts them. Real on-clock shot timing.
dominant (net xG for)conceding (net xG against)
Vision AI Model Insight
Newcastle tend to fade after a strong start — first-half net xG +5.84, second-half -2.76. Their strongest period is 0-15' (net +5.16 xG); their most dangerous period to face is 46-60' (net -3.09 xG against them).
xG Race — the season, match by match
Expected goals piling up over 38 matches: Newcastle against what their opponents created. A line pulling away upwards is a side creating more than it gives away; the gap at the end is the season’s balance (+3.1 xG). Hover a point for that match.
NewcastleOpponents against Newcastle
Tactical DNA
The football question
In five genes, what is Newcastle'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.
62
Build-Up
possession control from the back
88
Progression
moving the ball upfield with threat
67
Creation
manufacturing chances
72
Press
winning the ball high & hard
45
Solidity
resisting the opponent's threat
Genetic identity
Newcastle are defined most by their Progression DNA (88/100 · elite at moving the ball upfield with threat), and least by their Solidity DNA (45/100). Percentiles vs the 20 teams in the league.
The Playstyle Wheel
Fifteen style metrics across five domains — Possess, Disrupt, Finish, Press, Defend — each a percentile against the rest of the league. Metrics marked ~proxy use the closest available event-data signal where the standard definition needs data this feed doesn't carry (explicit pressure events, offside/keeper-sweep incidents).
Possess
Deep buildup
65%
Possession
65%
Field tilt
70%
Disrupt
Central progression ~proxy
35%
Dribble tendency
39%
Progressive passes
83%
Finish
Final-third patience
70%
Shot quality
52%
Open-play xG
52%
Press
Forward press ~proxy
78%
High regains
48%
Pressing efficiency ~proxy
70%
Defend
Def-mid press ~proxy
65%
High line ~proxy
52%
PAdj defensive actions
70%
Newcastle is defined most by Possess (67% in the league) and weakest on Disrupt (52%). Percentiles vs the 23 teams in the league this season.
In possession
In possession
How they keep the ball, build up, progress, create and finish, and where their attacks die.
How much of the pitch does Newcastle actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Newcastle'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; Newcastle highlighted. Hover any dot for the team.
Vision AI Model Insight
Newcastle post 53% field tilt, ranking #6 of 20 in the league — comfortably above the league mid-point for territorial control, and their 1.29 points/game sits below the league-average return — a real disconnect: their territorial control isn't showing up on the scoreboard the way it should.
Where the time goes — how long each phase lasts
The question
When Newcastle has the ball, how much of that time is spent building, progressing and creating?
The share of Newcastle's time on the ball spent in each phase of play, in the order the phases happen. A phase is where the ball is on the pitch (own third, middle third, final third); a transition or a set piece skips the build-up and is counted on its own.
Phase
Share of the time
Build-up
26.5%
Progression
44.4%
Chance creation
26.2%
Attacking transition
2.9%
Vision AI Model Insight
Progression is where Newcastle 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.
width = passes between the paircolour = xT per pass: low → high
Top 10 combinations
Botman ↔ Thiaw
382p · 6.8xT
Tonali ↔ Thiaw
253p · 9.6xT
Tonali ↔ Hall
252p · 8.0xT
Guimarães ↔ Tonali
230p · 9.7xT
Botman ↔ Hall
229p · 12.6xT
Burn ↔ Hall
214p · 9.6xT
Guimarães ↔ Thiaw
214p · 9.5xT
Gordon ↔ Hall
207p · 15.4xT
Burn ↔ Botman
197p · 7.4xT
Barnes ↔ Hall
195p · 14.9xT
Vision AI Model Insight
Busiest connection: Sven Botman ↔ Malick Thiaw (382 passes). Most dangerous per pass: Jacob Murphy ↔ Bruno Guimarães (0.08 xT/pass over 144 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Newcastle had the ball
Every touch across 380 matches. Brighter means more touches.
Which Zones Do They Attack Through?
The question
Across the whole pitch, where does Newcastle 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
18933
ACTIONS
Carries
the ball moved with a player
4346
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the middle third (10.0% of all actions). 58% of actions run through the inside lanes (centre + both half-spaces) versus 42% down the two wings — an inside-dominant, half-space build. By third: 28% defensive, 47% middle, 24% 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. Newcastle leaned on their right (41%). The bars under the pitch put the league’s share beside theirs.
Newcastle
36%23%41%
League
39%23%38%
Final-Third Entries
Every completed pass or carry that took the ball from outside the final third into it, by the channel it arrived in. Newcastle made 1704 this season (44.8 a match); 32% came into the right wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.
Channel
Entries
Per match
Share
League share
Left wing
435
11.4
26%
29%
Left half-space
252
6.6
15%
16%
Centre
189
5.0
11%
12%
Right half-space
282
7.4
17%
14%
Right wing
546
14.4
32%
29%
Build-up2 sections
Build-Up — the pass map
The football question
How does Newcastle 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.
5371build-up passes attempted
82%completed
30%reach the middle third
1%go long into the final third
Pass types
2054CB · 47%
236Long Wide · 5%
34Long Central · 1%
1707Wide → FB · 39%
368Central · 8%
Sequence success — build-up
1125build-up sequences this season
12%succeed — reach the next third or a shot
37%turned over with nothing to show
CB2054 · 47%
Long Wide236 · 5%
Long Central34 · 1%
Wide → FB1707 · 39%
Central368 · 8%
◆ Vision AI Insight
Newcastle build predominantly down the left, with Thiaw as the fulcrum (612 build-up passes). Only 31% 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 (277×).
Pass Explorer
Every pass of Newcastle’s last 10 matches as an arrow, theirs first and the opponents’ with other team, each side attacking left to right (solid = completed, dashed grey = failed). Eight families per team — click any map to open it wide, then filter by channel or third, from one to another (or click a cell of the flow grids), by outcome, half, minute and passer. Channels: right wing, right half-space, centre, left half-space, left wing.
From channel
To channel
From third
To third
Outcome
Minutes
Channel to channel · click a cell
Third to third · click a cell
Progression4 sections
How They Progress — the mechanism
Not just how many progressive passes, but where they start, who plays them, and whether they actually penetrate. 1771 progressive passes across 38 matches (46.6/game).
Origin lane
Right wing
37%
Right half-space
14%
Central
12%
Left half-space
9%
Left wing
27%
Progression is right-dominant: 51% right side · 12% central · 36% left.
Who generates it
Kieran Trippier
226 · 13%
Lewis Hall
150 · 8%
Bruno Guimarães
135 · 8%
Malick Thiaw
132 · 7%
Sandro Tonali
127 · 7%
Top two — Kieran Trippier & Lewis Hall — account for 21% of all progression.
PROGRESSION
46.6 prog passes/game
mostly right
→
PENETRATION
27% reach final third
21% reach the box
→
THREAT
the other 73% is recycled
progress ≠ danger
What came of it.27% of progressive passes reached the final third and 21% the box; the rest was recycled in front of the block. 21% 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-spacesterile
Left wingbalanced
Progression — the pass map
The football question
Once Newcastle 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.
8858progression passes attempted
85%completed
18%break into the final third
12%go backward into the defensive third
Pass types
2371CB · 31%
309Long Wide · 4%
47Long Central · 1%
3891Wide → FB · 52%
927Central · 12%
Sequence success — progression
1980progression sequences this season
25%succeed — reach the next third or a shot
41%turned over with nothing to show
CB2371 · 31%
Long Wide309 · 4%
Long Central47 · 1%
Wide → FB3891 · 52%
Central927 · 12%
◆ Vision AI Insight
Newcastle progress predominantly down the right, with Tonali the busiest midfield outlet (853 progression passes). Only 18% of passes that start in midfield actually break the final-third line — the rest (70%) is recycled back into midfield or (12%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is RW mid → RHS mid (396×) — 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)
14%
Progressive
1%
Neutral / sideways
50%
Safe / backward
34%
16% of passes are progressive-or-better; the remaining 84% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Newcastle actually progress the ball with their feet, not a pass?
1027 progressive carries this season across the whole squad (24% of 4346 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 56m. Most active carrier: Thiaw (125). Filter to one player below.
First (312)Second (293)Third (214)Fourth (208)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 Newcastle'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.
492shots
54.8xG
0.11xG per shot
31big chances (0.3+ xG)
53goals
#11key passes / game in the league
#4box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition21% of shots
104
11
12.93
0.12
Cross
12
1
2.09
0.17
Cut-back
8
2
0.96
0.12
Long ball
6
1
0.95
0.16
Pass into the box / short pass
51
4
6.26
0.12
Own creation (carry, dribble, rebound)
27
3
2.67
0.10
Settled attack57% of shots
279
27
26.56
0.10
Cross
48
6
6.93
0.14
Cut-back
20
3
2.54
0.13
Long ball
7
0
0.96
0.14
Pass into the box / short pass
131
10
10.17
0.08
Own creation (carry, dribble, rebound)
73
8
5.95
0.08
Set piece22% of shots
109
15
15.29
0.14
Corner
90
9
10.22
0.11
Free kick
13
0
0.30
0.02
Penalty
6
6
4.76
0.79
Every attempt to create — and what came of it
Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.
Who sets the shots up
Player
Set-ups
xG created
Goals
Joelinton
17
3.47
2
Anthony Gordon
26
3.07
2
Jacob Murphy
21
3.04
3
Sandro Tonali
23
2.46
1
Bruno Guimarães
31
2.41
3
Who takes them
Player
Shots
xG
Goals
Anthony Gordon
48
7.36
6
Nick Woltemade
32
6.00
8
Harvey Barnes
58
5.92
7
Malick Thiaw
28
5.50
4
Bruno Guimarães
42
5.36
9
Vision AI Model Insight
The biggest source of Newcastle's chances, by xG, is settled attack (26.6 of 54.8 xG, 279 of 492 shots), mostly pass into the box / short pass. 104 of the 492 shots (21%) came within 15 seconds of winning the ball. 109 of the 492 shots came from set pieces; 53 goals from 54.8 xG (-1.8).
Chance Creation — the pass map
The football question
How does Newcastle 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
27CB · 8%
21Long Wide · 6%
36Long Central · 11%
95Wide → FB · 29%
150Central · 46%
Sequence success — final-third
1380final-third sequences this season
23%succeed — produce a shot
40%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
CB27 · 8%
Long Wide21 · 6%
Long Central36 · 11%
Wide → FB95 · 29%
Central150 · 46%
Who creates — volume × threat
44Guimarães
32Tonali
28Trippier
26Gordon
25Hall
22Ramsey
22Murphy
329key passes #11 of 20
14.6box entries/game #4 of 20
36.1final-3rd entries/game #5 of 20
1.44xG/game #8 of 20
53goals #9 of 20
-1.8finishing vs xG #16 of 20
◆ Vision AI Insight
Newcastle lean left — 40% of their key passes come from that flank and its half-space (132 of 329), most often from Guimarães (22). They funnel chances into the c of the final third, most often via RW att → C att (43 key passes, most often from Murphy). Guimarães is the primary source overall. They generate 1.44 xG a game and finish it wasteful — they under-perform their xG, led by Bruno Guimarães (9G), Nick Woltemade (8G), William Osula (7G).
Crosses & Cutbacks — squad-wide
The question
How does Newcastle deliver into the box from wide areas, and what comes of it?
665 crosses: 211 found a team-mate (32%), 64 led to a shot (10%). 124 cut-backs: 54 found a team-mate (44%), 26 led to a shot (21%). 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 Newcastle actually cross from?
665 crosses this season (the same crosses as the map above), split into fifteen territories — five channels (both wings, both half-spaces and the centre) by three depths from the halfway line to the byline. 27% come from one territory, the byline right wing; 32 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · right wing
178
27%
15
byline · left wing
150
23%
13
advanced · right wing
139
21%
18
advanced · left wing
96
14%
14
deep · right wing
42
6%
1
deep · left wing
28
4%
1
advanced · right half-space
15
2%
0
byline · right half-space
7
1%
2
byline · left half-space
5
1%
0
advanced · left half-space
3
0%
0
deep · right half-space
1
0%
0
deep · left half-space
1
0%
0
Finishing3 sections
Shot Map
492 shots for 54.8 xG (1.44/game, #8 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Moderate attack. 12.9 shots/game at 0.111 xG/shot. Box entries 15/game (#4). Threat created 11.4 xT/game (#3).
Goal Sequences
The move behind each of Newcastle’s 53 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 — 53 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Newcastle scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
38 · 72%
Set pieces
9 · 17%
Penalties
6 · 11%
By finish
Right foot
30 · 57%
Left foot
13 · 25%
Header
10 · 19%
Vision AI Model Insight
53 goals scored. 72% 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
How they lose it
Incomplete pass — attacking third
1389
Failed forward pass
954
Failed take-on
422
Lost in the defensive third
972
Their weakest zone is the left wing in the attacking third: 32% of 1136 pass attempts there are lost (366 times). Separately, 38% of all losses happen in the attacking third — a fair share happen deeper, which invites transitions.
Out of possession
Out of possession
How they press, where they win the ball back, and how they concede.
How hard does Newcastle 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.
62
Pressing Index /100 · average
Intensity60
PPDA, high-press share, high-zone actions
Height65
how high up the pitch they defend
Effectiveness68
high recoveries & high-regain share
Disruption52
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
18%
RHS
20%
C
22%
LHS
20%
LW
20%
By third (high / mid / low regain)
Def 49%
Mid 37%
Att 14%
Read
Ranked #5 of 20 for press intensity, this is a high press. 51% of defensive actions happen in the middle & attacking thirds, at an average height of 38. Of recoveries, 56% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#5/20
lower = more intense; rank is what matters
Defensive actions / game
136
#14/20
High-press share
21%
#8/20
def actions won high up
Defensive-action height (0–100)
37.7
#7/20
avg pitch height of actions
High recoveries / game
22.9
#6/20
ball won in mid+att third
High-recovery share
56%
#7/20
share of recoveries won high
Opponent completion allowed
78%
#4/20
lower = more disruptive
Opponent progressive allowed
8.8%
#15/20
of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.
How long they keep it — passes and seconds until the ball is won
The question
Once the opponent has the ball, how many passes and how many seconds pass before Newcastle win it back with a defensive action?
Counted over the 1201 opposition possessions that Newcastle 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 Newcastle step in. Newcastle win it after 5.1 opponent passes in the first half-hour and after 3.7 after the hour mark (sooner).
PASSES THEY GET
4.3passes
median 2 · before Newcastle win it
TIME THEY KEEP IT
12sec
median 5s · 31.6 wins per game
How many passes the opponent got in before the ball was won
50%
27%
12%
11%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
4.9
14s
15–30′
5.3
15s
30–45+′
5.1
14s
45–60′
3.6
10s
60–75′
3.4
9s
75–90+′
3.9
12s
average passesaverage seconds
Phases of play
Every moment of the match read twice — what Newcastle were doing with the
ball, and what the opposition were doing about it at that exact moment. Built from the
real action sequence in time order, so one possession is split across the phases it
genuinely passed through rather than labelled once by where it began.
7,332phase segments analysed
9.0smedian time before the opposition engage
2.0their passes per defensive action when pressed
#8of 20 for share of defending spent pressing high
High press 8.4%Mid block 11.5%Low block 51.8%Unopposed 28.3%
What opponents do against Newcastle
The mirror image, and the part no other section can show: whether teams come
out to press Newcastle or sit in and invite them on. A side that is always faced with a low
block is playing a different sport from one that is pressed every week.
High press 7.5%Mid block 13.4%Low block 51.5%Unopposed 27.6%
Which phases actually produce
Phase
Segments
Avg length
Avg actions
Ends in shot
Turned over
Build-up
2,195
5.0s
3.1
0.3%
47.7%
Progression
3,096
5.9s
3.7
0.4%
46.5%
Chance creation
1,893
5.7s
3.4
23.5%
57.5%
Attacking transition
148
8.0s
4.8
4.7%
27.7%
Most common routes through the phases
How a possession actually travelled, in order. The chain is the tactical signature — a move that climbs all three thirds is a different thing from one that never leaves the first.
Route
Times
Ends in shot
build_up
834
0.2%
progression
819
0.1%
chance_creation
464
32.3%
progression → chance_creation
393
20.4%
build_up → progression
364
0.3%
build_up → progression → chance_creation
219
28.3%
Attitude in each third
Every other style number here says how much Newcastle 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 Newcastle 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) 5,371 passes
nothing unusual in this zone
Width of use+0.7322.52
Wide-channel share+0.530.34
Side bias+0.271.16
Pass length-0.1022.35
Long-ball share-0.260.20
Forward gain per pass-0.1310.91
Backward-pass share-0.160.19
Deep-pass share-0.270.26
Completion+0.230.81
Seconds between passes-0.103.26
Side used
left 31% · central 40% · right 29%
Progression (middle third) 8,858 passes
nothing unusual in this zone
Width of use+0.2526.10
Wide-channel share+0.210.42
Side bias-0.15-0.53
Pass length+0.1417.43
Long-ball share+0.200.11
Forward gain per pass+0.484.33
Backward-pass share-0.560.31
Deep-pass share+0.140.17
Completion-0.050.84
Seconds between passes+0.273.32
Side used
left 35% · central 28% · right 37%
Final third 4,704 passes
nothing unusual in this zone
Width of use-0.0531.49
Wide-channel share+0.010.59
Side bias-0.45-3.63
Pass length+0.1115.63
Long-ball share+0.060.10
Forward gain per pass+0.221.34
Backward-pass share-0.280.37
Deep-pass share-0.110.08
Completion-0.000.70
Seconds between passes-0.463.05
Side used
left 37% · central 16% · right 46%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Newcastle'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 Newcastle win or lose the ball, what actually happens in the seconds after?
Reconstructed from the full timestamped event stream: real possession spells (not zone-clustered), and shots that follow a regain within a fixed window. This phase of play needs ordered, per-event timestamps — which every match here carries.
Direct play share16%
#14 of 20 · reaches final third in ≤3 passes
Patient build-up share28%
#9 of 20 · spells of 6+ passes
Tempo (possession length)18.9s
#14 of 20 · shorter = faster tempo
Passes per possession4.6
#9 of 20
Counter-attack shots /game0.87
#14 of 20 · shot within 12s of a regain in own half
Press→shot /game2.74
#15 of 20 · shot within 8s of a high regain
Speed to final third after regain13.0s
#14 of 20 · lower = faster break
Sequence success — attacking transition
150attacking transition sequences this season
15%succeed — produce a shot
47%turned over with nothing to show
Sequence success — defensive transition
397defensive transition sequences this season
57%succeed — reach the next third or a shot
12%turned over with nothing to show
Vision AI Model Insight
Newcastle are a patient build-up side: 16% of possessions reach the final third in 3 passes or fewer (#14 of 20), against 28% built patiently over 6+ passes (#9 of 20). Winning the ball back leads to a shot inside 12 seconds 0.87 times a game (#14), and a high regain converts to a shot within 8 seconds 2.74 times a game (#15 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 Newcastle? 1499 opponent progressive passes and 470 shots faced (51.7 xG against) across the season.
Opponent threat by lane (attacking into Newcastle)
Right wing
28%
Right half-space
14%
Central
22%
Left half-space
13%
Left wing
24%
Where the danger came from. Opponents generated most of their threat through the right wing (28% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Newcastle actually come from — open play, dead balls, and who supplies them?
Every goal Newcastle conceded across the loaded matches — the opponent's shots in Newcastle's own matches — plus every individual opponent key pass faced, each drawn as its own real arrow (not zone-clustered) with the % share of each zone behind it.
Where the goals go in
Every opponent key pass against them (329 total)
By situation
Open play
36 · 68%
Set pieces
12 · 23%
Penalties
5 · 9%
Vision AI Model Insight
53 goals conceded. 68% come in open play; set pieces account for only 23%, so dead-ball defending is not the main issue. 23% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right half-space of the attacking third (21% of key passes faced) — that is the zone to shut off.
Context
Shape and tactics
Set pieces, strengths and weaknesses, and who they resemble.
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.
Open play
38 g · 39.5 xG
Set pieces
9 g · 10.5 xG
Penalties
6 g
17% of goals come from set pieces (9 of 53), worth 10.5 xG from 103 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Newcastle's corners go?
229 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 (104)
Delivered into the box 94%Short 6%
Left side (125)
Delivered into the box 99%Short 1%
Where opponents attack Newcastle from set pieces
63 shots from opponent corners against Newcastle, 11 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 (32)
Shot 32Goals 6
Left flag (31)
Shot 31Goals 5
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
progression /game — 46.61 (90th pct)
threat created /game — 11.43 (85th pct)
box entries /game — 14.61 (80th pct)
press intensity (PPDA) — 5.49 (75th pct)
field tilt % — 52.97 (70th pct)
Weaknesses (bottom-third vs league)
none stand out
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.
Man Utd
87%
Liverpool
68%
Man City
54%
Brighton
53%
Arsenal
47%
Performance vs Opponent Styles
The question
Not just how Newcastle 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 Newcastle's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (12m)
1.67
1.50
1.42
vs mid-block opponents (12m)
1.83
1.92
1.33
vs low-block opponents (14m)
0.79
1.00
1.14
Behaviour — how Newcastle actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
75%
17%
41
9.6
11.2
vs mid-block opponents
81%
12%
46
11.6
16.5
vs low-block opponents
83%
11%
52
12.9
15.9
Vision AI Model Insight
Facing a high press, retention drops to 75% vs 83% against a low block (7pt lower under pressure), and directness (long-ball share) sits at 17% when pressed vs 11% against a low block — a real style switch: they go noticeably more direct when pressed rather than trying to play through it.
Scouting Summary — the team in brief
In brief. Newcastle are balanced-territory with a aggressive high-press.
Their attack creates 1.44 xG a game and they concede 1.36 a game.
[Event-data based — no tracking, so off-ball structure and marking scheme need video.]
For each of ten match numbers, the one match this season that departed furthest from Newcastle’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.
Newcastle
across 38 matches this season
Progressive passesat Man Utd · 0-1 · 2025-12-2678avg 47
Pass accuracyvs Liverpool · 2-3 · 2025-08-2565%avg 80%
PPDAat Chelsea · 1-0 · 2026-03-149.5avg 5.5
Defensive actionsat West Ham · 1-3 · 2025-11-0293avg 136
Final-third entriesat Man Utd · 0-1 · 2025-12-2678avg 45
Threat from passingat Nottingham Forest · 1-1 · 2026-05-109.50avg 6.55
Passesvs Brighton · 3-1 · 2026-05-02274avg 498
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 Newcastle’s last 12 matches added up: where the value came from, who produced it, and the six biggest single moves. OBV only measures what a player does with the ball: it shows who added the most on-ball value, not who was the most important player (defending off the ball, positioning and pressing are not in it).
+17.7on-ball value, 12 matches
Where the value came from
Passes5803 actions+8.19
Carries1363 actions-2.63
Dribbles204 actions+1.07
Shots148 actions+7.92
Ball wins664 actions+3.13
Most on-ball value (OBV)
Actions
OBV
per 100
William Osula
130
+3.23
+2.48
Anthony Gordon
204
+2.37
+1.16
Bruno Guimarães
437
+2.29
+0.52
Malick Thiaw
791
+1.95
+0.25
Lewis Hall
867
+1.51
+0.17
Jacob Ramsey
527
+1.27
+0.24
Sven Botman
699
+0.90
+0.13
Kieran Trippier
422
+0.80
+0.19
Biggest single moves
OBV
1 William Osula · shot
+0.871
2 Anthony Gordon · shot
+0.863
3 Sven Botman · pass
+0.591
4 Malick Thiaw · shot
+0.486
5 William Osula · shot
+0.478
6 Sven Botman · pass
+0.399
Set Pieces by Player
Who delivers Newcastle’s dead balls and who finishes them this season. 229 corners taken, most by Sandro Tonali (49); 103 shots from corners and free kicks, 9 goals, led by Malick Thiaw (3 goals, 2.26 xG). “Into the box” counts corners that landed inside the penalty area; free-kick takers are the players who shot from one, because this feed does not mark who delivers the others.
Player
Corners taken
Into the box
Set-piece shots
Goals
xG
Free-kick shots
Penalties
Sandro Tonali
49
44 (90%)
9
—
0.27
2
—
Lewis Hall
41
34 (83%)
9
1
0.26
4
—
Bruno Guimarães
43
38 (88%)
5
1
0.35
2
2/2
Kieran Trippier
48
43 (90%)
2
—
0.05
2
—
Malick Thiaw
—
—
14
3
2.26
—
—
Lewis Miley
19
19 (100%)
4
—
0.16
—
—
Sven Botman
—
—
9
1
1.38
—
—
Anthony Gordon
4
2 (50%)
4
—
0.82
—
3/3
Nick Woltemade
—
—
7
1
1.11
—
1/1
Fabian Schär
—
—
7
—
0.44
2
—
Jacob Murphy
7
6 (86%)
4
—
0.15
—
—
Dan Burn
—
—
6
1
0.72
—
—
Joelinton
—
—
6
—
0.77
—
—
Anthony Elanga
15
14 (93%)
—
—
0.00
—
—
Top Performers
Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 300 minutes). Coloured chips are that player's strongest capability blocks.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Bruno Guimarães
M
2630
1.51
79
43.3
Kieran Trippier
D
1682
1.50
60
45.7
Lewis Hall
D
2373
0.95
50
36.2
Sandro Tonali
M
2669
1.08
42
35.6
Anthony Gordon
F
1896
1.23
44
16.4
Harvey Barnes
F
2144
0.92
46
15.4
Jacob Murphy
F
1735
1.14
43
19.8
Jacob Ramsey
M
1665
1.19
20
13.7
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.
player
pos
min
crosses (completed)
cutbacks (completed)
Jacob Murphy
W
1735
49 (39%)
19 (42%)
Harvey Barnes
W
2144
25 (32%)
29 (38%)
Lewis Hall
FB
2373
29 (52%)
15 (47%)
Kieran Trippier
FB
1682
37 (43%)
7 (43%)
Anthony Elanga
W
1473
12 (33%)
21 (43%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Malick Thiaw
D
3211
572
44
31
118
Dan Burn
D
2408
482
40
21
76
Sven Botman
D
1986
427
22
27
88
Lewis Hall
D
2373
393
54
28
134
Joelinton
M
2089
377
43
30
120
Bruno Guimarães
M
2630
332
62
15
135
Sandro Tonali
M
2669
330
35
31
147
Kieran Trippier
D
1682
250
26
10
73
Full Squad Data
Every player with 100+ minutes (22 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Malick Thiaw
D
35
3211
4
5.5
4
132
572
37.4
Sandro Tonali
M
35
2669
0
1.6
32
127
330
35.6
Bruno Guimarães
M
29
2630
9
5.4
44
135
332
43.3
Nick Pope
G
27
2602
0
0.2
0
68
63
18.0
Dan Burn
D
29
2408
1
1.0
5
80
482
21.4
Lewis Hall
D
30
2373
1
1.2
25
150
393
36.2
Harvey Barnes
F
37
2144
7
5.9
22
89
145
15.4
Joelinton
M
27
2089
2
2.5
15
37
377
14.0
Nick Woltemade
F
33
1997
8
6.0
18
13
211
5.6
Sven Botman
D
25
1986
1
1.7
5
54
427
21.8
Anthony Gordon
F
26
1896
6
7.4
26
84
162
16.4
Jacob Murphy
F
33
1735
3
3.3
22
112
160
19.8
Kieran Trippier
D
21
1682
0
0.0
28
226
250
45.7
Jacob Ramsey
M
28
1665
2
1.4
22
61
193
13.7
Lewis Miley
M
23
1648
1
1.2
14
84
242
16.9
Anthony Elanga
F
32
1473
0
1.4
14
83
111
11.6
Tino Livramento
D
17
1447
0
0.1
10
92
186
19.8
Fabian Schär
D
16
1185
0
0.9
3
64
229
19.7
Aaron Ramsdale
G
12
1101
0
0.0
1
44
31
11.1
Joe Willock
M
24
1086
0
1.4
14
26
146
7.4
William Osula
F
24
946
7
3.2
3
2
72
1.2
Yoane Wissa
F
19
638
1
3.3
2
4
60
1.5
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.
Malick Thiaw
Stopper / marker · Defender
minutes3211
goals · xG4 · 5.5
prog passes /903.7
key passes /900.11
def actions /9016.0
pass accuracy89%
Sandro Tonali
Ball-winner / destroyer · Midfielder
minutes2669
goals · xG0 · 1.6
prog passes /904.3
key passes /901.08
def actions /9011.1
pass accuracy81%
Bruno Guimarães
Creative forward · Forward
minutes2630
goals · xG9 · 5.4
prog passes /904.6
key passes /901.51
def actions /9011.4
pass accuracy83%
Nick Pope
Goalkeeper · Goalkeeper
minutes2602
goals · xG0 · 0.2
prog passes /902.4
key passes /900.00
def actions /902.2
pass accuracy69%
Dan Burn
Stopper / marker · Defender
minutes2408
goals · xG1 · 1.0
prog passes /903.0
key passes /900.19
def actions /9018.0
pass accuracy78%
Lewis Hall
Ball-playing defender · Defender
minutes2373
goals · xG1 · 1.2
prog passes /905.7
key passes /900.95
def actions /9014.9
pass accuracy81%
Harvey Barnes
Box-to-box midfielder · Midfielder
minutes2144
goals · xG7 · 5.9
prog passes /903.7
key passes /900.92
def actions /906.1
pass accuracy74%
Joelinton
Ball-winner / destroyer · Midfielder
minutes2089
goals · xG2 · 2.5
prog passes /901.6
key passes /900.65
def actions /9016.2
pass accuracy82%
Nick Woltemade
Poacher / finisher · Forward
minutes1997
goals · xG8 · 6.0
prog passes /900.6
key passes /900.81
def actions /909.5
pass accuracy76%
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: xG conceded /game (45th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.36, 45th percentile vs the league).
← BACK TO SEARCHSeason
