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Team reportPremier League 2026

Crystal Palace

A territorially-dominated side, aggressive high-press out of possession, with a moderate attack. Currently #17 of 20 on 7 points (2-1-5, 9:19). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

territorially-dominatedaggressive high-pressmoderate attack
D
L
L
D
L
D
L
L
L
W
L
D
W
L
L
7
points
#17 of 20 · 8 games
9:19
goals
-10 GD
2-1-5
record
W-D-L
0.88
points/game
#17 in the league
1.12
xG for/game
rank #14
1.87
xG against/game
rank #20
#18
press rank
of 20 · most aggressive
39%
field tilt
#18
Crystal Palace
League average
Expected goals for / game
1.121.33
Expected goals against / game
1.871.33
Field tilt
39%50%
Pass retention
77%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 Crystal Palace and how good was the season?
Read. Crystal Palace currently sit #17 of 20 on 7 points (2W-1D-5L, 0.88 pts/game), scoring 9 and conceding 19 for a goal difference of -10. On the ball they are a territorially-dominated team (39% field tilt, #18 in the league); off it they defend with a aggressive high-press (#18 of 20 for press intensity). Across the 8 matches of event data, they create 1.12 xG/game (#14) and concede 1.87 (#20), a net of -0.75 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

The question
Where did Crystal Palace actually finish, and against whom?

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

#teamPWDLGFGAGDPts
14Tottenham8233810-29
15Fulham8224810-28
16Man Utd81431013-37
17Crystal Palace8215919-107
18Nottingham Forest8134610-46
19Coventry8206615-96
20Sunderland8125614-85

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Crystal Palace actually dominate for chances — and which periods hurt them?

Net xG (created minus conceded) in each 15-minute window, summed across the whole season's matches — above the line is time they dominate for chances, below is time it hurts them. Real on-clock shot timing.

dominant (net xG for)conceding (net xG against)
even0-15'16-30'31-45'46-60'61-75'76-90+'+1.18-2.50
Vision AI Model Insight
Crystal Palace tend to fade after a strong start — first-half net xG -2.22, second-half -3.80. Their strongest period is 0-15' (net +1.18 xG); their most dangerous period to face is 46-60' (net -2.50 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Crystal Palace 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 (-6.0 xG). Hover a point for that match.

0511168.914.9Everton (A) 0-2 · xG 1.36 to 1.13Man City (H) 1-4 · xG 0.52 to 2.35Fulham (A) 3-2 · xG 1.06 to 3.16Ipswich (H) 2-3 · xG 0.70 to 1.62Leeds (A) 0-0 · xG 0.97 to 1.25Nottingham Forest (H) 3-1 · xG 1.74 to 2.70Brighton (A) 0-5 · xG 0.48 to 1.87Newcastle (H) 0-2 · xG 2.09 to 0.87M1M2M3M4M5M6M7M8
Crystal PalaceOpponents against Crystal Palace

Tactical DNA

The football question
In five genes, what is Crystal Palace'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.

20
Build-Up
possession control from the back
15
Progression
moving the ball upfield with threat
17
Creation
manufacturing chances
10
Press
winning the ball high & hard
0
Solidity
resisting the opponent's threat
Genetic identity
Crystal Palace are defined most by their Build-Up DNA (20/100 · limited at possession control from the back), and least by their Solidity DNA (0/100). 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).

Possess35Disrupt20Finish43Press33Defend39
Possess
Deep buildup
39%
Possession
35%
Field tilt
30%
Disrupt
Central progression ~proxy
17%
Dribble tendency
0%
Progressive passes
43%
Finish
Final-third patience
13%
Shot quality
78%
Open-play xG
39%
Press
Forward press ~proxy
30%
High regains
26%
Pressing efficiency ~proxy
43%
Defend
Def-mid press ~proxy
35%
High line ~proxy
26%
PAdj defensive actions
57%
Crystal Palace is defined most by Finish (43% in the league) and weakest on Disrupt (20%). 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 Crystal Palace actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Crystal Palace'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; Crystal Palace 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/gCrystal Palace33%44%55%66%0.61.32.02.6FIELD TILT %POINTS / GAME
Vision AI Model Insight
Crystal Palace post 39% field tilt, ranking #18 of 20 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 0.88 points/game sits below the league-average return — territory is genuinely converting into results.

Where the time goes — how long each phase lasts

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

The share of Crystal Palace'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: 32.2% of the time on the ball32%Progression: 45.5% of the time on the ball45%Chance creation: 19.7% of the time on the ball20%Attacking transition: 2.6% of the time on the ball45%PROGRESSION
PhaseShare of the time
Build-up32.2%
Progression45.5%
Chance creation19.7%
Attacking transition2.6%
Vision AI Model Insight
Progression is where Crystal Palace spends most of its time on the ball (45% 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.

Chris Richards ↔ Jaydee Canvot: 81 passes, -0.2 combined xTTyrick Mitchell ↔ Jaydee Canvot: 74 passes, -0.3 combined xTChris Richards ↔ Anan Khalaili: 70 passes, -0.1 combined xTDaichi Kamada ↔ Adam Wharton: 58 passes, 0.7 combined xTAnan Khalaili ↔ Jaydee Canvot: 58 passes, -0.2 combined xTChris Richards ↔ Adam Wharton: 52 passes, 0.6 combined xTYéremy Pino ↔ Adam Wharton: 51 passes, 0.9 combined xTDaichi Kamada ↔ Anan Khalaili: 49 passes, 1.5 combined xTDaichi Kamada ↔ Yéremy Pino: 45 passes, 1.6 combined xTAdam Wharton ↔ Anan Khalaili: 45 passes, 1.9 combined xTDaichi Kamada ↔ Tyrick Mitchell: 43 passes, 0.8 combined xTTyrick Mitchell ↔ Yéremy Pino: 42 passes, 1.5 combined xTAdam Wharton ↔ Jaydee Canvot: 38 passes, 0.5 combined xTYéremy Pino ↔ Anan Khalaili: 37 passes, 2.4 combined xTWalter Benítez ↔ Jaydee Canvot: 35 passes, -0.6 combined xTWalter Benítez ↔ Chris Richards: 34 passes, -0.1 combined xTDaichi Kamada ↔ Jaydee Canvot: 32 passes, 0.1 combined xTTyrick Mitchell ↔ Quinten Timber: 26 passes, 0.9 combined xTDaichi Kamada ↔ Chris Richards: 23 passes, 0.0 combined xTTyrick Mitchell ↔ Adam Wharton: 22 passes, 0.3 combined xTYéremy Pino ↔ Jaydee Canvot: 22 passes, -0.2 combined xTJørgen Strand Larsen ↔ Yéremy Pino: 19 passes, 0.3 combined xTQuinten Timber ↔ Adam Wharton: 19 passes, 0.0 combined xTChris Richards ↔ Yéremy Pino: 18 passes, -0.3 combined xTDaichi Kamada — isolate this player's connectionsKamadaMarc Guéhi — isolate this player's connectionsGuéhiTyrick Mitchell — isolate this player's connectionsMitchellChris Richards — isolate this player's connectionsRichardsAdam Wharton — isolate this player's connectionsWhartonAnan Khalaili — isolate this player's connectionsKhalailiMaxence Lacroix — isolate this player's connectionsLacroixYéremy Pino — isolate this player's connectionsPinoDaniel Muñoz — isolate this player's connectionsMuñozJaydee Canvot — isolate this player's connectionsCanvotBrennan Johnson — isolate this player's connectionsJohnsonJørgen Strand Larsen — isolate this player's connectionsLarsenEddie Nketiah — isolate this player's connectionsNketiahEberechi Eze — isolate this player's connectionsEzeWalter Benítez — isolate this player's connectionsBenítezQuinten Timber — isolate this player's connectionsTimber
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Richards ↔ Canvot
81p · -0.2xT
Mitchell ↔ Canvot
74p · -0.3xT
Richards ↔ Khalaili
70p · -0.1xT
Kamada ↔ Wharton
58p · 0.7xT
Khalaili ↔ Canvot
58p · -0.2xT
Richards ↔ Wharton
52p · 0.6xT
Pino ↔ Wharton
51p · 0.9xT
Kamada ↔ Khalaili
49p · 1.5xT
Kamada ↔ Pino
45p · 1.6xT
Wharton ↔ Khalaili
45p · 1.9xT
Vision AI Model Insight
Busiest connection: Chris Richards ↔ Jaydee Canvot (81 passes). Most dangerous per pass: Yéremy Pino ↔ Anan Khalaili (0.06 xT/pass over 37 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Crystal Palace 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 Crystal Palace 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
3500
ACTIONS
6%5%13%5%5%9%9%10%9%7%4%3%3%4%6%PASSES
Carries
the ball moved with a player
784
ACTIONS
4%7%11%7%3%10%9%11%11%8%5%2%2%3%6%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (13.0% of all actions). 63% of actions run through the inside lanes (centre + both half-spaces) versus 37% down the two wings — an inside-dominant, half-space build. By third: 35% defensive, 46% middle, 19% 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. Crystal Palace leaned on their left (38%). The bars under the pitch put the league’s share beside theirs.

38%Left side26%Middle36%Right sideATTACKING →
Crystal Palace
38%26%36%
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. Crystal Palace made 262 this season (32.8 a match); 28% came into the right wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.

Left wing: 63 entries (24%)6324%LEFT WINGLeft half-space: 51 entries (19%)5119%LEFT HALF-SPACECentre: 38 entries (15%)3815%CENTRERight half-space: 36 entries (14%)3614%RIGHT HALF-SPACERight wing: 74 entries (28%)7428%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing637.924%31%
Left half-space516.419%16%
Centre384.815%13%
Right half-space364.514%14%
Right wing749.228%27%
Build-up2 sections

Build-Up — the pass map

The football question
How does Crystal Palace 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.

1233build-up passes attempted
75%completed
26%reach the middle third
1%go long into the final third

Pass types

470CB · 51%
44Long Wide · 5%
13Long Central · 1%
312Wide → FB · 34%
87Central · 9%

Sequence success — build-up

90build-up sequences this season
6%succeed — reach the next third or a shot
44%turned over with nothing to show
CB470 · 51%
right: 237 passes, most from Richards237left: 233 passes, most from Richards233
Long Wide44 · 5%
right: 25 passes, most from Benítez25left: 19 passes, most from Benítez19
Long Central13 · 1%
right: 8 passes, most from Benítez8left: 5 passes, most from Benítez5
Wide → FB312 · 34%
right: 172 passes, most from Khalaili172left: 140 passes, most from Mitchell140
Central87 · 9%
right: 47 passes, most from Henderson47left: 40 passes, most from Benítez40
◆ Vision AI Insight
Crystal Palace build predominantly down the left, with Richards as the fulcrum (162 build-up passes). Only 27% 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 (73×).

Pass Explorer

Every pass of Crystal Palace’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. 300 progressive passes across 8 matches (37.5/game).

Origin lane

Right wing
32%
Right half-space
12%
Central
19%
Left half-space
11%
Left wing
26%
Progression is right-dominant: 45% right side · 19% central · 37% left.

Who generates it

Anan Khalaili
48 · 16%
Tyrick Mitchell
36 · 12%
Chris Richards
29 · 10%
Adam Wharton
29 · 10%
Yéremy Pino
28 · 9%
Top two — Anan Khalaili & Tyrick Mitchell — account for 28% of all progression.
PROGRESSION
37.5 prog passes/game
mostly right
→
PENETRATION
26% reach final third
18% reach the box
→
THREAT
the other 74% is recycled
progress ≠ danger
What came of it. 26% of progressive passes reached the final third and 18% the box; the rest was recycled in front of the block. 28% of the progression ran through two players, mostly down the right side.

Which lanes actually create the threat

Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.

Per lane — volume vs threat
Right wingefficient
Right half-spacebalanced
Centralbalanced
Left half-spacebalanced
Left wingbalanced

Progression — the pass map

The football question
Once Crystal Palace 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.

1573progression passes attempted
84%completed
15%break into the final third
14%go backward into the defensive third

Pass types

512CB · 39%
45Long Wide · 3%
8Long Central · 1%
585Wide → FB · 44%
174Central · 13%

Sequence success — progression

142progression sequences this season
30%succeed — reach the next third or a shot
39%turned over with nothing to show
CB512 · 39%
left: 260 passes, most from Canvot260right: 252 passes, most from Richards252
Long Wide45 · 3%
left: 23 passes, most from Mitchell23right: 22 passes, most from Khalaili22
Long Central8 · 1%
left: 4 passes, most from Mitchell4right: 4 passes, most from Timber4
Wide → FB585 · 44%
right: 295 passes, most from Khalaili295left: 290 passes, most from Mitchell290
Central174 · 13%
right: 88 passes, most from Pino88left: 86 passes, most from Wharton86
◆ Vision AI Insight
Crystal Palace progress predominantly down the right, with Canvot the busiest midfield outlet (170 progression passes). Only 15% of passes that start in midfield actually break the final-third line — the rest (71%) is recycled back into midfield or (14%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is C mid → LHS mid (72×) — 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)
12%
Progressive
1%
Neutral / sideways
53%
Safe / backward
34%
14% of passes are progressive-or-better; the remaining 86% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.

Carries Map — progressive ball-carries, squad-wide

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

192 progressive carries this season across the whole squad (25% of 762 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: Canvot (40). Filter to one player below.

First (62)Second (53)Third (40)Fourth (37)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 Crystal Palace'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.

88shots
8.9xG
0.10xG per shot
5big chances (0.3+ xG)
8goals
#17key passes / game in the league
#19box entries / game in the league
Attacking transition: 24 shots (27%)27%24Settled attack: 46 shots (52%)52%46Set piece: 18 shots (20%)20%1888SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 27% of shots2422.770.12
Cross400.550.14
Long ball100.090.09
Pass into the box / short pass1411.680.12
Own creation (carry, dribble, rebound)510.460.09
Settled attack 52% of shots4654.670.10
Cross700.380.05
Cut-back200.250.13
Long ball600.300.05
Pass into the box / short pass1831.280.07
Own creation (carry, dribble, rebound)1322.460.19
Set piece 20% of shots1811.490.08
Corner1511.390.09
Free kick300.090.03

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
Yéremy Pino110.891
Eddie Nketiah40.781
Anan Khalaili60.650
Daichi Kamada60.482
Adam Wharton70.450

Who takes them

PlayerShotsxGGoals
Jean-Philippe Mateta61.960
Jørgen Strand Larsen90.921
Anan Khalaili110.841
Jefferson Lerma50.831
Daichi Kamada60.701
Vision AI Model Insight
The biggest source of Crystal Palace's chances, by xG, is settled attack (4.7 of 8.9 xG, 46 of 88 shots), mostly own creation (carry, dribble, rebound). 24 of the 88 shots (27%) came within 15 seconds of winning the ball. 18 of the 88 shots came from set pieces; 8 goals from 8.9 xG (-0.9).

Chance Creation — the pass map

The football question
How does Crystal Palace 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

5CB · 8%
6Long Wide · 10%
8Long Central · 14%
14Wide → FB · 24%
26Central · 44%

Sequence success — final-third

76final-third sequences this season
20%succeed — produce a shot
41%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
CB5 · 8%
right: 3 passes, most from Tomiyasu3left: 2 passes, most from Richards2
Long Wide6 · 10%
left: 3 passes, most from Wharton3right: 3 passes, most from Pino3
Long Central8 · 14%
left: 5 passes, most from Wharton5right: 3 passes, most from Pino3
Wide → FB14 · 24%
left: 9 passes, most from Mitchell9right: 5 passes, most from Kamada5
Central26 · 44%
left: 15 passes, most from Wharton15right: 11 passes, most from Pino11

Who creates — volume × threat

12Wharton
12Pino
6Mitchell
6Kamada
4Nketiah
4Khalaili
2Osorio
59key passes #17 of 20
9.4box entries/game #19 of 20
25.9final-3rd entries/game #19 of 20
1.12xG/game #14 of 20
8goals #11 of 20
-0.9finishing vs xG #10 of 20
◆ Vision AI Insight
Crystal Palace lean left — 37% of their key passes come from that flank and its half-space (22 of 59), most often from Pino (7). They funnel chances into the c of the final third, most often via RW att → C att (8 key passes, most often from Wharton). Wharton is the primary source overall. They generate 1.12 xG a game and finish it wasteful — they under-perform their xG, led by Tyrick Mitchell (2G), Yéremy Pino (1G), Anan Khalaili (1G).

Crosses & Cutbacks — squad-wide

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

108 crosses: 32 found a team-mate (30%), 11 led to a shot (10%). 15 cut-backs: 3 found a team-mate (20%), 2 led to a shot (13%). 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 Crystal Palace actually cross from?

108 crosses this season (the same crosses as the map above), split into fifteen territories — five channels (both wings, both half-spaces and the centre) by three depths from the halfway line to the byline. 26% come from one territory, the byline left wing; 8 come from the half-spaces and 0 from the centre.

deep right wing: 7 crosses (6%)6%7deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 4 crosses (4%)4%4advanced right wing: 25 crosses (23%)23%25advanced right half-space: 1 crosses (1%)1%1advanced centre: 0 crosses (0%)advanced left half-space: 4 crosses (4%)4%4advanced left wing: 24 crosses (22%)22%24byline right wing: 12 crosses (11%)11%12byline right half-space: 2 crosses (2%)2%2byline centre: 0 crosses (0%)byline left half-space: 1 crosses (1%)1%1byline left wing: 28 crosses (26%)26%28
TerritoryCrossesShareLed to a shot
byline · left wing2826%2
advanced · right wing2523%1
advanced · left wing2422%1
byline · right wing1211%4
deep · right wing76%0
deep · left wing44%0
advanced · left half-space44%1
byline · right half-space22%0
advanced · right half-space11%1
byline · left half-space11%1
Finishing3 sections

Shot Map

88 shots for 8.9 xG (1.12/game, #14 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

Moderate attack. 11.0 shots/game at 0.101 xG/shot. Box entries 9/game (#19). Threat created 9.1 xT/game (#18).

Goal Sequences

The move behind each of Crystal Palace’s 9 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 — 9 goals traced.

How Do They Score?

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

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

By situation

Open play
7 · 88%
Set pieces
1 · 12%
Penalties
0 · 0%

By finish

Right foot
3 · 38%
Left foot
4 · 50%
Header
1 · 12%
Vision AI Model Insight
8 goals scored. 88% come in open play; set pieces add 12%. 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

62 of 207 pass attempts lost here (30%).30%62/207Khalaili30 of 187 pass attempts lost here (16%).16%30/187Wharton113 of 467 pass attempts lost here (24%).24%113/467Benítez26 of 184 pass attempts lost here (14%).14%26/184Richards76 of 188 pass attempts lost here (40%).40%76/188Mitchell68 of 314 pass attempts lost here (22%).22%68/314Khalaili64 of 323 pass attempts lost here (20%).20%64/323Wharton39 of 354 pass attempts lost here (11%).11%39/354Wharton41 of 320 pass attempts lost here (13%).13%41/320Wharton37 of 262 pass attempts lost here (14%).14%37/262Mitchell55 of 154 pass attempts lost here (36%).36%55/154Khalaili38 of 97 pass attempts lost here (39%).39%38/97Khalaili25 of 100 pass attempts lost here (25%).25%25/100Wharton58 of 148 pass attempts lost here (39%).39%58/148Mitchell65 of 195 pass attempts lost here (33%).33%65/195Pinoattacking →

How they lose it

Incomplete pass — attacking third
241
Failed forward pass
176
Failed take-on
54
Lost in the defensive third
307
Their weakest zone is the left wing in the defensive third: 40% of 188 pass attempts there are lost (76 times). Separately, 30% of all losses happen in the attacking third — a fair share happen deeper, which invites transitions.
Out of possession

Out of possession

How they press, where they win the ball back, and how they concede.

Pressing2 sections

Pressing — the full picture

The football question
How hard does Crystal Palace 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.

23
Pressing Index
/100 · passive
Intensity10
PPDA, high-press share, high-zone actions
Height5
how high up the pitch they defend
Effectiveness28
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
22%
RHS
20%
C
21%
LHS
19%
LW
18%
By third (high / mid / low regain)
Def 53%
Mid 34%
Att 13%
Read
Ranked #18 of 20 for press intensity, this is a high press. Note the tension: 53% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (20% high-press share) means that when they do defend, it is often deep. Of recoveries, 50% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#18/20lower = more intense; rank is what matters
Defensive actions / game167#5/20
High-press share20%#19/20def actions won high up
Defensive-action height (0–100)35.9#19/20avg pitch height of actions
High recoveries / game19.9#14/20ball won in mid+att third
High-recovery share50%#15/20share of recoveries won high
Opponent completion allowed82%#15/20lower = more disruptive
Opponent progressive allowed8.3%#4/20of 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 Crystal Palace win it back with a defensive action?

Counted over the 269 opposition possessions that Crystal Palace 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 Crystal Palace step in. Crystal Palace win it after 5.9 opponent passes in the first half-hour and after 4.7 after the hour mark (sooner).

PASSES THEY GET
5.3passes
median 3 · before Crystal Palace win it
TIME THEY KEEP IT
15sec
median 6s · 33.6 wins per game
How many passes the opponent got in before the ball was won
43%
26%
15%
16%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.1
18s
15–30′
5.7
16s
30–45+′
6.2
17s
45–60′
4.7
14s
60–75′
4.2
11s
75–90+′
5.0
15s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Crystal Palace 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 Crystal Palace 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) 1,233 passes

nothing unusual in this zone

Width of use+0.3721.76
Wide-channel share+0.480.34
Side bias-0.17-0.48
Pass length-0.1122.29
Long-ball share+0.050.23
Forward gain per pass+0.1211.98
Backward-pass share-0.470.18
Deep-pass share+0.010.29
Completion-0.580.75
Seconds between passes+0.083.38
Side used

left 28% · central 43% · right 29%

Progression (middle third) 1,573 passes

nothing unusual in this zone

Width of use-0.0425.48
Wide-channel share-0.150.39
Side bias-0.38-1.43
Pass length-0.6016.39
Long-ball share-0.530.08
Forward gain per pass-0.353.08
Backward-pass share-0.030.33
Deep-pass share-0.310.15
Completion-0.130.84
Seconds between passes-0.163.12
Side used

left 33% · central 31% · right 36%

Final third 694 passes

nothing unusual in this zone

Width of use-0.5430.28
Wide-channel share-0.480.54
Side bias+0.734.69
Pass length-0.1115.29
Long-ball share+0.130.10
Forward gain per pass+0.762.05
Backward-pass share-0.700.34
Deep-pass share+0.180.09
Completion-0.750.64
Seconds between passes-0.363.12
Side used

left 47% · central 19% · right 33%

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

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

Direct play share17%
#12 of 20 · reaches final third in ≤3 passes
Patient build-up share23%
#16 of 20 · spells of 6+ passes
Tempo (possession length)15.9s
#4 of 20 · shorter = faster tempo
Passes per possession4.0
#16 of 20
Counter-attack shots /game1.15
#7 of 20 · shot within 12s of a regain in own half
Press→shot /game2.50
#19 of 20 · shot within 8s of a high regain
Speed to final third after regain11.6s
#5 of 20 · lower = faster break

Sequence success — attacking transition

12attacking transition sequences this season
8%succeed — produce a shot
42%turned over with nothing to show

Sequence success — defensive transition

41defensive transition sequences this season
66%succeed — reach the next third or a shot
0%turned over with nothing to show
Vision AI Model Insight
Crystal Palace are a direct, fast-break side: 17% of possessions reach the final third in 3 passes or fewer (#12 of 20), against 23% built patiently over 6+ passes (#16 of 20). Winning the ball back leads to a shot inside 12 seconds 1.15 times a game (#7), and a high regain converts to a shot within 8 seconds 2.50 times a game (#19 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 Crystal Palace? 368 opponent progressive passes and 135 shots faced (14.9 xG against) across the season.

Opponent threat by lane (attacking into Crystal Palace)

Right wing
29%
Right half-space
11%
Central
17%
Left half-space
13%
Left wing
29%
Where the danger came from. Opponents generated most of their threat through the right wing (29% of the danger conceded).

How Do They Concede?

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

Every goal Crystal Palace conceded across the loaded matches — the opponent's shots in Crystal Palace'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 (89 total)

1%2%2%4%3%1%17%18%19%19%12%Hayden HackneyTyrique GeorgeIliman NdiayeIliman NdiayeThierno BarryKiernan Dewsbury-HallMerlin RöhlVitalii MykolenkoKiernan Dewsbury-HallIliman NdiayeJames GarnerTyrique GeorgeHarrison ArmstrongRayan CherkiRúben DiasAntoine SemenyoAntoine SemenyoElliot AndersonRayan CherkiJosko GvardiolPhil FodenAntoine SemenyoRayan CherkiMarc GuéhiPhil FodenJosko GvardiolRúben DiasPhil FodenJoachim AndersenAntonee RobinsonJosh KingShea CharlesGonzalo GarcíaOscar BobbAntonee RobinsonOscar BobbTimothy CastagneShea CharlesCésar PalaciosOscar BobbShea CharlesTimothy CastagneJoachim AndersenOscar BobbSaša LukicRyan SessegnonJosh KingAnton StachEthan AmpaduGabriel GudmundssonJames JustinEthan AmpaduLeif DavisJack ClarkeDara O'SheaDara O'SheaSamuel AmissahFlorentinoJulio EncisoJames McAteeMorgan Gibbs-WhiteNeco WilliamsXaver SchlagerDaniel MuñozDaniel MuñozDan NdoyeMatz SelsIbrahim SangaréLiam DelapMorgan Gibbs-WhiteJames McAteeJacob MurphyJacob MurphyLewis HallJacob MurphyJacob MurphyAmar DedicFabian SchärJoelintonOlivier BoscagliCharalampos KostoulasOlivier BoscagliLewis DunkMaxim De CuyperPascal GroßLuka VuskovicOlivier BoscagliMaxim De CuyperMaxim De Cuyper← own goal

By situation

Open play
17 · 94%
Set pieces
1 · 6%
Penalties
0 · 0%
Vision AI Model Insight
18 goals conceded. 94% come in open play; set pieces account for only 6%, so dead-ball defending is not the main issue. 22% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre of the attacking third (19% 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
7 g · 7.4 xG
Set pieces
1 g · 1.5 xG
Penalties
0 g
12% of goals come from set pieces (1 of 8), worth 1.5 xG from 18 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Crystal Palace's corners go?

29 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 (14)

29%7%14%36%14%
Delivered into the box 100%Short 0%

Left side (15)

13%7%7%33%33%
Delivered into the box 93%Short 7%

Where opponents attack Crystal Palace from set pieces

23 shots from opponent corners against Crystal Palace, 1 conceded, split by the flag the corner came from — arrows from the flag, dots where the shot was taken (gold = goal), shaded by the % of that flag's shots in each zone. Tap or hover a shot for who took it, the minute and the match; filter to one match and the shading recomputes for just that game.

Right flag (11)

9%9%36%36%9%
Shot 11Goals 0

Left flag (12)

25%17%33%8%8%8%
Shot 12Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • none stand out
Weaknesses (bottom-third vs league)
  • xG conceded /game — 1.87 (0th pct)
  • box entries /game — 9.38 (5th pct)
  • press intensity (PPDA) — 6.04 (10th pct)
  • field tilt % — 39.39 (10th pct)
  • threat created /game — 9.07 (10th 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
94%
Coventry
81%
Aston Villa
79%
Hull City
72%
Everton
65%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)1.501.501.50
vs mid-block opponents (2m)0.502.000.50
vs low-block opponents (4m)1.253.000.75

Behaviour — how Crystal Palace actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents71%17%4210.817.0
vs mid-block opponents78%14%368.36.5
vs low-block opponents79%12%368.67.0
Vision AI Model Insight
Facing a high press, retention drops to 71% vs 79% against a low block (8pt lower under pressure), and directness (long-ball share) sits at 17% when pressed vs 12% 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. Crystal Palace are territorially-dominated with a aggressive high-press. Their attack creates 1.12 xG a game and they concede 1.87 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 Crystal Palace’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.

Crystal Palace
across 8 matches this season
Progressive carriesat Everton · 0-2 · 2026-08-2283avg 41
Passesat Everton · 0-2 · 2026-08-22617avg 438
Pass accuracyvs Newcastle · 0-2 · 2026-10-2567%avg 77%
Progressive passesat Brighton · 0-5 · 2026-10-1823avg 38
Expected goalsvs Newcastle · 0-2 · 2026-10-252.09avg 1.12
Final-third entriesat Brighton · 0-5 · 2026-10-1813avg 33
PPDAvs Man City · 1-4 · 2026-08-289.7avg 6.0
Threat from passingvs Newcastle · 0-2 · 2026-10-257.67avg 5.32

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 Crystal Palace’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).

+10.1on-ball value, 8 matches
Where the value came from
Passes3500 actions+4.77
Carries762 actions-0.19
Dribbles94 actions-0.35
Shots88 actions+3.40
Ball wins499 actions+2.52
Most on-ball value (OBV)ActionsOBVper 100
Adam Wharton477+1.46+0.31
Anan Khalaili472+1.13+0.24
Eddie Nketiah95+0.84+0.89
Jørgen Strand Larsen119+0.78+0.66
Walter Benítez206+0.66+0.32
Chris Richards530+0.64+0.12
Daichi Kamada424+0.61+0.14
Axel Disasi194+0.60+0.31
123456
Biggest single movesOBV
1  Jørgen Strand Larsen · pass+0.389
2  Jørgen Strand Larsen · shot+0.301
3  Eddie Nketiah · pass+0.279
4  Daichi Kamada · shot+0.255
5  Anan Khalaili · shot+0.244
6  Anan Khalaili · pass+0.226

Set Pieces by Player

Who delivers Crystal Palace’s dead balls and who finishes them this season. 29 corners taken, most by Adam Wharton (15); 18 shots from corners and free kicks, 1 goals, led by Jefferson Lerma (1 goals, 0.78 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
Yéremy Pino1212 (100%)3—0.093—
Adam Wharton1515 (100%)1—0.03——
Jefferson Lerma——410.78——
Chris Richards——3—0.16——
Darío Osorio——2—0.06——
Daichi Kamada21 (50%)1—0.04——
Anan Khalaili——1—0.18——
Tyrick Mitchell——1—0.02——
Axel Disasi——1—0.07——
Eddie Nketiah——1—0.05——

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
Anan KhalailiCM6856.1Successful Dribble 84%Ball-Carrying 65%Progression 56%Chance Creation 39%
Dean HendersonGK2865.8Shot-Stopping 58%
Chris RichardsCB7605.6Progression 60%Ball-Winning 58%Aerial & Box Defending 36%Ball-Carrying 22%
Adam WhartonCM7414.9Progression 62%Chance Creation 57%Successful Dribble 54%Ball-Carrying 42%
Yéremy PinoCM5544.4Chance Creation 66%Progression 65%Successful Dribble 23%Ball-Carrying 22%
Jaydee CanvotCB6653.8Progression 62%Ball-Carrying 62%Ball-Winning 60%Aerial & Box Defending 33%
Daichi KamadaCM7233.4Successful Dribble 62%Ball-Carrying 60%Progression 39%Chance Creation 29%
Tyrick MitchellCM7202.6Successful Dribble 28%Progression 27%Ball-Carrying 27%Chance Creation 20%
Walter BenítezGK4741.7Shot-Stopping 17%
Jørgen Strand LarsenST4521.4Finishing 37%Ball-Carrying 26%Box Threat 2%Aerial Threat 0%

Top Creators

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

playerposminkey P /90box entriesxT
Yéremy PinoM5541.95187.5
Adam WhartonM7411.46119.1
Daichi KamadaM7230.7586.1
Tyrick MitchellM7200.7555.2
Anan KhalailiM6850.5378.3
Chris RichardsD7600.2467.2
Eddie NketiahM2621.3741.3
Jørgen Strand LarsenF4520.4030.9

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Anan KhalailiM68515927939
Chris RichardsD760152141223
Tyrick MitchellM72011820635
Jaydee CanvotD665117171126
Daichi KamadaM7239715238
Adam WhartonM7419614723
Yéremy PinoM554779323
Quinten TimberM4007213322

Full Squad Data

Every player with 100+ minutes (18 players).

playerposappsmingoalsxGkey PprogdefxT
Chris RichardsD876000.22291527.2
Adam WhartonM874100.21229969.1
Daichi KamadaM872310.7617976.1
Tyrick MitchellM872020.46361185.2
Anan KhalailiM868510.84481598.3
Jaydee CanvotD766500.11231176.5
Yéremy PinoM855410.61228777.5
Walter BenítezG547400.002795.2
Jørgen Strand LarsenF745210.923630.9
Quinten TimberM540000.426722.3
Axel DisasiD430900.519672.1
Dean HendersonG328600.00681.2
Eddie NketiahM726200.646451.3
Dwight McNeilM520600.122271.1
Takehiro TomiyasuD420200.014431.7
Jefferson LermaD417310.808541.9
Honest AhanorD317000.004381.4
Jean-Philippe MatetaF315702.011230.6

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.

Chris Richards
Stopper / marker · Defender
minutes760
goals · xG0 · 0.2
prog passes /903.4
key passes /900.24
def actions /9018.0
pass accuracy82%
Adam Wharton
Ball-winner / destroyer · Midfielder
minutes741
goals · xG0 · 0.2
prog passes /903.5
key passes /901.46
def actions /9011.7
pass accuracy72%
Daichi Kamada
Ball-winner / destroyer · Midfielder
minutes723
goals · xG1 · 0.7
prog passes /902.1
key passes /900.75
def actions /9012.1
pass accuracy84%
Tyrick Mitchell
Ball-winner / destroyer · Midfielder
minutes720
goals · xG2 · 0.4
prog passes /904.5
key passes /900.75
def actions /9014.8
pass accuracy71%
Anan Khalaili
Deep-lying playmaker · Midfielder
minutes685
goals · xG1 · 0.8
prog passes /906.3
key passes /900.53
def actions /9020.9
pass accuracy69%
Jaydee Canvot
Stopper / marker · Defender
minutes665
goals · xG0 · 0.1
prog passes /903.1
key passes /900.14
def actions /9015.8
pass accuracy88%
Yéremy Pino
Advanced creator · Attacking mid
minutes554
goals · xG1 · 0.6
prog passes /904.5
key passes /901.95
def actions /9012.5
pass accuracy71%
Walter Benítez
Goalkeeper · Goalkeeper
minutes474
goals · xG0 · 0.0
prog passes /905.1
key passes /900.00
def actions /901.7
pass accuracy58%
Jørgen Strand Larsen
Ball-winner / destroyer · Midfielder
minutes452
goals · xG1 · 0.9
prog passes /900.6
key passes /900.40
def actions /9012.5
pass accuracy75%

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 (0th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.87, 0th percentile vs the league).
Need — bottom-third: box entries /game (5th pct)
Sign a penetrative wide player or runner to create box entries. The data flags this because few entries into the box (9.38, 5th percentile vs the league).
Need — bottom-third: press intensity (PPDA) (10th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (6.04, 10th percentile vs the league).
Vision AI · building report