Combining every season — this one is larger, give it a moment.
Team reportPremier League 2026
Nottingham Forest
A balanced-territory side, aggressive high-press out of possession, with a high-volume attack. Currently #18 of 20 on 6 points (1-3-4, 6:10). 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 Nottingham Forest and how good was the season?
Read. Nottingham Forest currently sit #18 of 20 on 6 points (1W-3D-4L, 0.75 pts/game), scoring 6 and conceding 10 for a goal difference of -4.
On the ball they are a balanced-territory team (48% field tilt, #11 in the league); off it they defend with a aggressive high-press (#13 of 20 for press intensity).
Across the 8 matches of event data, they create 1.65 xG/game (#3) and concede 1.05 (#3), a net of +0.59 xG/game — the underlying performance diverges from the actual goal difference.
Season Context — the league table
The question
Where did Nottingham Forest actually finish, and against whom?
The authoritative final table (full season), centred on Nottingham Forest.
#
team
P
W
D
L
GF
GA
GD
Pts
15
Fulham
8
2
2
4
8
10
-2
8
16
Man Utd
8
1
4
3
10
13
-3
7
17
Crystal Palace
8
2
1
5
9
19
-10
7
18
Nottingham Forest
8
1
3
4
6
10
-4
6
19
Coventry
8
2
0
6
6
15
-9
6
20
Sunderland
8
1
2
5
6
14
-8
5
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Nottingham Forest 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
Nottingham Forest tend to stay fairly even across both halves — first-half net xG +2.26, second-half +2.47. Their strongest period is 61-75' (net +2.03 xG); their most dangerous period to face is 46-60' (net -0.26 xG against them).
xG Race — the season, match by match
Expected goals piling up over 8 matches: Nottingham Forest 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 (+4.7 xG). Hover a point for that match.
Nottingham ForestOpponents against Nottingham Forest
Tactical DNA
The football question
In five genes, what is Nottingham Forest'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.
35
Build-Up
possession control from the back
65
Progression
moving the ball upfield with threat
80
Creation
manufacturing chances
40
Press
winning the ball high & hard
85
Solidity
resisting the opponent's threat
Genetic identity
Nottingham Forest are defined most by their Solidity DNA (85/100 · elite at resisting the opponent's threat), and least by their Build-Up DNA (35/100). Percentiles vs the 20 teams in the league.
The Playstyle Wheel
Fifteen style metrics across five domains — Possess, Disrupt, Finish, Press, Defend — each a percentile against the rest of the league. Metrics marked ~proxy use the closest available event-data signal where the standard definition needs data this feed doesn't carry (explicit pressure events, offside/keeper-sweep incidents).
Possess
Deep buildup
22%
Possession
43%
Field tilt
43%
Disrupt
Central progression ~proxy
52%
Dribble tendency
70%
Progressive passes
61%
Finish
Final-third patience
26%
Shot quality
13%
Open-play xG
48%
Press
Forward press ~proxy
22%
High regains
52%
Pressing efficiency ~proxy
13%
Defend
Def-mid press ~proxy
39%
High line ~proxy
22%
PAdj defensive actions
39%
Nottingham Forest is defined most by Disrupt (61% in the league) and weakest on Finish (29%). 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 Nottingham Forest actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Nottingham Forest'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; Nottingham Forest highlighted. Hover any dot for the team.
Vision AI Model Insight
Nottingham Forest post 48% field tilt, ranking #11 of 20 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 0.75 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 Nottingham Forest has the ball, how much of that time is spent building, progressing and creating?
The share of Nottingham Forest'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
27.8%
Progression
41.7%
Chance creation
27.3%
Attacking transition
3.3%
Vision AI Model Insight
Progression is where Nottingham Forest spends most of its time on the ball (42% 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
Williams ↔ Murillo
118p · -0.1xT
Sels ↔ Murillo
62p · -0.2xT
Milenkovic ↔ Murillo
60p · -0.3xT
Gibbs-White ↔ McAtee
56p · 1.6xT
McAtee ↔ Murillo
56p · 0.7xT
Schlager ↔ Murillo
55p · -0.2xT
Gibbs-White ↔ Muñoz
54p · 2.3xT
Williams ↔ McAtee
54p · 1.0xT
Muñoz ↔ McAtee
54p · 0.1xT
Schlager ↔ Gibbs-White
45p · 1.4xT
Vision AI Model Insight
Busiest connection: Neco Williams ↔ Murillo (118 passes). Most dangerous per pass: Morgan Gibbs-White ↔ Neco Williams (0.05 xT/pass over 34 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Nottingham Forest 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 Nottingham Forest 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
3391
ACTIONS
Carries
the ball moved with a player
664
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (11.3% of all actions). 60% of actions run through the inside lanes (centre + both half-spaces) versus 40% down the two wings — an inside-dominant, half-space build. By third: 32% defensive, 44% middle, 24% 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. Nottingham Forest leaned on their right (37%). The bars under the pitch put the league’s share beside theirs.
Nottingham Forest
36%27%37%
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. Nottingham Forest made 326 this season (40.8 a match); 28% 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
90
11.2
28%
31%
Left half-space
53
6.6
16%
16%
Centre
44
5.5
13%
13%
Right half-space
56
7.0
17%
14%
Right wing
83
10.4
25%
27%
Build-up2 sections
Build-Up — the pass map
The football question
How does Nottingham Forest 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.
1129build-up passes attempted
75%completed
30%reach the middle third
3%go long into the final third
Pass types
392CB · 46%
73Long Wide · 9%
18Long Central · 2%
289Wide → FB · 34%
73Central · 9%
Sequence success — build-up
139build-up sequences this season
6%succeed — reach the next third or a shot
50%turned over with nothing to show
CB392 · 46%
Long Wide73 · 9%
Long Central18 · 2%
Wide → FB289 · 34%
Central73 · 9%
◆ Vision AI Insight
Nottingham Forest build predominantly down the left, with Murillo as the fulcrum (156 build-up passes). Only 34% 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 (50×).
Pass Explorer
Every pass of Nottingham Forest’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. 385 progressive passes across 8 matches (48.1/game).
Origin lane
Right wing
29%
Right half-space
12%
Central
19%
Left half-space
10%
Left wing
29%
Progression is right-dominant: 42% right side · 19% central · 39% left.
Who generates it
Neco Williams
61 · 16%
Matz Sels
51 · 13%
James McAtee
38 · 10%
Morgan Gibbs-White
38 · 10%
Murillo
37 · 10%
Top two — Neco Williams & Matz Sels — account for 29% of all progression.
PROGRESSION
48.1 prog passes/game
mostly right
→
PENETRATION
30% reach final third
21% reach the box
→
THREAT
the other 70% is recycled
progress ≠ danger
What came of it.30% of progressive passes reached the final third and 21% the box; the rest was recycled in front of the block. 29% 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 wingbalanced
Right half-spacebalanced
Centralbalanced
Left half-spacesterile
Left wingbalanced
Progression — the pass map
The football question
Once Nottingham Forest 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.
1456progression passes attempted
82%completed
19%break into the final third
16%go backward into the defensive third
Pass types
365CB · 30%
67Long Wide · 6%
20Long Central · 2%
577Wide → FB · 48%
170Central · 14%
Sequence success — progression
180progression sequences this season
26%succeed — reach the next third or a shot
42%turned over with nothing to show
CB365 · 30%
Long Wide67 · 6%
Long Central20 · 2%
Wide → FB577 · 48%
Central170 · 14%
◆ Vision AI Insight
Nottingham Forest progress predominantly down the right, with McAtee the busiest midfield outlet (164 progression passes). Only 19% of passes that start in midfield actually break the final-third line — the rest (66%) 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 RHS mid → RW mid (58×) — 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)
16%
Progressive
1%
Neutral / sideways
47%
Safe / backward
35%
18% of passes are progressive-or-better; the remaining 82% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Nottingham Forest actually progress the ball with their feet, not a pass?
171 progressive carries this season across the whole squad (26% of 657 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 45m. Most active carrier: Gibbs-White (22). Filter to one player below.
First (53)Second (48)Third (42)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 Nottingham Forest'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.
137shots
13.2xG
0.10xG per shot
5big chances (0.3+ xG)
6goals
#2key passes / game in the league
#6box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition23% of shots
31
1
3.16
0.10
Cross
1
0
0.11
0.11
Cut-back
2
0
0.20
0.10
Long ball
4
0
0.46
0.11
Pass into the box / short pass
17
0
1.85
0.11
Own creation (carry, dribble, rebound)
7
1
0.54
0.08
Settled attack58% of shots
79
4
7.43
0.09
Cross
15
1
1.42
0.09
Cut-back
10
1
1.06
0.11
Long ball
1
0
0.07
0.07
Pass into the box / short pass
35
1
3.78
0.11
Own creation (carry, dribble, rebound)
18
1
1.10
0.06
Set piece20% of shots
27
1
2.57
0.10
Corner
21
0
1.62
0.08
Free kick
5
0
0.15
0.03
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
Morgan Gibbs-White
22
2.10
2
Dan Ndoye
5
1.67
0
Daniel Muñoz
9
1.22
1
James McAtee
10
0.94
0
Liam Delap
8
0.64
0
Who takes them
Player
Shots
xG
Goals
Liam Delap
21
2.42
1
Morgan Gibbs-White
13
2.02
1
Dan Ndoye
19
1.92
2
Igor Jesus
9
1.80
1
Murillo
14
1.18
0
Vision AI Model Insight
The biggest source of Nottingham Forest's chances, by xG, is settled attack (7.4 of 13.2 xG, 79 of 137 shots), mostly pass into the box / short pass. 31 of the 137 shots (23%) came within 15 seconds of winning the ball. 27 of the 137 shots came from set pieces; 6 goals from 13.2 xG (-7.2).
Chance Creation — the pass map
The football question
How does Nottingham Forest 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
8CB · 9%
2Long Wide · 2%
12Long Central · 13%
23Wide → FB · 25%
46Central · 51%
Sequence success — final-third
114final-third sequences this season
24%succeed — produce a shot
43%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
CB8 · 9%
Long Wide2 · 2%
Long Central12 · 13%
Wide → FB23 · 25%
Central46 · 51%
Who creates — volume × threat
19Gibbs-White
16McAtee
12Williams
8Delap
7Muñoz
5Schlager
5Murillo
91key passes #2 of 20
14.8box entries/game #6 of 20
31.4final-3rd entries/game #9 of 20
1.65xG/game #3 of 20
6goals #18 of 20
-7.2finishing vs xG #20 of 20
◆ Vision AI Insight
Nottingham Forest lean right — 33% of their key passes come from that flank and its half-space (30 of 91), most often from Gibbs-White (8). They funnel chances into the c of the final third, most often via RW att → C att (13 key passes, most often from McAtee). Gibbs-White is the primary source overall. They generate 1.65 xG a game and finish it wasteful — they under-perform their xG, led by Dan Ndoye (2G), Liam Delap (1G), Morgan Gibbs-White (1G).
Crosses & Cutbacks — squad-wide
The question
How does Nottingham Forest deliver into the box from wide areas, and what comes of it?
117 crosses: 40 found a team-mate (34%), 13 led to a shot (11%). 30 cut-backs: 16 found a team-mate (53%), 11 led to a shot (37%). A cross starts wide and is aimed into the box; a cut-back starts near the byline and is squared back. Grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball.
Crosses by Territory
The question
Which part of the final third does Nottingham Forest actually cross from?
117 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. 32% come from one territory, the byline right wing; 5 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · right wing
37
32%
7
advanced · left wing
28
24%
3
byline · left wing
20
17%
1
advanced · right wing
19
16%
1
deep · right wing
7
6%
1
advanced · left half-space
2
2%
0
byline · right half-space
2
2%
0
deep · left wing
1
1%
0
advanced · right half-space
1
1%
0
Finishing3 sections
Shot Map
137 shots for 13.2 xG (1.65/game, #3 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
High-volume attack. 17.1 shots/game at 0.096 xG/shot. Box entries 15/game (#6). Threat created 11.2 xT/game (#10).
Goal Sequences
The move behind each of Nottingham Forest’s 6 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 — 6 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Nottingham Forest scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
5 · 83%
Set pieces
0 · 0%
Penalties
1 · 17%
By finish
Right foot
6 · 100%
Left foot
0 · 0%
Header
0 · 0%
Vision AI Model Insight
6 goals scored. 83% come in open play; set pieces add 0%. Open play is clearly their main route to goal.
When they lose it1 section
Ball-Loss Map — where attacks die
Every turnover has a location and a cause. This is a rate, not a raw count — the share of pass attempts from each zone that end in a turnover, so a zone they simply play through more often doesn't automatically look riskier. Grey cells are real zones with too few attempts to trust a rate.
Loss rate by zone
How they lose it
Incomplete pass — attacking third
239
Failed forward pass
159
Failed take-on
69
Lost in the defensive third
284
Their weakest zone is the right half-space in the attacking third: 37% of 129 pass attempts there are lost (48 times). Separately, 31% 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 Nottingham Forest 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.
38
Pressing Index /100 · passive
Intensity42
PPDA, high-press share, high-zone actions
Height25
how high up the pitch they defend
Effectiveness28
high recoveries & high-regain share
Disruption62
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
17%
RHS
20%
C
21%
LHS
21%
LW
21%
By third (high / mid / low regain)
Def 51%
Mid 34%
Att 15%
Read
Ranked #13 of 20 for press intensity, this is a high press. Note the tension: 51% 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, 47% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#13/20
lower = more intense; rank is what matters
Defensive actions / game
170
#3/20
High-press share
22%
#14/20
def actions won high up
Defensive-action height (0–100)
37.5
#15/20
avg pitch height of actions
High recoveries / game
20.6
#11/20
ball won in mid+att third
High-recovery share
47%
#18/20
share of recoveries won high
Opponent completion allowed
80%
#13/20
lower = more disruptive
Opponent progressive allowed
7.9%
#2/20
of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.
How long they keep it — passes and seconds until the ball is won
The question
Once the opponent has the ball, how many passes and how many seconds pass before Nottingham Forest win it back with a defensive action?
Counted over the 278 opposition possessions that Nottingham Forest 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 Nottingham Forest step in. Nottingham Forest win it after 6.9 opponent passes in the first half-hour and after 4.6 after the hour mark (sooner).
PASSES THEY GET
5.3passes
median 3 · before Nottingham Forest win it
TIME THEY KEEP IT
16sec
median 7s · 34.8 wins per game
How many passes the opponent got in before the ball was won
39%
28%
17%
16%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.1
20s
15–30′
7.7
24s
30–45+′
5.6
17s
45–60′
3.7
9s
60–75′
4.7
13s
75–90+′
4.6
12s
average passesaverage seconds
Attitude in each third
Every other style number here says how much Nottingham Forest 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 Nottingham Forest 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) 1,129 passes
nothing unusual in this zone
Width of use+0.5122.05
Wide-channel share+0.750.35
Side bias+0.000.17
Pass length+0.6425.02
Long-ball share+0.680.30
Forward gain per pass+0.7014.49
Backward-pass share-0.500.18
Deep-pass share+0.620.35
Completion-0.620.74
Seconds between passes-0.333.12
Side used
left 29% · central 42% · right 29%
Progression (middle third) 1,456 passes
trying to break lines, longer passing
Width of use-0.0225.52
Wide-channel share+0.040.41
Side bias+0.060.31
Pass length+1.0118.64
Long-ball share+0.780.13
Forward gain per pass+0.444.27
Backward-pass share-0.000.33
Deep-pass share+1.290.22
Completion-0.530.81
Seconds between passes+0.693.50
Side used
left 35% · central 30% · right 34%
Final third 806 passes
longer passing, more direct
Width of use-0.3930.65
Wide-channel share-0.250.56
Side bias+0.02-0.35
Pass length+1.4117.66
Long-ball share+1.060.15
Forward gain per pass-0.180.80
Backward-pass share+0.310.41
Deep-pass share+0.310.10
Completion-0.150.68
Seconds between passes+0.473.75
Side used
left 39% · central 20% · right 40%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Nottingham Forest'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 Nottingham Forest win or lose the ball, what actually happens in the seconds after?
Reconstructed from the full timestamped event stream: real possession spells (not zone-clustered), and shots that follow a regain within a fixed window. This phase of play needs ordered, per-event timestamps — which every match here carries.
Direct play share16%
#13 of 20 · reaches final third in ≤3 passes
Patient build-up share25%
#11 of 20 · spells of 6+ passes
Tempo (possession length)16.8s
#8 of 20 · shorter = faster tempo
Passes per possession4.2
#12 of 20
Counter-attack shots /game1.26
#2 of 20 · shot within 12s of a regain in own half
Press→shot /game2.83
#13 of 20 · shot within 8s of a high regain
Speed to final third after regain12.3s
#7 of 20 · lower = faster break
Sequence success — attacking transition
10attacking transition sequences this season
40%succeed — produce a shot
60%turned over with nothing to show
Sequence success — defensive transition
30defensive transition sequences this season
67%succeed — reach the next third or a shot
7%turned over with nothing to show
Vision AI Model Insight
Nottingham Forest are balanced between tempo and patience: 16% of possessions reach the final third in 3 passes or fewer (#13 of 20), against 25% built patiently over 6+ passes (#11 of 20). Winning the ball back leads to a shot inside 12 seconds 1.26 times a game (#2), and a high regain converts to a shot within 8 seconds 2.83 times a game (#13 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 Nottingham Forest? 311 opponent progressive passes and 81 shots faced (8.4 xG against) across the season.
Opponent threat by lane (attacking into Nottingham Forest)
Right wing
24%
Right half-space
16%
Central
24%
Left half-space
12%
Left wing
23%
Where the danger came from. Opponents generated most of their threat through the right wing (24% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Nottingham Forest actually come from — open play, dead balls, and who supplies them?
Every goal Nottingham Forest conceded across the loaded matches — the opponent's shots in Nottingham Forest'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 (56 total)
By situation
Open play
7 · 70%
Set pieces
3 · 30%
Penalties
0 · 0%
Vision AI Model Insight
10 goals conceded. 70% come in open play, and 30% from set pieces — a genuine defensive frailty at dead balls to fix on the training ground. 20% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right wing of the attacking third (25% 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
5 g · 10.6 xG
Set pieces
0 g · 1.8 xG
Penalties
1 g
0% of goals come from set pieces (0 of 6), worth 1.8 xG from 26 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Nottingham Forest's corners go?
38 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 (20)
Delivered into the box 100%Short 0%
Left side (18)
Delivered into the box 100%Short 0%
Where opponents attack Nottingham Forest from set pieces
11 shots from opponent corners against Nottingham Forest, 2 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 (6)
Shot 6Goals 0
Left flag (5)
Shot 5Goals 2
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
xG created /game — 1.65 (85th pct)
xG conceded /game — 1.05 (85th pct)
shots /game — 17.12 (85th pct)
progression /game — 48.12 (80th pct)
box entries /game — 14.75 (70th pct)
Weaknesses (bottom-third vs league)
pass retention % — 77.00 (25th pct)
press intensity (PPDA) — 5.36 (35th 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.
Bournemouth
79%
Brentford
54%
Man Utd
48%
Arsenal
26%
Brighton
23%
Performance vs Opponent Styles
The question
Not just how Nottingham Forest 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 Nottingham Forest's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (2m)
1.00
1.50
0.50
vs mid-block opponents (2m)
0.00
0.50
0.50
vs low-block opponents (4m)
1.00
1.50
1.00
Behaviour — how Nottingham Forest actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
66%
29%
38
8.4
9.0
vs mid-block opponents
75%
20%
36
9.4
9.5
vs low-block opponents
81%
14%
59
13.4
20.2
Vision AI Model Insight
Facing a high press, retention drops to 66% vs 81% against a low block (15pt lower under pressure), and directness (long-ball share) sits at 29% when pressed vs 14% 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. Nottingham Forest are balanced-territory with a aggressive high-press.
Their attack creates 1.65 xG a game and they concede 1.05 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 Nottingham Forest’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.
Nottingham Forest
across 8 matches this season
Defensive actionsvs Tottenham · 0-0 · 2026-09-05203avg 170
Threat from passingvs Coventry · 0-1 · 2026-09-199.78avg 6.60
Field tiltvs Arsenal · 0-1 · 2026-10-1823%avg 48%
Passesvs Arsenal · 0-1 · 2026-10-18249avg 424
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 Nottingham Forest’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).
+13.3on-ball value, 8 matches
Where the value came from
Passes3391 actions+5.00
Carries657 actions+0.50
Dribbles124 actions+0.18
Shots137 actions+5.11
Ball wins492 actions+2.46
Most on-ball value (OBV)
Actions
OBV
per 100
Liam Delap
181
+2.00
+1.11
Dan Ndoye
182
+1.98
+1.09
Morgan Gibbs-White
429
+1.95
+0.46
Xaver Schlager
405
+1.44
+0.36
James McAtee
528
+1.16
+0.22
Matz Sels
299
+1.14
+0.38
Murillo
557
+1.04
+0.19
Ola Aina
287
+0.65
+0.23
Biggest single moves
OBV
1 Morgan Gibbs-White · shot
+0.709
2 Dan Ndoye · pass
+0.501
3 Morgan Gibbs-White · pass
+0.479
4 Liam Delap · shot
+0.458
5 Daniel Muñoz · pass
+0.446
6 Dan Ndoye · pass
+0.347
Set Pieces by Player
Who delivers Nottingham Forest’s dead balls and who finishes them this season. 38 corners taken, most by Neco Williams (18); 26 shots from corners and free kicks, 0 goals. “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
Murillo
—
—
9
—
0.75
—
—
Neco Williams
18
18 (100%)
2
—
0.08
1
—
James McAtee
17
17 (100%)
2
—
0.06
2
—
Xaver Schlager
2
2 (100%)
5
—
0.27
—
—
Morgan Gibbs-White
—
—
2
—
0.06
2
1/1
Ousmane Diomande
—
—
2
—
0.20
—
—
Nikola Milenkovic
—
—
1
—
0.07
—
—
Igor Jesus
—
—
1
—
0.07
—
—
Daniel Muñoz
—
—
1
—
0.08
—
—
Dan Ndoye
—
—
1
—
0.14
—
—
Luca Netz
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
Morgan Gibbs-White
M
667
2.56
24
10.4
James McAtee
M
698
2.06
21
9.8
Neco Williams
M
745
1.45
21
11.6
Daniel Muñoz
M
500
1.26
11
6.6
Liam Delap
F
546
1.32
9
1.8
Dan Ndoye
M
527
0.85
8
0.9
Xaver Schlager
M
658
0.68
5
6.1
Ola Aina
M
394
0.91
5
5.0
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)
Callum Hudson-Odoi
W
66
2 (100%)
2 (0%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Murillo
D
753
165
15
12
37
Neco Williams
M
745
134
18
3
40
James McAtee
M
698
133
18
5
50
Xaver Schlager
M
658
123
28
9
40
Jair Cunha
D
561
102
7
4
15
Daniel Muñoz
M
500
89
16
1
15
Ola Aina
M
394
80
12
5
19
Ousmane Diomande
D
361
79
5
3
22
Full Squad Data
Every player with 100+ minutes (16 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Matz Sels
G
8
760
0
0.0
1
51
27
10.2
Murillo
D
8
753
0
1.2
5
37
165
10.3
Neco Williams
M
8
745
1
0.9
12
61
134
11.6
James McAtee
M
8
698
0
0.6
16
38
133
9.8
Morgan Gibbs-White
M
7
667
1
2.0
19
38
66
10.4
Xaver Schlager
M
8
658
0
0.6
5
25
123
6.1
Jair Cunha
D
6
561
0
0.2
2
29
102
5.9
Liam Delap
F
7
546
1
2.4
8
7
71
1.8
Dan Ndoye
M
8
527
2
1.9
5
3
67
0.9
Daniel Muñoz
M
6
500
0
0.7
7
36
89
6.6
Ola Aina
M
5
394
0
0.1
4
24
80
5.0
Nikola Milenkovic
D
4
381
0
0.2
1
6
78
2.5
Ousmane Diomande
D
5
361
0
0.3
0
7
79
2.7
Igor Jesus
F
5
281
1
1.8
2
7
64
1.9
Ibrahim Sangaré
M
5
171
0
0.0
2
4
24
1.6
Chris Wood
F
7
121
0
0.4
0
1
22
0.2
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.
Matz Sels
Goalkeeper · Goalkeeper
minutes760
goals · xG0 · 0.0
prog passes /906.0
key passes /900.12
def actions /903.2
pass accuracy59%
Murillo
Stopper / marker · Defender
minutes753
goals · xG0 · 1.2
prog passes /904.4
key passes /900.60
def actions /9019.7
pass accuracy85%
Neco Williams
Deep-lying playmaker · Midfielder
minutes745
goals · xG1 · 0.9
prog passes /907.4
key passes /901.45
def actions /9016.2
pass accuracy75%
James McAtee
Advanced creator · Attacking mid
minutes698
goals · xG0 · 0.6
prog passes /904.9
key passes /902.06
def actions /9017.1
pass accuracy75%
Morgan Gibbs-White
Advanced creator · Attacking mid
minutes667
goals · xG1 · 2.0
prog passes /905.1
key passes /902.56
def actions /908.9
pass accuracy77%
Xaver Schlager
Ball-winner / destroyer · Midfielder
minutes658
goals · xG0 · 0.6
prog passes /903.4
key passes /900.68
def actions /9016.8
pass accuracy82%
Jair Cunha
Ball-playing defender · Defender
minutes561
goals · xG0 · 0.2
prog passes /904.7
key passes /900.32
def actions /9016.4
pass accuracy82%
Liam Delap
Ball-winner / destroyer · Midfielder
minutes546
goals · xG1 · 2.4
prog passes /901.2
key passes /901.32
def actions /9011.7
pass accuracy62%
Dan Ndoye
Ball-winner / destroyer · Midfielder
minutes527
goals · xG2 · 1.9
prog passes /900.5
key passes /900.85
def actions /9011.4
pass accuracy70%
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: pass retention % (25th pct)
Sign a secure ball-retaining midfielder. The data flags this because possession is turned over cheaply (77.00, 25th percentile vs the league).
Need — bottom-third: press intensity (PPDA) (35th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (5.36, 35th percentile vs the league).
Need — below-average: field tilt % (45th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (48.09, 45th percentile vs the league).