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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.

balanced-territoryaggressive high-pressmoderate attack
L
L
L
W
D
W
L
D
W
D
L
W
L
L
W
11
points
#8 of 20 · 8 games
12:14
goals
-2 GD
3-2-3
record
W-D-L
1.38
points/game
#8 in the league
1.11
xG for/game
rank #16
1.82
xG against/game
rank #19
#7
press rank
of 20 · most aggressive
48%
field tilt
#12
Newcastle
League average
Expected goals for / game
1.111.33
Expected goals against / game
1.821.33
Field tilt
48%50%
Pass retention
80%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 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.

#teamPWDLGFGAGDPts
5Chelsea84131715+213
6Brentford8251149+511
7Leeds825196+311
8Newcastle83231214-211
9Aston Villa8323912-311
10Hull City824298+110
11Everton824289-110

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)
even0-15'16-30'31-45'46-60'61-75'76-90+'+0.92-3.11
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.

0510168.914.6Liverpool (H) 2-2 · xG 1.43 to 3.59Tottenham (A) 2-0 · xG 0.78 to 1.15Bournemouth (H) 2-2 · xG 0.66 to 1.27Leeds (A) 1-4 · xG 0.70 to 2.08Hull City (H) 2-1 · xG 1.48 to 1.54Coventry (A) 1-4 · xG 1.83 to 1.50Aston Villa (H) 0-1 · xG 1.14 to 1.34Crystal Palace (A) 2-0 · xG 0.87 to 2.09M1M2M3M4M5M6M7M8
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).

Possess67Disrupt52Finish58Press65Defend62
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.

Keeping the ball6 sections

Field Tilt — Territorial Control

The question
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.

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/gNewcastle33%44%55%66%0.61.32.02.6FIELD TILT %POINTS / GAME
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.

Build-up: 27.5% of the time on the ball27%Progression: 47.4% of the time on the ball47%Chance creation: 23.1% of the time on the ball23%Attacking transition: 2.0% of the time on the ball47%PROGRESSION
PhaseShare of the time
Build-up27.5%
Progression47.4%
Chance creation23.1%
Attacking transition2.0%
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.

Sven Botman ↔ Lewis Hall: 136 passes, -0.5 combined xTMalick Thiaw ↔ Lewis Miley: 100 passes, -0.3 combined xTSven Botman ↔ Malick Thiaw: 96 passes, -0.0 combined xTSven Botman ↔ Lukás Hornícek: 92 passes, 0.0 combined xTHarvey Barnes ↔ Lewis Hall: 85 passes, 1.3 combined xTMalick Thiaw ↔ Lukás Hornícek: 76 passes, -0.3 combined xTMalick Thiaw ↔ Amar Dedic: 56 passes, -0.7 combined xTNico González ↔ Lewis Miley: 55 passes, 0.0 combined xTSven Botman ↔ Nico González: 52 passes, -0.0 combined xTLewis Miley ↔ Sean Steur: 46 passes, -0.0 combined xTJoe Willock ↔ Lewis Hall: 45 passes, 0.6 combined xTNico González ↔ Lewis Hall: 44 passes, 0.2 combined xTMalick Thiaw ↔ Nico González: 43 passes, -0.0 combined xTLewis Hall ↔ Sean Steur: 41 passes, 0.2 combined xTJacob Murphy ↔ Lewis Miley: 38 passes, 0.5 combined xTSven Botman ↔ Lewis Miley: 37 passes, -0.2 combined xTMalick Thiaw ↔ Sean Steur: 35 passes, -0.2 combined xTLewis Hall ↔ Lewis Miley: 33 passes, 0.4 combined xTJoe Willock ↔ Nico González: 30 passes, 0.6 combined xTJoe Willock ↔ Lewis Miley: 30 passes, 0.3 combined xTJoe Willock ↔ Sven Botman: 28 passes, 0.2 combined xTHarvey Barnes ↔ Sven Botman: 27 passes, 0.1 combined xTHarvey Barnes ↔ Joe Willock: 26 passes, 0.2 combined xTLewis Hall ↔ Matias Fernandez-Pardo: 23 passes, 1.2 combined xTYoane Wissa — isolate this player's connectionsWissaHarvey Barnes — isolate this player's connectionsBarnesJoe Willock — isolate this player's connectionsWillockSandro Tonali — isolate this player's connectionsTonaliLukás Hornícek — isolate this player's connectionsHornícekLewis Hall — isolate this player's connectionsHallLewis Miley — isolate this player's connectionsMileySven Botman — isolate this player's connectionsBotmanMalick Thiaw — isolate this player's connectionsThiawJacob Murphy — isolate this player's connectionsMurphyBruno Guimarães — isolate this player's connectionsGuimarãesAmar Dedic — isolate this player's connectionsDedicNico González — isolate this player's connectionsGonzálezMatias Fernandez-Pardo — isolate this player's connectionsFernandez-Sean Steur — isolate this player's connectionsSteurBazoumana Touré — isolate this player's connectionsTouré
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
4%4%11%5%5%8%8%10%11%11%6%3%3%4%7%PASSES
Carries
the ball moved with a player
911
ACTIONS
3%5%9%9%4%8%9%12%11%11%5%3%1%3%8%CARRIES
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.

44%Left side24%Middle33%Right sideATTACKING →
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.

Left wing: 99 entries (33%)9933%LEFT WINGLeft half-space: 54 entries (18%)5418%LEFT HALF-SPACECentre: 35 entries (12%)3512%CENTRERight half-space: 43 entries (14%)4314%RIGHT HALF-SPACERight wing: 66 entries (22%)6622%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing9912.433%31%
Left half-space546.818%16%
Centre354.412%13%
Right half-space435.414%14%
Right wing668.222%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%
left: 182 passes, most from Botman182right: 162 passes, most from Thiaw162
Long Wide49 · 6%
left: 34 passes, most from Hornícek34right: 15 passes, most from Hornícek15
Long Central6 · 1%
left: 5 passes, most from Hornícek5
Wide → FB349 · 42%
left: 183 passes, most from Hall183right: 166 passes, most from Hornícek166
Central91 · 11%
left: 47 passes, most from Hornícek47right: 44 passes, most from Hornícek44
◆ 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.

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%
left: 238 passes, most from Botman238right: 196 passes, most from Thiaw196
Long Wide63 · 4%
right: 33 passes, most from Miley33left: 30 passes, most from Hall30
Long Central11 · 1%
right: 7 passes, most from González7left: 4 passes, most from Hall4
Wide → FB826 · 54%
left: 490 passes, most from Hall490right: 336 passes, most from Miley336
Central190 · 12%
left: 98 passes, most from Willock98right: 92 passes, most from Steur92
◆ 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.

Carries Map — progressive ball-carries, squad-wide

The question
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
Attacking transition: 21 shots (22%)22%21Settled attack: 65 shots (68%)68%65Set piece: 10 shots (10%)10%1096SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 22% of shots2141.860.09
Cross100.120.12
Cut-back100.090.09
Long ball100.190.19
Pass into the box / short pass1040.730.07
Own creation (carry, dribble, rebound)800.730.09
Settled attack 68% of shots6575.700.09
Cross1121.730.16
Cut-back610.480.08
Long ball410.220.06
Pass into the box / short pass2721.990.07
Own creation (carry, dribble, rebound)1711.280.08
Set piece 10% of shots1011.320.13
Corner710.480.07
Free kick200.050.03
Penalty100.790.79

Every attempt to create — and what came of it

Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.

Who sets the shots up

PlayerSet-upsxG createdGoals
Harvey Barnes101.032
Lewis Hall80.821
Jacob Murphy60.701
Joe Willock30.490
Nico González70.471

Who takes them

PlayerShotsxGGoals
Yoane Wissa182.811
Harvey Barnes191.562
Joe Willock161.272
William Osula60.531
Jacob Murphy40.470
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%
left: 2 passes, most from Schär2right: 2 passes, most from Schär2
Long Wide2 · 3%
Long Central9 · 13%
right: 7 passes, most from Hall7left: 2 passes, most from Miley2
Wide → FB33 · 48%
left: 19 passes, most from González19right: 14 passes, most from Dedic14
Central21 · 30%
left: 12 passes, most from Barnes12right: 9 passes, most from Barnes9

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.

deep right wing: 9 crosses (8%)8%9deep right half-space: 1 crosses (1%)1%1deep centre: 0 crosses (0%)deep left half-space: 1 crosses (1%)1%1deep left wing: 13 crosses (12%)12%13advanced right wing: 26 crosses (23%)23%26advanced right half-space: 2 crosses (2%)2%2advanced centre: 0 crosses (0%)advanced left half-space: 2 crosses (2%)2%2advanced left wing: 13 crosses (12%)12%13byline right wing: 22 crosses (20%)20%22byline right half-space: 1 crosses (1%)1%1byline centre: 0 crosses (0%)byline left half-space: 1 crosses (1%)1%1byline left wing: 21 crosses (19%)19%21
TerritoryCrossesShareLed to a shot
advanced · right wing2623%2
byline · right wing2220%4
byline · left wing2119%2
deep · left wing1312%0
advanced · left wing1312%3
deep · right wing98%0
advanced · right half-space22%1
advanced · left half-space22%0
deep · right half-space11%0
deep · left half-space11%0
byline · right half-space11%0
byline · left half-space11%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

37 of 142 pass attempts lost here (26%).26%37/142Thiaw29 of 163 pass attempts lost here (18%).18%29/163Hornícek89 of 400 pass attempts lost here (22%).22%89/400Hornícek27 of 182 pass attempts lost here (15%).15%27/182Botman54 of 188 pass attempts lost here (29%).29%54/188Hall49 of 294 pass attempts lost here (17%).17%49/294Dedic52 of 311 pass attempts lost here (17%).17%52/311Thiaw52 of 371 pass attempts lost here (14%).14%52/371González52 of 395 pass attempts lost here (13%).13%52/395González52 of 410 pass attempts lost here (13%).13%52/410Hall64 of 205 pass attempts lost here (31%).31%64/205Hall44 of 113 pass attempts lost here (39%).39%44/113Wissa24 of 101 pass attempts lost here (24%).24%24/101Botman42 of 139 pass attempts lost here (30%).30%42/139Barnes54 of 249 pass attempts lost here (22%).22%54/249Barnesattacking →

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.

Pressing2 sections

Pressing — the full picture

The football question
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

metricvaluerankmeaning
PPDA (opp passes per def action)—#7/20lower = more intense; rank is what matters
Defensive actions / game164#6/20
High-press share20%#17/20def actions won high up
Defensive-action height (0–100)36.9#17/20avg pitch height of actions
High recoveries / game22.0#9/20ball won in mid+att third
High-recovery share53%#9/20share of recoveries won high
Opponent completion allowed77%#3/20lower = more disruptive
Opponent progressive allowed9.8%#17/20of 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 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

← opponent shot at own goal

Every opponent key pass against them (76 total)

1%1%3%1%3%4%7%5%20%16%21%8%11%Cody GakpoDominik SzoboszlaiDominik SzoboszlaiFlorian WirtzJérémy JacquetMilos KerkezRyan GravenberchJeremie FrimpongDominik SzoboszlaiCody GakpoJeremie FrimpongJeremie FrimpongCody GakpoAndy RobertsonOmar MarmoushOmar MarmoushMateus FernandesSandro TonaliOmar MarmoushMateus FernandesMateus FernandesJan Paul van HeckeDestiny UdogieAdam SmithJames HillAdam SmithAdrien TruffertMatt CrooksRegan SlaterOliver McBurnieSorba ThomasMohamed BelloumiMohamed BelloumiTim IroegbunamRyan GilesLucas Gourna-DouathRyan GilesRobinio VazMohamed-Ali ChoLucas HerringtonMohamed-Ali ChoAlex ScottMarcus TavernierJames HillJames HillAlex ScottAnton StachJames JustinAnton StachAnton StachNoah OkaforJames JustinJayden BogleTarik MuharemovicVictor TorpJay DasilvaYéremy PinoYéremy PinoDarío OsorioTyrick MitchellAdam WhartonYéremy PinoDarío OsorioYéremy PinoDwight McNeilAlyssonNicolas JacksonJohan ManzambiJohan ManzambiJoão GomesNicolas JacksonIbrahim MbayeRoss BarkleyRoss BarkleyTyrone MingsJohn McGinn← own goal

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.

Premium
Tactical Phase Read
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
Subscribe →

Set-Piece Threat

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

Open play
11 g · 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)

11%22%6%6%22%17%6%
Delivered into the box 89%Short 11%

Left side (18)

6%6%6%6%6%17%28%22%
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)

36%29%7%7%21%
Shot 14Goals 0

Left flag (10)

20%40%10%20%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 typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)2.001.002.00
vs mid-block opponents (2m)1.503.000.50
vs low-block opponents (4m)1.251.501.50

Behaviour — how Newcastle actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents71%20%317.610.5
vs mid-block opponents80%14%308.59.5
vs low-block opponents83%11%4010.914.5
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.]
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 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 8 matches this season
PPDAat Tottenham · 2-0 · 2026-08-297.4avg 4.3
Progressive carriesat Coventry · 1-4 · 2026-10-1289avg 50
Pass accuracyat Crystal Palace · 2-0 · 2026-10-2569%avg 80%
Expected goalsat Coventry · 1-4 · 2026-10-121.83avg 1.11
Field tiltvs Liverpool · 2-2 · 2026-08-2331%avg 48%
Threat from passingat Coventry · 1-4 · 2026-10-127.48avg 4.98
Final-third entriesvs Liverpool · 2-2 · 2026-08-2321avg 37
Progressive passesat Coventry · 1-4 · 2026-10-1247avg 36

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 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)ActionsOBVper 100
Yoane Wissa230+2.24+0.98
Harvey Barnes333+1.24+0.37
Sven Botman582+0.83+0.14
Anthony Elanga99+0.70+0.71
Joe Willock284+0.67+0.23
Jacob Murphy138+0.63+0.46
William Osula30+0.59+1.95
Nico González424+0.59+0.14
123456
Biggest single movesOBV
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.

PlayerCorners takenInto the boxSet-piece shotsGoalsxGFree-kick shotsPenalties
Lewis Hall1913 (68%)2—0.06——
Yoane Wissa——310.31—0/1
Harvey Barnes76 (86%)——0.00——
Jacob Murphy55 (100%)——0.00——
Anthony Elanga33 (100%)——0.00——
William Osula——1—0.021—
Nick Woltemade——1—0.04——
Amar Dedic——1—0.031—
Joelinton——1—0.07——
Lewis Miley11 (100%)——0.00——
Matias Fernandez-Pardo10 (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.

playerposminVision AI Scorecapability blocks
Lewis HallFB7607.2Ball-Carrying 78%Ball-Winning 67%Wide Delivery 45%
Sven BotmanCB6696.1Ball-Winning 60%Ball-Carrying 57%Aerial & Box Defending 40%Progression 34%
Nico GonzálezCM4525.4Ball-Carrying 76%Successful Dribble 64%Progression 48%Chance Creation 27%
Malick ThiawCB6735.3Progression 68%Ball-Carrying 68%Ball-Winning 46%Aerial & Box Defending 29%
Lewis MileyCM5605.3Successful Dribble 72%Ball-Carrying 59%Progression 52%Chance Creation 28%
Lukás HornícekGK7674.9Shot-Stopping 49%
Amar DedicFB4764.8Ball-Winning 51%Ball-Carrying 48%Wide Delivery 2%
Harvey BarnesW7433.9Box Threat 64%Ball-Carrying 37%Wide Delivery 29%Chance Creation 26%
Joe WillockAM4892.1Ball-Carrying 58%Box Threat 27%Chance Creation 19%
Yoane WissaST6561.5Box Threat 54%Ball-Carrying 53%Finishing 15%Aerial Threat 0%

Top Creators

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

playerposminkey P /90box entriesxT
Harvey BarnesM7431.33154.4
Lewis HallD7601.071413.0
Lewis MileyM5601.12107.0
Jacob MurphyM3651.9793.6
Nico GonzálezM4521.7966.9
Amar DedicD4760.7684.2
Anthony ElangaM2541.4241.7
Joe WillockM4890.5542.3

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.

playerposmincrosses (completed)cutbacks (completed)
Lewis HallFB76012 (50%)0
Jacob MurphyW36511 (36%)1 (0%)
Harvey BarnesW7436 (33%)3 (0%)
Amar DedicFB4764 (75%)1 (100%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Lewis HallD760174171357
Sven BotmanD6691426617
Malick ThiawD6731180419
Yoane WissaF6561097020
Lewis MileyM560959636
Harvey BarnesM743956428
Nico GonzálezM452889628
Amar DedicD476838325

Full Squad Data

Every player with 100+ minutes (20 players).

playerposappsmingoalsxGkey PprogdefxT
Lukás HornícekG876700.0026216.2
Lewis HallD876010.495817413.0
Harvey BarnesM874321.61117954.4
Malick ThiawD867300.02191187.1
Sven BotmanD766910.30241427.6
Yoane WissaF865612.8171092.0
Lewis MileyM756000.1726957.0
Joe WillockM848921.3311622.3
Amar DedicD647600.2418834.2
Nico GonzálezM645200.1918886.9
Jacob MurphyM736500.5815463.6
Matias Fernandez-PardoM531200.2210321.2
Sean SteurM625400.035262.4
Anthony ElangaM425420.448291.7
JoelintonM320900.127441.7
William OsulaF418910.511170.1
Bazoumana TouréM513610.315241.0
Fabian SchärD313400.022261.0
Jacob RamseyM411310.103221.0
Dan BurnD310900.004301.1

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).
Vision AI · building report