Combining every season — this one is larger, give it a moment.
Team reportPremier League 2026
Newcastle
A balanced-territory side, aggressive high-press out of possession, with a moderate attack. Currently #8 of 20 on 11 points (3-2-3, 12:14). Tactical profile below is built from 8 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 currently sit #8 of 20 on 11 points (3W-2D-3L, 1.38 pts/game), scoring 12 and conceding 14 for a goal difference of -2.
On the ball they are a balanced-territory team (48% field tilt, #12 in the league); off it they defend with a aggressive high-press (#7 of 20 for press intensity).
Across the 8 matches of event data, they create 1.11 xG/game (#16) and concede 1.82 (#19), a net of -0.71 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
5
Chelsea
8
4
1
3
17
15
+2
13
6
Brentford
8
2
5
1
14
9
+5
11
7
Leeds
8
2
5
1
9
6
+3
11
8
Newcastle
8
3
2
3
12
14
-2
11
9
Aston Villa
8
3
2
3
9
12
-3
11
10
Hull City
8
2
4
2
9
8
+1
10
11
Everton
8
2
4
2
8
9
-1
10
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 come alive after the break — first-half net xG -4.06, second-half -1.61. Their strongest period is 61-75' (net +0.92 xG); their most dangerous period to face is 0-15' (net -3.11 xG against them).
xG Race — the season, match by match
Expected goals piling up over 8 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 (-5.7 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.
45
Build-Up
possession control from the back
15
Progression
moving the ball upfield with threat
32
Creation
manufacturing chances
52
Press
winning the ball high & hard
5
Solidity
resisting the opponent's threat
Genetic identity
Newcastle are defined most by their Press DNA (52/100 · average at winning the ball high & hard), and least by their Solidity DNA (5/100). 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 48% field tilt, ranking #12 of 20 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 1.38 points/game sits above 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
27.5%
Progression
47.4%
Chance creation
23.1%
Attacking transition
2.0%
Vision AI Model Insight
Progression is where Newcastle spends most of its time on the ball (47% 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 ↔ Hall
136p · -0.5xT
Thiaw ↔ Miley
100p · -0.3xT
Botman ↔ Thiaw
96p · -0.0xT
Botman ↔ Hornícek
92p · 0.0xT
Barnes ↔ Hall
85p · 1.3xT
Thiaw ↔ Hornícek
76p · -0.3xT
Thiaw ↔ Dedic
56p · -0.7xT
González ↔ Miley
55p · 0.0xT
Botman ↔ González
52p · -0.0xT
Miley ↔ Steur
46p · -0.0xT
Vision AI Model Insight
Busiest connection: Sven Botman ↔ Lewis Hall (136 passes). Most dangerous per pass: Lewis Hall ↔ Matias Fernandez-Pardo (0.05 xT/pass over 23 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 80 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
3663
ACTIONS
Carries
the ball moved with a player
911
ACTIONS
Vision AI Model Insight
Their single busiest zone is the left wing of the middle third (11.1% of all actions). 60% of actions run through the inside lanes (centre + both half-spaces) versus 40% down the two wings — an inside-dominant, half-space build. By third: 29% defensive, 49% middle, 21% 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 left (44%). The bars under the pitch put the league’s share beside theirs.
Newcastle
44%24%33%
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. Newcastle made 297 this season (37.1 a match); 33% came into the left wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.
Channel
Entries
Per match
Share
League share
Left wing
99
12.4
33%
31%
Left half-space
54
6.8
18%
16%
Centre
35
4.4
12%
13%
Right half-space
43
5.4
14%
14%
Right wing
66
8.2
22%
27%
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.
1075build-up passes attempted
78%completed
24%reach the middle third
1%go long into the final third
Pass types
344CB · 41%
49Long Wide · 6%
6Long Central · 1%
349Wide → FB · 42%
91Central · 11%
Sequence success — build-up
120build-up sequences this season
5%succeed — reach the next third or a shot
42%turned over with nothing to show
CB344 · 41%
Long Wide49 · 6%
Long Central6 · 1%
Wide → FB349 · 42%
Central91 · 11%
◆ Vision AI Insight
Newcastle build predominantly down the left, with Hornícek as the fulcrum (183 build-up passes). Only 26% 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 (57×).
Pass Explorer
Every pass of Newcastle’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.
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. 285 progressive passes across 8 matches (35.6/game).
Origin lane
Right wing
24%
Right half-space
12%
Central
14%
Left half-space
14%
Left wing
36%
Progression is left-dominant: 35% right side · 14% central · 51% left.
Who generates it
Lewis Hall
58 · 20%
Lukás Hornícek
26 · 9%
Lewis Miley
26 · 9%
Sven Botman
24 · 8%
Malick Thiaw
19 · 7%
Top two — Lewis Hall & Lukás Hornícek — account for 29% of all progression.
PROGRESSION
35.6 prog passes/game
mostly left
→
PENETRATION
32% reach final third
22% reach the box
→
THREAT
the other 68% is recycled
progress ≠ danger
What came of it.32% of progressive passes reached the final third and 22% the box; the rest was recycled in front of the block. 29% of the progression ran through two players, mostly down the left side.
Which lanes actually create the threat
Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.
Per lane — volume vs threat
Right wingbalanced
Right half-spacebalanced
Centralbalanced
Left half-spacebalanced
Left 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.
1781progression passes attempted
86%completed
14%break into the final third
12%go backward into the defensive third
Pass types
434CB · 28%
63Long Wide · 4%
11Long Central · 1%
826Wide → FB · 54%
190Central · 12%
Sequence success — progression
180progression sequences this season
23%succeed — reach the next third or a shot
46%turned over with nothing to show
CB434 · 28%
Long Wide63 · 4%
Long Central11 · 1%
Wide → FB826 · 54%
Central190 · 12%
◆ Vision AI Insight
Newcastle progress predominantly down the right, with Hall the busiest midfield outlet (206 progression passes). Only 14% of passes that start in midfield actually break the final-third line — the rest (73%) is recycled back into midfield or (12%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LHS mid → LW mid (96×) — 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)
11%
Progressive
1%
Neutral / sideways
51%
Safe / backward
37%
12% of passes are progressive-or-better; the remaining 88% 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?
248 progressive carries this season across the whole squad (27% of 911 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 39m. Most active carrier: Thiaw (40). Filter to one player below.
First (77)Second (71)Third (52)Fourth (48)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.
96shots
8.9xG
0.09xG per shot
4big chances (0.3+ xG)
12goals
#13key passes / game in the league
#11box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition22% of shots
21
4
1.86
0.09
Cross
1
0
0.12
0.12
Cut-back
1
0
0.09
0.09
Long ball
1
0
0.19
0.19
Pass into the box / short pass
10
4
0.73
0.07
Own creation (carry, dribble, rebound)
8
0
0.73
0.09
Settled attack68% of shots
65
7
5.70
0.09
Cross
11
2
1.73
0.16
Cut-back
6
1
0.48
0.08
Long ball
4
1
0.22
0.06
Pass into the box / short pass
27
2
1.99
0.07
Own creation (carry, dribble, rebound)
17
1
1.28
0.08
Set piece10% of shots
10
1
1.32
0.13
Corner
7
1
0.48
0.07
Free kick
2
0
0.05
0.03
Penalty
1
0
0.79
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
Harvey Barnes
10
1.03
2
Lewis Hall
8
0.82
1
Jacob Murphy
6
0.70
1
Joe Willock
3
0.49
0
Nico González
7
0.47
1
Who takes them
Player
Shots
xG
Goals
Yoane Wissa
18
2.81
1
Harvey Barnes
19
1.56
2
Joe Willock
16
1.27
2
William Osula
6
0.53
1
Jacob Murphy
4
0.47
0
Vision AI Model Insight
The biggest source of Newcastle's chances, by xG, is settled attack (5.7 of 8.9 xG, 65 of 96 shots), mostly pass into the box / short pass. 21 of the 96 shots (22%) came within 15 seconds of winning the ball. 10 of the 96 shots came from set pieces; 12 goals from 8.9 xG (+3.1).
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
4CB · 6%
2Long Wide · 3%
9Long Central · 13%
33Wide → FB · 48%
21Central · 30%
Sequence success — final-third
90final-third sequences this season
16%succeed — produce a shot
37%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
CB4 · 6%
Long Wide2 · 3%
Long Central9 · 13%
Wide → FB33 · 48%
Central21 · 30%
Who creates — volume × threat
11Barnes
9Hall
9González
8Murphy
7Miley
4Dedic
4Elanga
69key passes #13 of 20
12.2box entries/game #11 of 20
29.0final-3rd entries/game #15 of 20
1.11xG/game #16 of 20
12goals #6 of 20
+3.1finishing vs xG #4 of 20
◆ Vision AI Insight
Newcastle lean right — 43% of their key passes come from that flank and its half-space (30 of 69), most often from Murphy (7). They funnel chances into the c of the final third, most often via RHS att → C att (8 key passes, most often from Dedic). Barnes is the primary source overall. They generate 1.11 xG a game and finish it clinical — they beat their xG, led by Harvey Barnes (2G), Joe Willock (2G), Anthony Elanga (2G).
Crosses & Cutbacks — squad-wide
The question
How does Newcastle deliver into the box from wide areas, and what comes of it?
112 crosses: 38 found a team-mate (34%), 12 led to a shot (11%). 19 cut-backs: 10 found a team-mate (53%), 7 led to a shot (37%). 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?
112 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. 23% come from one territory, the advanced right wing; 8 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
advanced · right wing
26
23%
2
byline · right wing
22
20%
4
byline · left wing
21
19%
2
deep · left wing
13
12%
0
advanced · left wing
13
12%
3
deep · right wing
9
8%
0
advanced · right half-space
2
2%
1
advanced · left half-space
2
2%
0
deep · right half-space
1
1%
0
deep · left half-space
1
1%
0
byline · right half-space
1
1%
0
byline · left half-space
1
1%
0
Finishing3 sections
Shot Map
96 shots for 8.9 xG (1.11/game, #16 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 0.093 xG/shot. Box entries 12/game (#11). Threat created 9.5 xT/game (#15).
Goal Sequences
The move behind each of Newcastle’s 12 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 — 12 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
11 · 92%
Set pieces
1 · 8%
Penalties
0 · 0%
By finish
Right foot
6 · 50%
Left foot
6 · 50%
Header
0 · 0%
Vision AI Model Insight
12 goals scored. 92% 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
How they lose it
Incomplete pass — attacking third
228
Failed forward pass
160
Failed take-on
82
Lost in the defensive third
236
Their weakest zone is the right half-space in the attacking third: 39% of 113 pass attempts there are lost (44 times). Separately, 32% 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.
39
Pressing Index /100 · passive
Intensity32
PPDA, high-press share, high-zone actions
Height15
how high up the pitch they defend
Effectiveness55
high recoveries & high-regain share
Disruption50
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
14%
RHS
20%
C
23%
LHS
22%
LW
22%
By third (high / mid / low regain)
Def 49%
Mid 39%
Att 13%
Read
Ranked #7 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 37. Of recoveries, 53% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#7/20
lower = more intense; rank is what matters
Defensive actions / game
164
#6/20
High-press share
20%
#17/20
def actions won high up
Defensive-action height (0–100)
36.9
#17/20
avg pitch height of actions
High recoveries / game
22.0
#9/20
ball won in mid+att third
High-recovery share
53%
#9/20
share of recoveries won high
Opponent completion allowed
77%
#3/20
lower = more disruptive
Opponent progressive allowed
9.8%
#17/20
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 243 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 4.6 opponent passes in the first half-hour and after 3.9 after the hour mark (sooner).
PASSES THEY GET
4.5passes
median 3 · before Newcastle win it
TIME THEY KEEP IT
14sec
median 7s · 30.4 wins per game
How many passes the opponent got in before the ball was won
45%
29%
13%
13%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
4.6
13s
15–30′
4.6
18s
30–45+′
6.4
21s
45–60′
3.9
11s
60–75′
3.6
10s
75–90+′
4.1
13s
average passesaverage seconds
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) 1,075 passes
nothing unusual in this zone
Width of use+0.0921.20
Wide-channel share+0.130.31
Side bias+0.712.81
Pass length+0.3624.00
Long-ball share+0.090.24
Forward gain per pass+0.1812.22
Backward-pass share+0.260.21
Deep-pass share+0.260.31
Completion-0.220.78
Seconds between passes+0.293.50
Side used
left 31% · central 45% · right 24%
Progression (middle third) 1,781 passes
left-sided
Width of use+0.2126.02
Wide-channel share+0.140.41
Side bias+0.893.60
Pass length+0.0817.34
Long-ball share+0.200.11
Forward gain per pass-0.033.57
Backward-pass share+0.310.35
Deep-pass share-0.100.16
Completion+0.060.85
Seconds between passes+0.413.38
Side used
left 40% · central 29% · right 31%
Final third 807 passes
nothing unusual in this zone
Width of use-0.1131.33
Wide-channel share-0.000.58
Side bias+0.482.90
Pass length-0.1615.21
Long-ball share-0.430.08
Forward gain per pass-0.190.79
Backward-pass share+0.100.39
Deep-pass share-0.210.08
Completion+0.270.72
Seconds between passes+0.473.75
Side used
left 45% · central 17% · right 38%
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
#16 of 20 · shot within 8s of a high regain
Speed to final third after regain13.0s
#12 of 20 · lower = faster break
Sequence success — attacking transition
14attacking transition sequences this season
29%succeed — produce a shot
43%turned over with nothing to show
Sequence success — defensive transition
32defensive transition sequences this season
50%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 (#16 of 20) — not yet a major source of chances.
Defending the box2 sections
Vulnerability Map — how opponents hurt them
The report flipped: where do opponents create their threat against Newcastle? 340 opponent progressive passes and 138 shots faced (14.6 xG against) across the season.
Opponent threat by lane (attacking into Newcastle)
Right wing
36%
Right half-space
15%
Central
16%
Left half-space
10%
Left wing
24%
Where the danger came from. Opponents generated most of their threat through the right wing (36% 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 (76 total)
By situation
Open play
10 · 83%
Set pieces
0 · 0%
Penalties
2 · 17%
Vision AI Model Insight
12 goals conceded. 83% come in open play; set pieces account for only 0%, so dead-ball defending is not the main issue. 17% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre 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
11 g · 7.6 xG
Set pieces
1 g · 0.5 xG
Penalties
0 g
8% of goals come from set pieces (1 of 12), worth 0.5 xG from 9 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Newcastle's corners go?
36 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 (18)
Delivered into the box 89%Short 11%
Left side (18)
Delivered into the box 94%Short 6%
Where opponents attack Newcastle from set pieces
24 shots from opponent corners against Newcastle, 0 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 (14)
Shot 14Goals 0
Left flag (10)
Shot 10Goals 0
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
press intensity (PPDA) — 4.29 (65th pct)
Weaknesses (bottom-third vs league)
xG conceded /game — 1.82 (5th pct)
progression /game — 35.62 (5th pct)
xG created /game — 1.11 (20th pct)
threat created /game — 9.48 (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.
Ipswich
70%
Crystal Palace
64%
Everton
61%
Aston Villa
48%
Sunderland
35%
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 (2m)
2.00
1.00
2.00
vs mid-block opponents (2m)
1.50
3.00
0.50
vs low-block opponents (4m)
1.25
1.50
1.50
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
71%
20%
31
7.6
10.5
vs mid-block opponents
80%
14%
30
8.5
9.5
vs low-block opponents
83%
11%
40
10.9
14.5
Vision AI Model Insight
Facing a high press, retention drops to 71% vs 83% against a low block (12pt lower under pressure), and directness (long-ball share) sits at 20% 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 1.11 xG a game and they concede 1.82 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.
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 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).
+10.5on-ball value, 8 matches
Where the value came from
Passes3663 actions+2.75
Carries911 actions+0.38
Dribbles142 actions+0.66
Shots96 actions+4.59
Ball wins446 actions+2.07
Most on-ball value (OBV)
Actions
OBV
per 100
Yoane Wissa
230
+2.24
+0.98
Harvey Barnes
333
+1.24
+0.37
Sven Botman
582
+0.83
+0.14
Anthony Elanga
99
+0.70
+0.71
Joe Willock
284
+0.67
+0.23
Jacob Murphy
138
+0.63
+0.46
William Osula
30
+0.59
+1.95
Nico González
424
+0.59
+0.14
Biggest single moves
OBV
1 Yoane Wissa · shot
+0.778
2 Lewis Hall · pass
+0.427
3 William Osula · shot
+0.410
4 Anthony Elanga · pass
+0.377
5 Anthony Elanga · take-on
+0.347
6 Matias Fernandez-Pardo · take-on
+0.314
Set Pieces by Player
Who delivers Newcastle’s dead balls and who finishes them this season. 36 corners taken, most by Lewis Hall (19); 9 shots from corners and free kicks, 1 goals, led by Yoane Wissa (1 goals, 0.31 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
Lewis Hall
19
13 (68%)
2
—
0.06
—
—
Yoane Wissa
—
—
3
1
0.31
—
0/1
Harvey Barnes
7
6 (86%)
—
—
0.00
—
—
Jacob Murphy
5
5 (100%)
—
—
0.00
—
—
Anthony Elanga
3
3 (100%)
—
—
0.00
—
—
William Osula
—
—
1
—
0.02
1
—
Nick Woltemade
—
—
1
—
0.04
—
—
Amar Dedic
—
—
1
—
0.03
1
—
Joelinton
—
—
1
—
0.07
—
—
Lewis Miley
1
1 (100%)
—
—
0.00
—
—
Matias Fernandez-Pardo
1
0 (0%)
—
—
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.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Harvey Barnes
M
743
1.33
15
4.4
Lewis Hall
D
760
1.07
14
13.0
Lewis Miley
M
560
1.12
10
7.0
Jacob Murphy
M
365
1.97
9
3.6
Nico González
M
452
1.79
6
6.9
Amar Dedic
D
476
0.76
8
4.2
Anthony Elanga
M
254
1.42
4
1.7
Joe Willock
M
489
0.55
4
2.3
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)
Lewis Hall
FB
760
12 (50%)
0
Jacob Murphy
W
365
11 (36%)
1 (0%)
Harvey Barnes
W
743
6 (33%)
3 (0%)
Amar Dedic
FB
476
4 (75%)
1 (100%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Lewis Hall
D
760
174
17
13
57
Sven Botman
D
669
142
6
6
17
Malick Thiaw
D
673
118
0
4
19
Yoane Wissa
F
656
109
7
0
20
Lewis Miley
M
560
95
9
6
36
Harvey Barnes
M
743
95
6
4
28
Nico González
M
452
88
9
6
28
Amar Dedic
D
476
83
8
3
25
Full Squad Data
Every player with 100+ minutes (20 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Lukás Hornícek
G
8
767
0
0.0
0
26
21
6.2
Lewis Hall
D
8
760
1
0.4
9
58
174
13.0
Harvey Barnes
M
8
743
2
1.6
11
17
95
4.4
Malick Thiaw
D
8
673
0
0.0
2
19
118
7.1
Sven Botman
D
7
669
1
0.3
0
24
142
7.6
Yoane Wissa
F
8
656
1
2.8
1
7
109
2.0
Lewis Miley
M
7
560
0
0.1
7
26
95
7.0
Joe Willock
M
8
489
2
1.3
3
11
62
2.3
Amar Dedic
D
6
476
0
0.2
4
18
83
4.2
Nico González
M
6
452
0
0.1
9
18
88
6.9
Jacob Murphy
M
7
365
0
0.5
8
15
46
3.6
Matias Fernandez-Pardo
M
5
312
0
0.2
2
10
32
1.2
Sean Steur
M
6
254
0
0.0
3
5
26
2.4
Anthony Elanga
M
4
254
2
0.4
4
8
29
1.7
Joelinton
M
3
209
0
0.1
2
7
44
1.7
William Osula
F
4
189
1
0.5
1
1
17
0.1
Bazoumana Touré
M
5
136
1
0.3
1
5
24
1.0
Fabian Schär
D
3
134
0
0.0
2
2
26
1.0
Jacob Ramsey
M
4
113
1
0.1
0
3
22
1.0
Dan Burn
D
3
109
0
0.0
0
4
30
1.1
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.
Lukás Hornícek
Goalkeeper · Goalkeeper
minutes767
goals · xG0 · 0.0
prog passes /903.1
key passes /900.00
def actions /902.5
pass accuracy67%
Lewis Hall
Ball-playing defender · Defender
minutes760
goals · xG1 · 0.4
prog passes /906.9
key passes /901.07
def actions /9020.6
pass accuracy80%
Harvey Barnes
Ball-winner / destroyer · Midfielder
minutes743
goals · xG2 · 1.6
prog passes /902.1
key passes /901.33
def actions /9011.5
pass accuracy73%
Malick Thiaw
Stopper / marker · Defender
minutes673
goals · xG0 · 0.0
prog passes /902.5
key passes /900.27
def actions /9015.8
pass accuracy86%
Sven Botman
Stopper / marker · Defender
minutes669
goals · xG1 · 0.3
prog passes /903.2
key passes /900.00
def actions /9019.1
pass accuracy87%
Yoane Wissa
Ball-winner / destroyer · Midfielder
minutes656
goals · xG1 · 2.8
prog passes /901.0
key passes /900.14
def actions /9015.0
pass accuracy71%
Lewis Miley
Ball-winner / destroyer · Midfielder
minutes560
goals · xG0 · 0.1
prog passes /904.2
key passes /901.12
def actions /9015.3
pass accuracy86%
Joe Willock
Ball-winner / destroyer · Midfielder
minutes489
goals · xG2 · 1.3
prog passes /902.0
key passes /900.55
def actions /9011.4
pass accuracy90%
Amar Dedic
Stopper / marker · Defender
minutes476
goals · xG0 · 0.2
prog passes /903.4
key passes /900.76
def actions /9015.7
pass accuracy79%
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: xG conceded /game (5th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.82, 5th percentile vs the league).
Need — bottom-third: progression /game (5th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (35.62, 5th percentile vs the league).
Need — bottom-third: xG created /game (20th pct)
Sign a higher-volume goalscorer or chance creator. The data flags this because the attack under-produces xG (1.11, 20th percentile vs the league).