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Team reportPremier League 2025/26
HC

Hull City

A territorially-dominated side, aggressive high-press out of possession, with a moderate attack. Currently #10 of 20 on 10 points (2-4-2, 9:8). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

territorially-dominatedaggressive high-pressmoderate attack
W
W
D
D
L
D
L
D
10
points
#10 of 20 · 8 games
9:8
goals
+1 GD
2-4-2
record
W-D-L
1.25
points/game
#10 in the league
1.04
xG for/game
rank #20
1.40
xG against/game
rank #12
#17
press rank
of 23 · most aggressive
33%
field tilt
#23
Hull City
League average
Expected goals for / game
1.041.31
Expected goals against / game
1.401.37
Field tilt
33%49%
Pass retention
69%79%
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 Hull City and how good was the season?
Read. Hull City currently sit #10 of 20 on 10 points (2W-4D-2L, 1.25 pts/game), scoring 9 and conceding 8 for a goal difference of +1. On the ball they are a territorially-dominated team (33% field tilt, #23 in the league); off it they defend with a aggressive high-press (#17 of 23 for press intensity). Across the 8 matches of event data, they create 1.04 xG/game (#20) and concede 1.40 (#12), a net of -0.36 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

The question
Where did Hull City actually finish, and against whom?

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

#teamPWDLGFGAGDPts
7Leeds825196+311
8Newcastle83231214-211
9Aston Villa8323912-311
10Hull City824298+110
11Everton824289-110
12Ipswich83141216-410
13Bournemouth82331213-19

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Hull City 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+'+1.02-1.87
Vision AI Model Insight
Hull City tend to stay fairly even across both halves — first-half net xG -1.58, second-half -1.31. Their strongest period is 76-90+' (net +1.02 xG); their most dangerous period to face is 46-60' (net -1.87 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Hull City 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 (-2.9 xG). Hover a point for that match.

048128.411.2Man Utd (H) 2-0 · xG 1.03 to 1.85Coventry (A) 1-0 · xG 0.54 to 1.19Aston Villa (H) 0-0 · xG 0.52 to 1.37Chelsea (A) 2-2 · xG 1.51 to 0.79Newcastle (A) 1-2 · xG 1.54 to 1.48Everton (H) 2-2 · xG 1.35 to 1.51Fulham (A) 0-1 · xG 0.20 to 1.33Brentford (H) 1-1 · xG 1.65 to 1.71M1M2M3M4M5M6M7M8
Hull CityOpponents against Hull City

Tactical DNA

The football question
In five genes, what is Hull City'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.

0
Build-Up
possession control from the back
0
Progression
moving the ball upfield with threat
9
Creation
manufacturing chances
13
Press
winning the ball high & hard
48
Solidity
resisting the opponent's threat
Genetic identity
Hull City are defined most by their Solidity DNA (48/100 · average at resisting the opponent's threat), and least by their Build-Up DNA (0/100). Percentiles vs the 23 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).

Possess0Disrupt28Finish12Press30Defend14
Possess
Deep buildup
0%
Possession
0%
Field tilt
0%
Disrupt
Central progression ~proxy
26%
Dribble tendency
57%
Progressive passes
0%
Finish
Final-third patience
0%
Shot quality
22%
Open-play xG
13%
Press
Forward press ~proxy
26%
High regains
39%
Pressing efficiency ~proxy
26%
Defend
Def-mid press ~proxy
0%
High line ~proxy
43%
PAdj defensive actions
0%
Hull City is defined most by Press (30% in the league) and weakest on Possess (0%). 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 Hull City actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Hull City'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; Hull City highlighted. Hover any dot for the team.

Arsenal: 64% tilt, 2.30 pts/gMan City: 66% tilt, 2.15 pts/gMan Utd: 52% tilt, 1.70 pts/gAston Villa: 49% tilt, 1.65 pts/gLiverpool: 59% tilt, 1.63 pts/gBrighton: 56% tilt, 1.50 pts/gBournemouth: 51% tilt, 1.43 pts/gChelsea: 54% tilt, 1.41 pts/gBrentford: 45% tilt, 1.39 pts/gFulham: 50% tilt, 1.30 pts/gNewcastle: 52% tilt, 1.30 pts/gSunderland: 44% tilt, 1.28 pts/gEverton: 48% tilt, 1.28 pts/gLeeds: 45% tilt, 1.26 pts/gIpswich: 43% tilt, 1.25 pts/gHull City: 33% tilt, 1.25 pts/gCrystal Palace: 44% tilt, 1.13 pts/gNottingham Forest: 48% tilt, 1.09 pts/gTottenham: 52% tilt, 1.09 pts/gWest Ham: 41% tilt, 1.03 pts/gCoventry: 39% tilt, 0.75 pts/gBurnley: 41% tilt, 0.58 pts/gWolves: 39% tilt, 0.53 pts/gHull City33%44%55%66%0.51.11.72.3FIELD TILT %POINTS / GAME
Vision AI Model Insight
Hull City post 33% field tilt, ranking #23 of 23 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 1.25 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 Hull City has the ball, how much of that time is spent building, progressing and creating?

The share of Hull City'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: 27.2% of the time on the ball27%Progression: 41.4% of the time on the ball41%Chance creation: 28.6% of the time on the ball29%Attacking transition: 2.8% of the time on the ball41%PROGRESSION
PhaseShare of the time
Build-up27.2%
Progression41.4%
Chance creation28.6%
Attacking transition2.8%
Vision AI Model Insight
Progression is where Hull City spends most of its time on the ball (41% 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.

Semi Ajayi ↔ Lewie Coyle: 46 passes, -0.4 combined xTLewie Coyle ↔ Mohamed Belloumi: 44 passes, 1.0 combined xTJohn Egan ↔ Semi Ajayi: 43 passes, -0.1 combined xTSemi Ajayi ↔ Konstantinos Tzolakis: 40 passes, -0.4 combined xTKonstantinos Tzolakis ↔ Nobel Mendy: 35 passes, -0.2 combined xTRyan Giles ↔ Nobel Mendy: 32 passes, -0.7 combined xTKonstantinos Tzolakis ↔ Lucas Herrington: 32 passes, -0.2 combined xTJohn Egan ↔ Konstantinos Tzolakis: 31 passes, -0.3 combined xTRegan Slater ↔ Ryan Giles: 31 passes, 0.2 combined xTOliver McBurnie ↔ Konstantinos Tzolakis: 29 passes, 4.3 combined xTJohn Egan ↔ Nobel Mendy: 28 passes, -0.1 combined xTLewie Coyle ↔ Konstantinos Tzolakis: 28 passes, -0.1 combined xTRyan Giles ↔ Sorba Thomas: 26 passes, 0.1 combined xTRyan Giles ↔ Konstantinos Tzolakis: 24 passes, 0.5 combined xTSemi Ajayi ↔ Mohamed Belloumi: 24 passes, 1.6 combined xTJohn Egan ↔ Lucas Herrington: 24 passes, -0.2 combined xTRegan Slater ↔ Lucas Herrington: 21 passes, -0.3 combined xTRegan Slater ↔ Mohamed Belloumi: 20 passes, 0.3 combined xTMatt Crooks ↔ Lewie Coyle: 20 passes, 0.0 combined xTRyan Giles ↔ Lucas Herrington: 20 passes, 0.1 combined xTRegan Slater ↔ Sorba Thomas: 19 passes, 0.2 combined xTJohn Egan ↔ Regan Slater: 19 passes, 0.1 combined xTSemi Ajayi ↔ Regan Slater: 19 passes, 0.0 combined xTTim Iroegbunam ↔ Mohamed Belloumi: 19 passes, 0.5 combined xTTim Iroegbunam — isolate this player's connectionsIroegbunamMohamed Belloumi — isolate this player's connectionsBelloumiJohn Egan — isolate this player's connectionsEganOliver McBurnie — isolate this player's connectionsMcBurnieSemi Ajayi — isolate this player's connectionsAjayiLewie Coyle — isolate this player's connectionsCoyleRegan Slater — isolate this player's connectionsSlaterRyan Giles — isolate this player's connectionsGilesKonstantinos Tzolakis — isolate this player's connectionsTzolakisLucas Herrington — isolate this player's connectionsHerringtonElliot Stroud — isolate this player's connectionsStroudNobel Mendy — isolate this player's connectionsMendySorba Thomas — isolate this player's connectionsThomasMatt Crooks — isolate this player's connectionsCrooksHidemasa Morita — isolate this player's connectionsMoritaBrooke Norton-Cuffy — isolate this player's connectionsNorton-Cuf
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Ajayi ↔ Coyle
46p · -0.4xT
Coyle ↔ Belloumi
44p · 1.0xT
Egan ↔ Ajayi
43p · -0.1xT
Ajayi ↔ Tzolakis
40p · -0.4xT
Tzolakis ↔ Mendy
35p · -0.2xT
Giles ↔ Mendy
32p · -0.7xT
Tzolakis ↔ Herrington
32p · -0.2xT
Egan ↔ Tzolakis
31p · -0.3xT
Slater ↔ Giles
31p · 0.2xT
McBurnie ↔ Tzolakis
29p · 4.3xT
Vision AI Model Insight
Busiest connection: Semi Ajayi ↔ Lewie Coyle (46 passes). Most dangerous per pass: Oliver McBurnie ↔ Konstantinos Tzolakis (0.15 xT/pass over 29 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Hull City had the ball

Every touch across 460 matches. Brighter means more touches.

Which Zones Do They Attack Through?

The question
Across the whole pitch, where does Hull City 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
2552
ACTIONS
4%5%14%6%6%11%7%8%8%10%6%3%2%3%8%PASSES
Carries
the ball moved with a player
647
ACTIONS
3%4%11%6%4%8%10%11%10%11%6%4%2%3%7%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (13.1% of all actions). 57% of actions run through the inside lanes (centre + both half-spaces) versus 43% down the two wings — an inside-dominant, half-space build. By third: 32% defensive, 45% middle, 23% 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. Hull City leaned on their left (40%). The bars under the pitch put the league’s share beside theirs.

40%Left side21%Middle39%Right sideATTACKING →
Hull City
40%21%39%
League
39%23%38%

Final-Third Entries

Every completed pass or carry that took the ball from outside the final third into it, by the channel it arrived in. Hull City made 228 this season (28.5 a match); 39% 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: 88 entries (39%)8839%LEFT WINGLeft half-space: 21 entries (9%)219%LEFT HALF-SPACECentre: 20 entries (9%)209%CENTRERight half-space: 34 entries (15%)3415%RIGHT HALF-SPACERight wing: 65 entries (29%)6529%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing8811.039%29%
Left half-space212.69%16%
Centre202.59%12%
Right half-space344.215%14%
Right wing658.129%29%
Build-up2 sections

Build-Up — the pass map

The football question
How does Hull City 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.

862build-up passes attempted
66%completed
34%reach the middle third
4%go long into the final third

Pass types

255CB · 45%
96Long Wide · 17%
5Long Central · 1%
174Wide → FB · 31%
36Central · 6%
CB255 · 45%
left: 148 passes, most from Egan148right: 107 passes, most from Ajayi107
Long Wide96 · 17%
left: 49 passes, most from Tzolakis49right: 47 passes, most from Tzolakis47
Long Central5 · 1%
left: 4 passes, most from Giles4
Wide → FB174 · 31%
left: 107 passes, most from Tzolakis107right: 67 passes, most from Tzolakis67
Central36 · 6%
right: 23 passes, most from Tzolakis23left: 13 passes, most from Slater13
◆ Vision AI Insight
Hull City build predominantly down the left, with Tzolakis as the fulcrum (165 build-up passes). Only 37% 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 RHS def → C def (34×).

Pass Explorer

Every pass of Hull City’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. 257 progressive passes across 8 matches (32.1/game).

Origin lane

Right wing
25%
Right half-space
12%
Central
19%
Left half-space
12%
Left wing
33%
Progression is left-dominant: 37% right side · 19% central · 44% left.

Who generates it

Konstantinos Tzolakis
57 · 22%
Ryan Giles
36 · 14%
Mohamed Belloumi
25 · 10%
Lewie Coyle
19 · 7%
Semi Ajayi
19 · 7%
Top two — Konstantinos Tzolakis & Ryan Giles — account for 36% of all progression.
PROGRESSION
32.1 prog passes/game
mostly left
→
PENETRATION
28% reach final third
19% reach the box
→
THREAT
the other 72% is recycled
progress ≠ danger
What came of it. 28% of progressive passes reached the final third and 19% the box; the rest was recycled in front of the block. 36% 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 wingefficient

Progression — the pass map

The football question
Once Hull City 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.

1094progression passes attempted
75%completed
18%break into the final third
16%go backward into the defensive third

Pass types

287CB · 35%
37Long Wide · 4%
9Long Central · 1%
384Wide → FB · 47%
107Central · 13%
CB287 · 35%
left: 163 passes, most from Herrington163right: 124 passes, most from Ajayi124
Long Wide37 · 4%
left: 23 passes, most from Giles23right: 14 passes, most from Coyle14
Long Central9 · 1%
right: 5 passes, most from Coyle5left: 4 passes, most from Slater4
Wide → FB384 · 47%
right: 200 passes, most from Coyle200left: 184 passes, most from Giles184
Central107 · 13%
left: 57 passes, most from Slater57right: 50 passes, most from Slater50
◆ Vision AI Insight
Hull City progress predominantly down the left, with Slater the busiest midfield outlet (101 progression passes). Only 18% of passes that start in midfield actually break the final-third line — the rest (65%) is recycled back into midfield or (16%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LW mid → LHS mid (38×) — press that lane and midfield progression stalls.

Decision Quality — not all completed passes are equal

A 90% pass completion can hide a sideways habit. Grading every pass by the threat it adds separates value creation from safe circulation.

Excellent (high xT gain)
14%
Progressive
1%
Neutral / sideways
53%
Safe / backward
32%
15% of passes are progressive-or-better; the remaining 85% 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 Hull City actually progress the ball with their feet, not a pass?

143 progressive carries this season across the whole squad (27% of 538 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 16m, longest 50m. Most active carrier: Giles (24). Filter to one player below.

First (42)Second (38)Third (35)Fourth (28)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 Hull City'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.

85shots
8.4xG
0.10xG per shot
5big chances (0.3+ xG)
9goals
#18key passes / game in the league
#23box entries / game in the league
Attacking transition: 28 shots (33%)33%28Settled attack: 42 shots (49%)49%42Set piece: 15 shots (18%)18%1585SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 33% of shots2843.010.11
Cross100.100.10
Cut-back310.260.09
Long ball210.320.16
Pass into the box / short pass1521.920.13
Own creation (carry, dribble, rebound)700.410.06
Settled attack 49% of shots4223.280.08
Cross911.100.12
Cut-back100.330.33
Long ball200.150.08
Pass into the box / short pass1611.030.06
Own creation (carry, dribble, rebound)1400.670.05
Set piece 18% of shots1532.060.14
Corner1221.220.10
Free kick200.040.02
Penalty110.790.79

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
Ryan Giles90.921
Sorba Thomas50.791
Lewie Coyle30.720
Mohamed Belloumi50.552
Mohamed-Ali Cho40.520

Who takes them

PlayerShotsxGGoals
Oliver McBurnie102.251
Joe Gelhardt91.291
Mohamed Belloumi221.263
Semi Ajayi30.641
Mohamed-Ali Cho50.501
Vision AI Model Insight
The biggest source of Hull City's chances, by xG, is settled attack (3.3 of 8.4 xG, 42 of 85 shots), mostly cross. 28 of the 85 shots (33%) came within 15 seconds of winning the ball. 15 of the 85 shots came from set pieces; 9 goals from 8.4 xG (+0.6).

Chance Creation — the pass map

The football question
How does Hull City 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 · 7%
4Long Wide · 7%
9Long Central · 16%
16Wide → FB · 28%
25Central · 43%

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 · 7%
right: 3 passes, most from Herrington3
Long Wide4 · 7%
right: 3 passes, most from Slater3
Long Central9 · 16%
right: 7 passes, most from Giles7left: 2 passes, most from Thomas2
Wide → FB16 · 28%
right: 9 passes, most from Slater9left: 7 passes, most from McBurnie7
Central25 · 43%
right: 14 passes, most from McBurnie14left: 11 passes, most from Slater11

Who creates — volume × threat

9Giles
8McBurnie
7Thomas
6Slater
6Belloumi
5Cho
3Gourna-Douath
58key passes #18 of 23
8.8box entries/game #23 of 23
21.6final-3rd entries/game #23 of 23
1.04xG/game #20 of 23
9goals #22 of 23
+0.6finishing vs xG #13 of 23
◆ Vision AI Insight
Hull City lean left — 45% of their key passes come from that flank and its half-space (26 of 58), most often from Giles (9). They funnel chances into the c of the final third, most often via LW att → C att (13 key passes, most often from Giles). Giles is the primary source overall. They generate 1.04 xG a game and finish it clinical — they beat their xG, led by Mohamed Belloumi (3G), Nobel Mendy (1G), Mohamed-Ali Cho (1G).

Crosses & Cutbacks — squad-wide

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

128 crosses: 29 found a team-mate (23%), 10 led to a shot (8%). 22 cut-backs: 7 found a team-mate (32%), 5 led to a shot (23%). 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 Hull City actually cross from?

128 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. 31% come from one territory, the byline left wing; 3 come from the half-spaces and 0 from the centre.

deep right wing: 5 crosses (4%)4%5deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 6 crosses (5%)5%6advanced right wing: 21 crosses (16%)16%21advanced right half-space: 2 crosses (2%)2%2advanced centre: 0 crosses (0%)advanced left half-space: 0 crosses (0%)advanced left wing: 29 crosses (23%)23%29byline right wing: 24 crosses (19%)19%24byline right half-space: 1 crosses (1%)1%1byline centre: 0 crosses (0%)byline left half-space: 0 crosses (0%)byline left wing: 40 crosses (31%)31%40
TerritoryCrossesShareLed to a shot
byline · left wing4031%5
advanced · left wing2923%3
byline · right wing2419%2
advanced · right wing2116%0
deep · left wing65%0
deep · right wing54%0
advanced · right half-space22%0
byline · right half-space11%0
Finishing3 sections

Shot Map

85 shots for 8.4 xG (1.04/game, #20 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

Moderate attack. 10.6 shots/game at 0.098 xG/shot. Box entries 9/game (#23). Threat created 7.3 xT/game (#23).

Goal Sequences

The move behind each of Hull City’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 Hull City scored across the loaded matches, broken down by how it was created and finished.

By situation

Open play
6 · 67%
Set pieces
2 · 22%
Penalties
1 · 11%

By finish

Right foot
3 · 33%
Left foot
5 · 56%
Header
1 · 11%
Vision AI Model Insight
9 goals scored. 67% come in open play, but 22% from set pieces — a genuine dead-ball weapon that bypasses the open-play build-up.
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

40 of 98 pass attempts lost here (41%).41%40/98Coyle36 of 116 pass attempts lost here (31%).31%36/116Tzolakis134 of 351 pass attempts lost here (38%).38%134/351Tzolakis44 of 156 pass attempts lost here (28%).28%44/156Tzolakis42 of 141 pass attempts lost here (30%).30%42/141Giles78 of 269 pass attempts lost here (29%).29%78/269McBurnie47 of 175 pass attempts lost here (27%).27%47/175Ajayi43 of 202 pass attempts lost here (21%).21%43/202Belloumi45 of 200 pass attempts lost here (22%).22%45/200Egan57 of 248 pass attempts lost here (23%).23%57/248Giles64 of 155 pass attempts lost here (41%).41%64/155Belloumi39 of 88 pass attempts lost here (44%).44%39/88McBurnie16 of 62 pass attempts lost here (26%).26%16/62McBurnie28 of 82 pass attempts lost here (34%).34%28/82Giles90 of 209 pass attempts lost here (43%).43%90/209Gilesattacking →

How they lose it

Incomplete pass — attacking third
237
Failed forward pass
162
Failed take-on
45
Lost in the defensive third
296
Their weakest zone is the right half-space in the attacking third: 44% of 88 pass attempts there are lost (39 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 Hull City 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.

35
Pressing Index
/100 · passive
Intensity55
PPDA, high-press share, high-zone actions
Height43
how high up the pitch they defend
Effectiveness15
high recoveries & high-regain share
Disruption26
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
20%
RHS
17%
C
21%
LHS
21%
LW
20%
By third (high / mid / low regain)
Def 52%
Mid 33%
Att 15%
Read
Ranked #17 of 23 for press intensity, this is a high press. Note the tension: 52% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (22% high-press share) means that when they do defend, it is often deep. Of recoveries, 51% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#17/23lower = more intense; rank is what matters
Defensive actions / game156#3/23
High-press share22%#9/23def actions won high up
Defensive-action height (0–100)37.1#13/23avg pitch height of actions
High recoveries / game18.2#22/23ball won in mid+att third
High-recovery share51%#17/23share of recoveries won high
Opponent completion allowed85%#22/23lower = more disruptive
Opponent progressive allowed8.7%#12/23of 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 Hull City win it back with a defensive action?

Counted over the 223 opposition possessions that Hull City 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 Hull City step in. Hull City win it after 6.0 opponent passes in the first half-hour and after 7.4 after the hour mark (later).

PASSES THEY GET
6.5passes
median 4 · before Hull City win it
TIME THEY KEEP IT
20sec
median 11s · 27.9 wins per game
How many passes the opponent got in before the ball was won
30%
32%
20%
18%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
5.5
17s
15–30′
6.6
20s
30–45+′
5.2
16s
45–60′
6.5
20s
60–75′
8.2
24s
75–90+′
6.8
20s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Hull City 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 Hull City 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) 862 passes

longer passing, trying to break lines, more direct

Width of use-0.3820.21
Wide-channel share-0.210.29
Side bias+0.652.60
Pass length+2.0530.10
Long-ball share+1.850.41
Forward gain per pass+1.8119.31
Backward-pass share-0.410.18
Deep-pass share+2.020.48
Completion-1.620.66
Seconds between passes+0.703.75
Side used

left 29% · central 50% · right 21%

Progression (middle third) 1,094 passes

riskier, longer passing, played in the channels

Width of use+1.0827.87
Wide-channel share+1.180.49
Side bias-0.03-0.07
Pass length+1.2719.00
Long-ball share+1.170.15
Forward gain per pass+0.854.89
Backward-pass share-0.240.32
Deep-pass share+0.950.21
Completion-1.490.75
Seconds between passes+0.693.50
Side used

left 38% · central 25% · right 37%

Final third 596 passes

riskier, attacking the next line, longer passing

Width of use+0.6133.12
Wide-channel share+0.480.63
Side bias+0.674.24
Pass length+1.0017.02
Long-ball share+0.840.14
Forward gain per pass+1.052.44
Backward-pass share-1.000.32
Deep-pass share+0.640.11
Completion-1.360.59
Seconds between passes+0.303.62
Side used

left 47% · central 16% · right 37%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Hull City'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 Hull City 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 share20%
#1 of 23 · reaches final third in ≤3 passes
Patient build-up share14%
#23 of 23 · spells of 6+ passes
Tempo (possession length)11.4s
#1 of 23 · shorter = faster tempo
Passes per possession3.0
#23 of 23
Counter-attack shots /game1.25
#3 of 23 · shot within 12s of a regain in own half
Press→shot /game3.62
#2 of 23 · shot within 8s of a high regain
Speed to final third after regain9.5s
#1 of 23 · lower = faster break
Vision AI Model Insight
Hull City are a direct, fast-break side: 20% of possessions reach the final third in 3 passes or fewer (#1 of 23), against 14% built patiently over 6+ passes (#23 of 23). Winning the ball back leads to a shot inside 12 seconds 1.25 times a game (#3), and a high regain converts to a shot within 8 seconds 3.62 times a game (#2 of 23) — a genuine transition weapon.
Defending the box2 sections

Vulnerability Map — how opponents hurt them

The report flipped: where do opponents create their threat against Hull City? 451 opponent progressive passes and 116 shots faced (11.2 xG against) across the season.

Opponent threat by lane (attacking into Hull City)

Right wing
29%
Right half-space
13%
Central
16%
Left half-space
14%
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 Hull City actually come from — open play, dead balls, and who supplies them?

Every goal Hull City conceded across the loaded matches — the opponent's shots in Hull City'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 (93 total)

2%1%3%2%1%15%20%20%18%16%Luke ShawNoussair MazraouiHarry MaguireLuke ShawBryan MbeumoMatheus CunhaBruno FernandesBruno FernandesMarcus RashfordLuke ShawLuke ShawNoussair MazraouiMatheus CunhaHarry MaguireMarcus RashfordDiogo DalotMarcus RashfordMarcus RashfordBruno FernandesJack RudoniJack RudoniTaiwo AwoniyiEphron Mason-ClarkCaleb YirenkyiMatt GrimesLoum TchaounaMilan van EwijkTaiwo AwoniyiMilan van EwijkIan MaatsenRoss BarkleyMatty CashVictor LindelöfBoubacar KamaraNicolas JacksonGeorge HemmingsVictor LindelöfLewis HallHarvey BarnesLewis MileyHarvey BarnesJacob MurphyLewis HallSean SteurSean SteurFabian SchärHarvey BarnesJoão PedroCole PalmerPedro NetoCole PalmerLevi ColwillMalo GustoCole PalmerDanny WelbeckKiernan Dewsbury-HallJames GarnerHarrison ArmstrongJames GarnerAinsley Maitland-NilesJack GrealishHarrison ArmstrongJack GrealishBrennan JohnsonAinsley Maitland-NilesJarrad BranthwaiteMichael KayodeMichael KayodeDango OuattaraMichael KayodeDango OuattaraMichael KayodeJaidon AnthonyIgor ThiagoDango OuattaraMikkel DamsgaardMathias JensenMikkel DamsgaardJosh KingJosh KingSaša LukicOscar BobbSander BergeSaša LukicGonzalo GarcíaOscar BobbShea CharlesGonzalo GarcíaOscar BobbJosh KingSaša LukicAntonee RobinsonCésar Palacios← own goal

By situation

Open play
7 · 88%
Set pieces
1 · 12%
Penalties
0 · 0%
Vision AI Model Insight
8 goals conceded. 88% come in open play; set pieces account for only 12%, so dead-ball defending is not the main issue. 12% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right half-space of the attacking third (20% 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
6 g · 6.3 xG
Set pieces
2 g · 1.3 xG
Penalties
1 g
22% of goals come from set pieces (2 of 9), worth 1.3 xG from 14 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Hull City's corners go?

31 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 (13)

31%23%8%31%8%
Delivered into the box 100%Short 0%

Left side (18)

6%17%6%6%6%11%28%22%
Delivered into the box 100%Short 0%

Where opponents attack Hull City from set pieces

16 shots from opponent corners against Hull City, 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 (9)

22%33%22%11%11%
Shot 9Goals 1

Left flag (7)

14%29%29%14%14%
Shot 7Goals 0

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • none stand out
Weaknesses (bottom-third vs league)
  • field tilt % — 33.03 (0th pct)
  • progression /game — 32.12 (0th pct)
  • box entries /game — 8.75 (0th pct)
  • threat created /game — 7.27 (0th pct)
  • pass retention % — 68.53 (0th 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.

Coventry
95%
Sunderland
92%
Leeds
75%
Crystal Palace
71%
Wolves
71%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)1.501.501.00
vs mid-block opponents (2m)1.000.501.50
vs low-block opponents (4m)1.001.001.25

Behaviour — how Hull City actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents67%25%347.711.5
vs mid-block opponents66%26%265.74.5
vs low-block opponents69%22%347.89.5
Vision AI Model Insight
Facing a high press, retention drops to 67% vs 69% against a low block (2pt lower under pressure), and directness (long-ball share) sits at 25% when pressed vs 22% against a low block — a mild adjustment, not a wholesale change.

Scouting Summary — the team in brief

In brief. Hull City are territorially-dominated with a aggressive high-press. Their attack creates 1.04 xG a game and they concede 1.40 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 Hull City’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.

Hull City
across 8 matches this season
Progressive carriesat Newcastle · 1-2 · 2026-09-1944avg 28
Progressive passesat Newcastle · 1-2 · 2026-09-1949avg 32
PPDAat Fulham · 0-1 · 2026-10-179.5avg 6.5
Final-third entriesat Newcastle · 1-2 · 2026-09-1944avg 28
Passesat Newcastle · 1-2 · 2026-09-19437avg 319
Pass accuracyat Newcastle · 1-2 · 2026-09-1976%avg 68%
Field tiltat Newcastle · 1-2 · 2026-09-1956%avg 33%
Threat from passingat Fulham · 0-1 · 2026-10-172.62avg 4.42

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 Hull City’s last 8 matches added up: where the value came from, who produced it, and the six biggest single moves. OBV only measures what a player does with the ball: it shows who added the most on-ball value, not who was the most important player (defending off the ball, positioning and pressing are not in it).

+11.1on-ball value, 8 matches
Where the value came from
Passes2552 actions+3.38
Carries538 actions+0.37
Dribbles101 actions+0.44
Shots85 actions+4.54
Ball wins436 actions+2.32
Most on-ball value (OBV)ActionsOBVper 100
Konstantinos Tzolakis408+1.62+0.40
Mohamed Belloumi324+1.15+0.36
Oliver McBurnie211+1.11+0.52
Mohamed-Ali Cho51+1.10+2.16
Nobel Mendy179+0.86+0.48
Liam Millar19+0.77+4.07
Sorba Thomas153+0.77+0.50
Semi Ajayi323+0.73+0.23
123456
Biggest single movesOBV
1  Oliver McBurnie · shot+0.760
2  Semi Ajayi · shot+0.483
3  Mohamed-Ali Cho · pass+0.413
4  Mohamed-Ali Cho · pass+0.403
5  Oliver McBurnie · shot+0.289
6  Nobel Mendy · shot+0.289

Set Pieces by Player

Who delivers Hull City’s dead balls and who finishes them this season. 31 corners taken, most by Mohamed Belloumi (10); 14 shots from corners and free kicks, 2 goals, led by Semi Ajayi (1 goals, 0.64 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
Mohamed Belloumi107 (70%)410.112—
Semi Ajayi——310.64——
Joe Gelhardt22 (100%)2—0.06——
Regan Slater86 (75%)——0.00——
Sorba Thomas66 (100%)——0.00——
John Egan——2—0.09——
Oliver McBurnie——1—0.10—1/1
Ryan Giles44 (100%)——0.00——
Tim Iroegbunam——1—0.03——
Nobel Mendy——1—0.23——
Mohamed-Ali Cho11 (100%)——0.00——

Top Performers

Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 216 minutes). Coloured chips are that player's strongest capability blocks.

playerposminVision AI Scorecapability blocks
Mohamed BelloumiW6126.6Box Threat 57%Chance Creation 50%Ball-Carrying 50%Wide Delivery 28%
Regan SlaterCM6985.4Successful Dribble 92%Ball-Carrying 46%Chance Creation 27%Progression 9%
John EganCB7414.2Breaking Pressure 46%Aerial & Box Defending 43%Ball-Winning 37%Progression 3%
Oliver McBurnieST7373.9Ball-Carrying 40%Finishing 31%Box Threat 15%Aerial Threat 0%
Semi AjayiCB7273.9Breaking Pressure 68%Ball-Winning 54%Progression 12%Aerial & Box Defending 8%
Konstantinos TzolakisGK7603.2Shot-Stopping 32%
Ryan GilesFB6202.8Ball-Carrying 72%Breaking Pressure 61%Wide Delivery 28%Ball-Winning 18%
Lewie CoyleFB6090.8Breaking Pressure 33%Ball-Winning 16%Ball-Carrying 12%Wide Delivery 7%

Top Creators

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

playerposminkey P /90box entriesxT
Mohamed BelloumiM6120.88205.8
Ryan GilesD6201.31136.5
Sorba ThomasM2822.23113.1
Regan SlaterM6980.7763.7
Oliver McBurnieF7370.9842.5
Elliot StroudM3740.7231.6
Lewie CoyleD6090.3034.4
Matt CrooksM3400.2621.6

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)
Ryan GilesFB62025 (20%)11 (18%)
Mohamed BelloumiW61212 (33%)7 (29%)
Lewie CoyleFB6096 (0%)2 (0%)
Sorba ThomasW2822 (50%)4 (50%)
Elliot StroudW3742 (50%)2 (50%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Oliver McBurnieF7371444218
John EganD74113912820
Semi AjayiD72711415927
Mohamed BelloumiM612106221025
Regan SlaterM6988715519
Nobel MendyD34474748
Lewie CoyleD609709121
Ryan GilesD620647417

Full Squad Data

Every player with 100+ minutes (19 players).

playerposappsmingoalsxGkey PprogdefxT
Konstantinos TzolakisG876000.00573111.1
John EganD874100.2181393.2
Oliver McBurnieF873712.3891442.5
Semi AjayiD872710.61191144.7
Regan SlaterM869800.3614873.7
Ryan GilesD862000.0936646.5
Mohamed BelloumiM861231.36251065.8
Lewie CoyleD860900.1219704.4
Elliot StroudM637400.136561.6
Lucas HerringtonD736500.018642.1
Nobel MendyD534410.508742.1
Matt CrooksM534000.018621.6
Sorba ThomasM528200.4713363.1
Tim IroegbunamM523200.918491.7
Lucas Gourna-DouathM315000.034290.9
Brooke Norton-CuffyD414100.112190.4
Mohamed-Ali ChoM512510.554110.9
Joe GelhardtM411511.302240.6
Hidemasa MoritaM411000.022220.6

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.

Konstantinos Tzolakis
Goalkeeper · Goalkeeper
minutes760
goals · xG0 · 0.0
prog passes /906.8
key passes /900.00
def actions /903.7
pass accuracy49%
John Egan
Stopper / marker · Defender
minutes741
goals · xG0 · 0.2
prog passes /901.0
key passes /900.12
def actions /9016.9
pass accuracy78%
Oliver McBurnie
Ball-winner / destroyer · Midfielder
minutes737
goals · xG1 · 2.3
prog passes /901.1
key passes /900.98
def actions /9017.6
pass accuracy57%
Semi Ajayi
Stopper / marker · Defender
minutes727
goals · xG1 · 0.6
prog passes /902.4
key passes /900.12
def actions /9014.1
pass accuracy79%
Regan Slater
Ball-winner / destroyer · Midfielder
minutes698
goals · xG0 · 0.3
prog passes /901.8
key passes /900.77
def actions /9011.2
pass accuracy79%
Ryan Giles
Ball-playing defender · Defender
minutes620
goals · xG0 · 0.0
prog passes /905.2
key passes /901.31
def actions /909.3
pass accuracy63%
Mohamed Belloumi
Ball-winner / destroyer · Midfielder
minutes612
goals · xG3 · 1.3
prog passes /903.7
key passes /900.88
def actions /9015.6
pass accuracy61%
Lewie Coyle
Stopper / marker · Defender
minutes609
goals · xG0 · 0.1
prog passes /902.8
key passes /900.30
def actions /9010.3
pass accuracy71%
Elliot Stroud
Ball-winner / destroyer · Midfielder
minutes374
goals · xG0 · 0.1
prog passes /901.4
key passes /900.72
def actions /9013.5
pass accuracy69%

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: field tilt % (0th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (33.03, 0th percentile vs the league).
Need — bottom-third: progression /game (0th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (32.12, 0th percentile vs the league).
Need — bottom-third: box entries /game (0th pct)
Sign a penetrative wide player or runner to create box entries. The data flags this because few entries into the box (8.75, 0th percentile vs the league).
Vision AI · building report