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.
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.
#
team
P
W
D
L
GF
GA
GD
Pts
7
Leeds
8
2
5
1
9
6
+3
11
8
Newcastle
8
3
2
3
12
14
-2
11
9
Aston Villa
8
3
2
3
9
12
-3
11
10
Hull City
8
2
4
2
9
8
+1
10
11
Everton
8
2
4
2
8
9
-1
10
12
Ipswich
8
3
1
4
12
16
-4
10
13
Bournemouth
8
2
3
3
12
13
-1
9
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)
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.
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).
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.
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.
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.
Phase
Share of the time
Build-up
27.2%
Progression
41.4%
Chance creation
28.6%
Attacking transition
2.8%
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.
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
Carries
the ball moved with a player
647
ACTIONS
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.
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.
Channel
Entries
Per match
Share
League share
Left wing
88
11.0
39%
29%
Left half-space
21
2.6
9%
16%
Centre
20
2.5
9%
12%
Right half-space
34
4.2
15%
14%
Right wing
65
8.1
29%
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%
Long Wide96 · 17%
Long Central5 · 1%
Wide → FB174 · 31%
Central36 · 6%
◆ 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.
From channel
To channel
From third
To third
Outcome
Minutes
Channel to channel · click a cell
Third to third · click a cell
Progression4 sections
How They Progress — the mechanism
Not just how many progressive passes, but where they start, who plays them, and whether they actually penetrate. 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%
Long Wide37 · 4%
Long Central9 · 1%
Wide → FB384 · 47%
Central107 · 13%
◆ 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.
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
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition33% of shots
28
4
3.01
0.11
Cross
1
0
0.10
0.10
Cut-back
3
1
0.26
0.09
Long ball
2
1
0.32
0.16
Pass into the box / short pass
15
2
1.92
0.13
Own creation (carry, dribble, rebound)
7
0
0.41
0.06
Settled attack49% of shots
42
2
3.28
0.08
Cross
9
1
1.10
0.12
Cut-back
1
0
0.33
0.33
Long ball
2
0
0.15
0.08
Pass into the box / short pass
16
1
1.03
0.06
Own creation (carry, dribble, rebound)
14
0
0.67
0.05
Set piece18% of shots
15
3
2.06
0.14
Corner
12
2
1.22
0.10
Free kick
2
0
0.04
0.02
Penalty
1
1
0.79
0.79
Every attempt to create — and what came of it
Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.
Who sets the shots up
Player
Set-ups
xG created
Goals
Ryan Giles
9
0.92
1
Sorba Thomas
5
0.79
1
Lewie Coyle
3
0.72
0
Mohamed Belloumi
5
0.55
2
Mohamed-Ali Cho
4
0.52
0
Who takes them
Player
Shots
xG
Goals
Oliver McBurnie
10
2.25
1
Joe Gelhardt
9
1.29
1
Mohamed Belloumi
22
1.26
3
Semi Ajayi
3
0.64
1
Mohamed-Ali Cho
5
0.50
1
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%
Long Wide4 · 7%
Long Central9 · 16%
Wide → FB16 · 28%
Central25 · 43%
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.
Territory
Crosses
Share
Led to a shot
byline · left wing
40
31%
5
advanced · left wing
29
23%
3
byline · right wing
24
19%
2
advanced · right wing
21
16%
0
deep · left wing
6
5%
0
deep · right wing
5
4%
0
advanced · right half-space
2
2%
0
byline · right half-space
1
1%
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
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.
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
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#17/23
lower = more intense; rank is what matters
Defensive actions / game
156
#3/23
High-press share
22%
#9/23
def actions won high up
Defensive-action height (0–100)
37.1
#13/23
avg pitch height of actions
High recoveries / game
18.2
#22/23
ball won in mid+att third
High-recovery share
51%
#17/23
share of recoveries won high
Opponent completion allowed
85%
#22/23
lower = more disruptive
Opponent progressive allowed
8.7%
#12/23
of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.
How long they keep it — passes and seconds until the ball is won
The question
Once the opponent has the ball, how many passes and how many seconds pass before 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
Every opponent key pass against them (93 total)
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.
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.
Open play
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)
Delivered into the box 100%Short 0%
Left side (18)
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)
Shot 9Goals 1
Left flag (7)
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 type
goals for/g
goals against/g
points/g
vs high-pressing opponents (2m)
1.50
1.50
1.00
vs mid-block opponents (2m)
1.00
0.50
1.50
vs low-block opponents (4m)
1.00
1.00
1.25
Behaviour — how Hull City actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
67%
25%
34
7.7
11.5
vs mid-block opponents
66%
26%
26
5.7
4.5
vs low-block opponents
69%
22%
34
7.8
9.5
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.]
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.
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)
Actions
OBV
per 100
Konstantinos Tzolakis
408
+1.62
+0.40
Mohamed Belloumi
324
+1.15
+0.36
Oliver McBurnie
211
+1.11
+0.52
Mohamed-Ali Cho
51
+1.10
+2.16
Nobel Mendy
179
+0.86
+0.48
Liam Millar
19
+0.77
+4.07
Sorba Thomas
153
+0.77
+0.50
Semi Ajayi
323
+0.73
+0.23
Biggest single moves
OBV
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.
Player
Corners taken
Into the box
Set-piece shots
Goals
xG
Free-kick shots
Penalties
Mohamed Belloumi
10
7 (70%)
4
1
0.11
2
—
Semi Ajayi
—
—
3
1
0.64
—
—
Joe Gelhardt
2
2 (100%)
2
—
0.06
—
—
Regan Slater
8
6 (75%)
—
—
0.00
—
—
Sorba Thomas
6
6 (100%)
—
—
0.00
—
—
John Egan
—
—
2
—
0.09
—
—
Oliver McBurnie
—
—
1
—
0.10
—
1/1
Ryan Giles
4
4 (100%)
—
—
0.00
—
—
Tim Iroegbunam
—
—
1
—
0.03
—
—
Nobel Mendy
—
—
1
—
0.23
—
—
Mohamed-Ali Cho
1
1 (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.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Mohamed Belloumi
M
612
0.88
20
5.8
Ryan Giles
D
620
1.31
13
6.5
Sorba Thomas
M
282
2.23
11
3.1
Regan Slater
M
698
0.77
6
3.7
Oliver McBurnie
F
737
0.98
4
2.5
Elliot Stroud
M
374
0.72
3
1.6
Lewie Coyle
D
609
0.30
3
4.4
Matt Crooks
M
340
0.26
2
1.6
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.
player
pos
min
crosses (completed)
cutbacks (completed)
Ryan Giles
FB
620
25 (20%)
11 (18%)
Mohamed Belloumi
W
612
12 (33%)
7 (29%)
Lewie Coyle
FB
609
6 (0%)
2 (0%)
Sorba Thomas
W
282
2 (50%)
4 (50%)
Elliot Stroud
W
374
2 (50%)
2 (50%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Oliver McBurnie
F
737
144
4
2
18
John Egan
D
741
139
12
8
20
Semi Ajayi
D
727
114
15
9
27
Mohamed Belloumi
M
612
106
22
10
25
Regan Slater
M
698
87
15
5
19
Nobel Mendy
D
344
74
7
4
8
Lewie Coyle
D
609
70
9
1
21
Ryan Giles
D
620
64
7
4
17
Full Squad Data
Every player with 100+ minutes (19 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Konstantinos Tzolakis
G
8
760
0
0.0
0
57
31
11.1
John Egan
D
8
741
0
0.2
1
8
139
3.2
Oliver McBurnie
F
8
737
1
2.3
8
9
144
2.5
Semi Ajayi
D
8
727
1
0.6
1
19
114
4.7
Regan Slater
M
8
698
0
0.3
6
14
87
3.7
Ryan Giles
D
8
620
0
0.0
9
36
64
6.5
Mohamed Belloumi
M
8
612
3
1.3
6
25
106
5.8
Lewie Coyle
D
8
609
0
0.1
2
19
70
4.4
Elliot Stroud
M
6
374
0
0.1
3
6
56
1.6
Lucas Herrington
D
7
365
0
0.0
1
8
64
2.1
Nobel Mendy
D
5
344
1
0.5
0
8
74
2.1
Matt Crooks
M
5
340
0
0.0
1
8
62
1.6
Sorba Thomas
M
5
282
0
0.4
7
13
36
3.1
Tim Iroegbunam
M
5
232
0
0.9
1
8
49
1.7
Lucas Gourna-Douath
M
3
150
0
0.0
3
4
29
0.9
Brooke Norton-Cuffy
D
4
141
0
0.1
1
2
19
0.4
Mohamed-Ali Cho
M
5
125
1
0.5
5
4
11
0.9
Joe Gelhardt
M
4
115
1
1.3
0
2
24
0.6
Hidemasa Morita
M
4
110
0
0.0
2
2
22
0.6
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).