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Team reportSerie A 2026

Lazio

A possession-dominant side, aggressive high-press out of possession, with a moderate attack. Currently #2 of 20 on 25 points (8-1-0, 22:7). Tactical profile below is built from 9 matches of ball-by-ball event data, contextualised against the league.

possession-dominantaggressive high-pressmoderate attack
W
D
W
L
L
W
W
W
W
D
W
W
W
W
W
25
points
#2 of 20 · 9 games
22:7
goals
+15 GD
8-1-0
record
W-D-L
2.78
points/game
#2 in the league
1.46
xG for/game
rank #7
1.22
xG against/game
rank #5
#9
press rank
of 20 · most aggressive
56%
field tilt
#5
Lazio
League average
Expected goals for / game
1.461.42
Expected goals against / game
1.221.43
Field tilt
56%50%
Pass retention
85%83%
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 Lazio and how good was the season?
Read. Lazio currently sit #2 of 20 on 25 points (8W-1D-0L, 2.78 pts/game), scoring 22 and conceding 7 for a goal difference of +15. On the ball they are a possession-dominant team (56% field tilt, #5 in the league); off it they defend with a aggressive high-press (#9 of 20 for press intensity). Across the 9 matches of event data, they create 1.46 xG/game (#7) and concede 1.22 (#5), a net of +0.24 xG/game — the underlying performance diverges from the actual goal difference.

Season Context — the league table

The question
Where did Lazio actually finish, and against whom?

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

#teamPWDLGFGAGDPts
1Inter98102510+1525
2Lazio9810227+1525
3Roma9630238+1521
4Como9621178+920
5AC Milan95311811+718

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Lazio 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+'+1.73-0.41
Vision AI Model Insight
Lazio tend to come alive after the break — first-half net xG +0.47, second-half +1.71. Their strongest period is 61-75' (net +1.73 xG); their most dangerous period to face is 16-30' (net -0.41 xG against them).

xG Race — the season, match by match

Expected goals piling up over 9 matches: Lazio 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 (+2.2 xG). Hover a point for that match.

0591413.211.0Bologna (A) 1-0 · xG 0.59 to 2.38Genoa (H) 1-0 · xG 1.18 to 0.79Udinese (A) 2-1 · xG 1.82 to 0.94AC Milan (H) 2-2 · xG 1.62 to 1.47Venezia (A) 2-0 · xG 1.71 to 1.84Monza (H) 3-1 · xG 1.32 to 1.32Juventus (A) 3-0 · xG 0.51 to 0.89Parma Calcio 1913 (H) 2-1 · xG 1.52 to 0.73Sassuolo (A) 6-2 · xG 2.90 to 0.62M1M2M3M4M5M6M7M8M9
LazioOpponents against Lazio

Tactical DNA

The football question
In five genes, what is Lazio'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.

70
Build-Up
possession control from the back
70
Progression
moving the ball upfield with threat
57
Creation
manufacturing chances
65
Press
winning the ball high & hard
75
Solidity
resisting the opponent's threat
Genetic identity
Lazio are defined most by their Solidity DNA (75/100 · strong at resisting the opponent's threat), and least by their Creation DNA (57/100). 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).

Possess62Disrupt48Finish57Press22Defend23
Possess
Deep buildup
70%
Possession
57%
Field tilt
61%
Disrupt
Central progression ~proxy
83%
Dribble tendency
13%
Progressive passes
48%
Finish
Final-third patience
78%
Shot quality
43%
Open-play xG
48%
Press
Forward press ~proxy
4%
High regains
26%
Pressing efficiency ~proxy
35%
Defend
Def-mid press ~proxy
43%
High line ~proxy
26%
PAdj defensive actions
0%
Lazio is defined most by Possess (62% in the league) and weakest on Press (22%). 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 Lazio actually control, relative to the rest of the league?

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

Lazio: 56% tilt, 2.78 pts/gInter: 69% tilt, 2.78 pts/gRoma: 64% tilt, 2.33 pts/gComo: 62% tilt, 2.22 pts/gAC Milan: 52% tilt, 2.00 pts/gFrosinone: 50% tilt, 1.75 pts/gNapoli: 52% tilt, 1.56 pts/gJuventus: 65% tilt, 1.56 pts/gTorino: 40% tilt, 1.44 pts/gCagliari: 33% tilt, 1.44 pts/gAtalanta: 47% tilt, 1.25 pts/gBologna: 45% tilt, 1.22 pts/gLecce: 44% tilt, 1.12 pts/gGenoa: 38% tilt, 1.11 pts/gSassuolo: 47% tilt, 0.89 pts/gMonza: 47% tilt, 0.78 pts/gParma Calcio 1913: 34% tilt, 0.56 pts/gUdinese: 54% tilt, 0.56 pts/gFiorentina: 50% tilt, 0.50 pts/gVenezia: 51% tilt, 0.33 pts/gLazio33%45%57%69%0.31.12.02.8FIELD TILT %POINTS / GAME
Vision AI Model Insight
Lazio post 56% field tilt, ranking #5 of 20 in the league — comfortably above the league mid-point for territorial control, and their 2.78 points/game sits above the league-average return — territory is genuinely converting into results.

Where the time goes — how long each phase lasts

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

The share of Lazio'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: 20.3% of the time on the ball20%Progression: 52.4% of the time on the ball52%Chance creation: 24.6% of the time on the ball25%Attacking transition: 2.7% of the time on the ball52%PROGRESSION
PhaseShare of the time
Build-up20.3%
Progression52.4%
Chance creation24.6%
Attacking transition2.7%
Vision AI Model Insight
Progression is where Lazio spends most of its time on the ball (52% 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.

Mattia Zaccagni ↔ Nuno Tavares: 156 passes, 5.0 combined xTNuno Tavares ↔ Kenneth Taylor: 126 passes, 1.9 combined xTNuno Tavares ↔ Oliver Provstgaard: 121 passes, 0.3 combined xTChristos Mandas ↔ Oliver Provstgaard: 100 passes, -0.3 combined xTJosip Sutalo ↔ Reda Belahyane: 96 passes, -0.3 combined xTNuno Tavares ↔ Reda Belahyane: 89 passes, 0.3 combined xTMattia Zaccagni ↔ Kenneth Taylor: 83 passes, 2.0 combined xTKenneth Taylor ↔ Reda Belahyane: 83 passes, 0.6 combined xTReda Belahyane ↔ Oliver Provstgaard: 72 passes, 0.2 combined xTJosip Sutalo ↔ Romano Floriani Mussolini: 69 passes, -0.5 combined xTGustav Isaksen ↔ Romano Floriani Mussolini: 68 passes, 1.6 combined xTMattia Zaccagni ↔ Oliver Provstgaard: 66 passes, 0.9 combined xTJosip Sutalo ↔ Christos Mandas: 65 passes, -0.6 combined xTRomano Floriani Mussolini ↔ Reda Belahyane: 63 passes, 0.3 combined xTKenneth Taylor ↔ Oliver Provstgaard: 57 passes, -0.3 combined xTMattia Zaccagni ↔ Reda Belahyane: 53 passes, 0.8 combined xTNuno Tavares ↔ Christos Mandas: 44 passes, 0.8 combined xTNuno Tavares ↔ Tijjani Noslin: 43 passes, 1.0 combined xTMatteo Cancellieri ↔ Romano Floriani Mussolini: 42 passes, 0.4 combined xTJosip Sutalo ↔ Oliver Provstgaard: 37 passes, -0.4 combined xTKenneth Taylor ↔ Tijjani Noslin: 36 passes, 0.7 combined xTGustav Isaksen ↔ Reda Belahyane: 36 passes, 0.4 combined xTChristos Mandas ↔ Romano Floriani Mussolini: 33 passes, -0.0 combined xTDavide Frattesi ↔ Josip Sutalo: 32 passes, -0.1 combined xTMattia Zaccagni — isolate this player's connectionsZaccagniDavide Frattesi — isolate this player's connectionsFrattesiNuno Tavares — isolate this player's connectionsTavaresDaniel Maldini — isolate this player's connectionsMaldiniKenneth Taylor — isolate this player's connectionsTaylorGustav Isaksen — isolate this player's connectionsIsaksenChristos Mandas — isolate this player's connectionsMandasRomano Floriani Mussolini — isolate this player's connectionsMussoliniReda Belahyane — isolate this player's connectionsBelahyaneOliver Provstgaard — isolate this player's connectionsProvstgaarMario Gila — isolate this player's connectionsGilaTijjani Noslin — isolate this player's connectionsNoslinMatteo Cancellieri — isolate this player's connectionsCancellierJosip Sutalo — isolate this player's connectionsSutaloToma Basic — isolate this player's connectionsBasicAndrea Pinamonti — isolate this player's connectionsPinamonti
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Zaccagni ↔ Tavares
156p · 5.0xT
Tavares ↔ Taylor
126p · 1.9xT
Tavares ↔ Provstgaard
121p · 0.3xT
Mandas ↔ Provstgaard
100p · -0.3xT
Sutalo ↔ Belahyane
96p · -0.3xT
Tavares ↔ Belahyane
89p · 0.3xT
Zaccagni ↔ Taylor
83p · 2.0xT
Taylor ↔ Belahyane
83p · 0.6xT
Belahyane ↔ Provstgaard
72p · 0.2xT
Sutalo ↔ Mussolini
69p · -0.5xT
Vision AI Model Insight
Busiest connection: Mattia Zaccagni ↔ Nuno Tavares (156 passes). Most dangerous per pass: Mattia Zaccagni ↔ Nuno Tavares (0.03 xT/pass over 156 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Lazio had the ball

Every touch across 88 matches. Brighter means more touches.

Which Zones Do They Attack Through?

The question
Across the whole pitch, where does Lazio 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
4739
ACTIONS
3%4%9%4%4%8%9%11%12%12%4%3%3%5%9%PASSES
Carries
the ball moved with a player
1047
ACTIONS
2%5%11%4%3%8%9%12%12%13%4%3%2%4%8%CARRIES
Vision AI Model Insight
Their single busiest zone is the left wing of the middle third (12.4% of all actions). 61% of actions run through the inside lanes (centre + both half-spaces) versus 39% down the two wings — an inside-dominant, half-space build. By third: 24% defensive, 52% 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. Lazio leaned on their left (50%). The bars under the pitch put the league’s share beside theirs.

50%Left side21%Middle29%Right sideATTACKING →
Lazio
50%21%29%
League
38%24%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. Lazio made 420 this season (46.7 a match); 40% 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: 168 entries (40%)16840%LEFT WINGLeft half-space: 63 entries (15%)6315%LEFT HALF-SPACECentre: 50 entries (12%)5012%CENTRERight half-space: 50 entries (12%)5012%RIGHT HALF-SPACERight wing: 89 entries (21%)8921%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing16818.740%29%
Left half-space637.015%15%
Centre505.612%13%
Right half-space505.612%15%
Right wing899.921%28%
Build-up2 sections

Build-Up — the pass map

The football question
How does Lazio 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.

1110build-up passes attempted
82%completed
30%reach the middle third
2%go long into the final third

Pass types

323CB · 35%
75Long Wide · 8%
7Long Central · 1%
402Wide → FB · 44%
106Central · 12%

Sequence success — build-up

90build-up sequences this season
10%succeed — reach the next third or a shot
47%turned over with nothing to show
CB323 · 35%
left: 174 passes, most from Provstgaard174right: 149 passes, most from Sutalo149
Long Wide75 · 8%
left: 39 passes, most from Mandas39right: 36 passes, most from Mandas36
Long Central7 · 1%
right: 6 passes, most from Mandas6
Wide → FB402 · 44%
left: 218 passes, most from Mandas218right: 184 passes, most from Mandas184
Central106 · 12%
left: 55 passes, most from Mandas55right: 51 passes, most from Mandas51
◆ Vision AI Insight
Lazio build predominantly down the left, with Mandas as the fulcrum (256 build-up passes). Only 32% 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 (51×).

Pass Explorer

Every pass of Lazio’s last 9 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. 428 progressive passes across 9 matches (47.6/game).

Origin lane

Right wing
18%
Right half-space
10%
Central
11%
Left half-space
17%
Left wing
45%
Progression is left-dominant: 27% right side · 11% central · 62% left.

Who generates it

Nuno Tavares
89 · 21%
Mattia Zaccagni
71 · 17%
Oliver Provstgaard
36 · 8%
Kenneth Taylor
34 · 8%
Christos Mandas
31 · 7%
Top two — Nuno Tavares & Mattia Zaccagni — account for 37% of all progression.
PROGRESSION
47.6 prog passes/game
mostly left
→
PENETRATION
25% reach final third
20% reach the box
→
THREAT
the other 75% is recycled
progress ≠ danger
What came of it. 25% of progressive passes reached the final third and 20% the box; the rest was recycled in front of the block. 37% 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 Lazio 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.

2443progression passes attempted
90%completed
15%break into the final third
9%go backward into the defensive third

Pass types

658CB · 30%
75Long Wide · 3%
13Long Central · 1%
1172Wide → FB · 53%
282Central · 13%

Sequence success — progression

158progression sequences this season
27%succeed — reach the next third or a shot
35%turned over with nothing to show
CB658 · 30%
left: 399 passes, most from Provstgaard399right: 259 passes, most from Sutalo259
Long Wide75 · 3%
right: 38 passes, most from Belahyane38left: 37 passes, most from Tavares37
Long Central13 · 1%
right: 9 passes, most from Mussolini9left: 4 passes, most from Belahyane4
Wide → FB1172 · 53%
left: 691 passes, most from Tavares691right: 481 passes, most from Mussolini481
Central282 · 13%
left: 144 passes, most from Belahyane144right: 138 passes, most from Taylor138
◆ Vision AI Insight
Lazio progress predominantly down the left, with Belahyane the busiest midfield outlet (266 progression passes). Only 15% of passes that start in midfield actually break the final-third line — the rest (76%) is recycled back into midfield or (9%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LHS mid → LW mid (142×) — 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
2%
Neutral / sideways
48%
Safe / backward
37%
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 Lazio actually progress the ball with their feet, not a pass?

245 progressive carries this season across the whole squad (24% of 1041 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 65m. Most active carrier: Tavares (41). Filter to one player below.

First (79)Second (78)Third (46)Fourth (42)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 Lazio'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.

127shots
13.2xG
0.10xG per shot
8big chances (0.3+ xG)
21goals
#10key passes / game in the league
#8box entries / game in the league
Attacking transition: 21 shots (17%)17%21Settled attack: 85 shots (67%)67%85Set piece: 21 shots (17%)17%21127SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 17% of shots2151.880.09
Cross300.310.10
Cut-back420.580.14
Long ball110.060.06
Pass into the box / short pass1000.720.07
Own creation (carry, dribble, rebound)320.210.07
Settled attack 67% of shots85147.880.09
Cross1021.170.12
Cut-back600.560.09
Long ball100.040.04
Pass into the box / short pass48104.060.08
Own creation (carry, dribble, rebound)2022.060.10
Set piece 17% of shots2123.410.16
Corner1210.900.08
Free kick600.130.02
Penalty312.380.79

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
Mattia Zaccagni181.804
Nuno Tavares101.023
Kenneth Taylor80.671
Davide Frattesi40.530
Matteo Cancellieri60.520

Who takes them

PlayerShotsxGGoals
Mattia Zaccagni263.252
Davide Frattesi142.563
Tijjani Noslin121.924
Gustav Isaksen161.133
Matteo Cancellieri90.851
Vision AI Model Insight
The biggest source of Lazio's chances, by xG, is settled attack (7.9 of 13.2 xG, 85 of 127 shots), mostly pass into the box / short pass. 21 of the 127 shots (17%) came within 15 seconds of winning the ball. 21 of the 127 shots came from set pieces; 21 goals from 13.2 xG (+7.8).

Chance Creation — the pass map

The football question
How does Lazio 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

3CB · 3%
2Long Wide · 2%
6Long Central · 6%
39Wide → FB · 41%
45Central · 47%

Sequence success — final-third

98final-third sequences this season
31%succeed — produce a shot
38%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
CB3 · 3%
left: 2 passes, most from Provstgaard2
Long Wide2 · 2%
Long Central6 · 6%
left: 3 passes, most from Tavares3right: 3 passes, most from Tavares3
Wide → FB39 · 41%
right: 20 passes, most from Zaccagni20left: 19 passes, most from Taylor19
Central45 · 47%
right: 23 passes, most from Zaccagni23left: 22 passes, most from Zaccagni22

Who creates — volume × threat

22Zaccagni
14Tavares
9Taylor
6Cancellieri
6Belahyane
5Mussolini
4Noslin
95key passes #10 of 20
14.2box entries/game #8 of 20
38.3final-3rd entries/game #6 of 20
1.46xG/game #7 of 20
21goals #3 of 20
+7.8finishing vs xG #1 of 20
◆ Vision AI Insight
Lazio lean left — 45% of their key passes come from that flank and its half-space (43 of 95), most often from Zaccagni (16). They funnel chances into the c of the final third, most often via LHS att → C att (19 key passes, most often from Zaccagni). Zaccagni is the primary source overall. They generate 1.46 xG a game and finish it clinical — they beat their xG, led by Tijjani Noslin (4G), Gustav Isaksen (3G), Davide Frattesi (3G).

Crosses & Cutbacks — squad-wide

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

110 crosses: 44 found a team-mate (40%), 15 led to a shot (14%). 33 cut-backs: 17 found a team-mate (52%), 10 led to a shot (30%). 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 Lazio actually cross from?

110 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. 30% come from one territory, the advanced left wing; 7 come from the half-spaces and 0 from the centre.

deep right wing: 3 crosses (3%)3%3deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 1 crosses (1%)1%1deep left wing: 7 crosses (6%)6%7advanced right wing: 15 crosses (14%)14%15advanced right half-space: 0 crosses (0%)advanced centre: 0 crosses (0%)advanced left half-space: 2 crosses (2%)2%2advanced left wing: 33 crosses (30%)30%33byline right wing: 15 crosses (14%)14%15byline right half-space: 0 crosses (0%)byline centre: 0 crosses (0%)byline left half-space: 4 crosses (4%)4%4byline left wing: 30 crosses (27%)27%30
TerritoryCrossesShareLed to a shot
advanced · left wing3330%3
byline · left wing3027%6
advanced · right wing1514%3
byline · right wing1514%1
deep · left wing76%0
byline · left half-space44%2
deep · right wing33%0
advanced · left half-space22%0
deep · left half-space11%0
Finishing3 sections

Shot Map

127 shots for 13.2 xG (1.46/game, #7 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

Moderate attack. 14.1 shots/game at 0.104 xG/shot. Box entries 14/game (#8). Threat created 11.9 xT/game (#6).

Goal Sequences

The move behind each of Lazio’s 22 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 — 22 goals traced.

How Do They Score?

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

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

By situation

Open play
19 · 90%
Set pieces
1 · 5%
Penalties
1 · 5%

By finish

Right foot
8 · 38%
Left foot
8 · 38%
Header
5 · 24%
Vision AI Model Insight
21 goals scored. 90% come in open play; set pieces add 5%. 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

36 of 140 pass attempts lost here (26%).26%36/140Mussolini27 of 177 pass attempts lost here (15%).15%27/177Mandas74 of 446 pass attempts lost here (17%).17%74/446Mandas19 of 172 pass attempts lost here (11%).11%19/172Provstgaar41 of 175 pass attempts lost here (23%).23%41/175Tavares47 of 363 pass attempts lost here (13%).13%47/363Mussolini32 of 429 pass attempts lost here (7%).7%32/429Belahyane34 of 500 pass attempts lost here (7%).7%34/500Frattesi62 of 568 pass attempts lost here (11%).11%62/568Noslin68 of 583 pass attempts lost here (12%).12%68/583Tavares50 of 186 pass attempts lost here (27%).27%50/186Mussolini41 of 161 pass attempts lost here (25%).25%41/161Isaksen29 of 154 pass attempts lost here (19%).19%29/154Frattesi73 of 253 pass attempts lost here (29%).29%73/253Zaccagni91 of 432 pass attempts lost here (21%).21%91/432Tavaresattacking →

How they lose it

Incomplete pass — attacking third
284
Failed forward pass
194
Failed take-on
77
Lost in the defensive third
197
Their weakest zone is the left half-space in the attacking third: 29% of 253 pass attempts there are lost (73 times). Separately, 39% 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 Lazio 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.

64
Pressing Index
/100 · strong
Intensity65
PPDA, high-press share, high-zone actions
Height70
how high up the pitch they defend
Effectiveness68
high recoveries & high-regain share
Disruption52
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
14%
RHS
20%
C
27%
LHS
20%
LW
19%
By third (high / mid / low regain)
Def 43%
Mid 44%
Att 14%
Read
Ranked #9 of 20 for press intensity, this is a high press. 57% of defensive actions happen in the middle & attacking thirds, at an average height of 40. Of recoveries, 58% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#9/20lower = more intense; rank is what matters
Defensive actions / game141#16/20
High-press share23%#6/20def actions won high up
Defensive-action height (0–100)39.9#6/20avg pitch height of actions
High recoveries / game23.2#7/20ball won in mid+att third
High-recovery share58%#6/20share of recoveries won high
Opponent completion allowed83%#10/20lower = more disruptive
Opponent progressive allowed8.5%#9/20of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.

How long they keep it — passes and seconds until the ball is won

The question
Once the opponent has the ball, how many passes and how many seconds pass before Lazio win it back with a defensive action?

Counted over the 284 opposition possessions that Lazio 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 Lazio step in. Lazio win it after 5.7 opponent passes in the first half-hour and after 4.7 after the hour mark (sooner).

PASSES THEY GET
5.4passes
median 4 · before Lazio win it
TIME THEY KEEP IT
16sec
median 8s · 31.6 wins per game
How many passes the opponent got in before the ball was won
38%
26%
20%
16%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.0
19s
15–30′
5.4
16s
30–45+′
4.7
13s
45–60′
8.2
24s
60–75′
4.4
12s
75–90+′
4.9
14s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Lazio 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 Lazio 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) 1,110 passes

nothing unusual in this zone

Width of use-0.3320.31
Wide-channel share-0.180.29
Side bias+0.220.99
Pass length-0.2821.68
Long-ball share-0.360.19
Forward gain per pass-0.2310.46
Backward-pass share-0.010.20
Deep-pass share-0.380.25
Completion+0.320.82
Seconds between passes-0.363.11
Side used

left 28% · central 48% · right 24%

Progression (middle third) 2,443 passes

left-sided

Width of use+0.0925.77
Wide-channel share+0.110.41
Side bias+1.194.75
Pass length-0.7116.24
Long-ball share-0.750.07
Forward gain per pass-0.562.76
Backward-pass share+0.020.34
Deep-pass share-0.670.13
Completion+0.760.89
Seconds between passes-0.443.00
Side used

left 43% · central 28% · right 29%

Final third 1,186 passes

left-sided, kept on the floor, shorter passing

Width of use-0.3930.66
Wide-channel share-0.400.55
Side bias+1.379.23
Pass length-0.8614.13
Long-ball share-0.980.05
Forward gain per pass-0.090.93
Backward-pass share-0.160.38
Deep-pass share+0.010.09
Completion+0.600.75
Seconds between passes-0.233.22
Side used

left 54% · central 16% · right 30%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Lazio'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 Lazio 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 share14%
#20 of 20 · reaches final third in ≤3 passes
Patient build-up share36%
#5 of 20 · spells of 6+ passes
Tempo (possession length)21.4s
#16 of 20 · shorter = faster tempo
Passes per possession5.7
#5 of 20
Counter-attack shots /game0.91
#16 of 20 · shot within 12s of a regain in own half
Press→shot /game2.51
#17 of 20 · shot within 8s of a high regain
Speed to final third after regain14.8s
#20 of 20 · lower = faster break

Sequence success — attacking transition

20attacking transition sequences this season
5%succeed — produce a shot
55%turned over with nothing to show

Sequence success — defensive transition

26defensive transition sequences this season
54%succeed — reach the next third or a shot
12%turned over with nothing to show
Vision AI Model Insight
Lazio are a patient build-up side: 14% of possessions reach the final third in 3 passes or fewer (#20 of 20), against 36% built patiently over 6+ passes (#5 of 20). Winning the ball back leads to a shot inside 12 seconds 0.91 times a game (#16), and a high regain converts to a shot within 8 seconds 2.51 times a game (#17 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 Lazio? 375 opponent progressive passes and 107 shots faced (11.0 xG against) across the season.

Opponent threat by lane (attacking into Lazio)

Right wing
29%
Right half-space
17%
Central
19%
Left half-space
11%
Left wing
24%
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 Lazio actually come from — open play, dead balls, and who supplies them?

Every goal Lazio conceded across the loaded matches — the opponent's shots in Lazio'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 (78 total)

3%5%10%3%1%17%17%14%13%18%Juan MirandaRiccardo OrsoliniRiccardo OrsoliniJuan MirandaLewis FergusonOussama El AzzouziTorbjørn HeggemFederico BernardeschiLewis FergusonMikael EllertssonBrooke Norton-CuffyMorten FrendrupMilutin OsmajicBrooke Norton-CuffyMorten FrendrupBrooke Norton-CuffyJunior MessiasJurgen EkkelenkampKike PérezJohn YeboahJakub PiotrowskiMërgim VojvodaJames AbankwahUnai GómezKeinan DavisKeinan DavisLennon MillerRuben Loftus-CheekSamuel ChukwuezeMario GilaLuka ModricMario GilaChristian PulisicSamuel ChukwuezeAlphadjo CisseChristian PulisicAdrien RabiotAdrien RabiotChristian PulisicChristian PulisicJohn YeboahEddy KouadioCyril NgongeAndrea CarboniSamuele BirindelliRicardo MangasDany MotaRicardo MangasSamuele BirindelliEbenezer AkinsanmiroAdam BakouneDavid RomeroEmanuele ValeriAdrián BernabéEmanuele ValeriGiovanni FabbianSimon SohmSimon SohmKike PérezKike PérezKike PérezThierry CorreiaJohn YeboahDouglas LuizWeston McKennieRandal Kolo MuaniRandal Kolo MuaniNick WoltemadeAndrea CambiasoPierre KaluluEdon ZhegrovaEmanuele ValeriEmanuele ValeriChristian OrdóñezJosh DoigKristian ThorstvedtSimone CinquegranoSebastiano Esposito← own goal

By situation

Open play
5 · 83%
Set pieces
1 · 17%
Penalties
0 · 0%
Vision AI Model Insight
6 goals conceded. 83% come in open play; set pieces account for only 17%, so dead-ball defending is not the main issue. 17% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the left wing of the attacking third (18% 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
19 g · 9.8 xG
Set pieces
1 g · 1.0 xG
Penalties
1 g
5% of goals come from set pieces (1 of 21), worth 1.0 xG from 18 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Lazio's corners go?

45 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 (21)

10%5%14%5%10%29%29%
Delivered into the box 100%Short 0%

Left side (24)

17%12%38%21%4%
Delivered into the box 92%Short 8%

Where opponents attack Lazio from set pieces

25 shots from opponent corners against Lazio, 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 (13)

15%8%23%15%23%15%
Shot 13Goals 0

Left flag (12)

8%8%8%25%25%25%
Shot 12Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • xG conceded /game — 1.22 (75th pct)
  • field tilt % — 56.00 (75th pct)
  • progression /game — 47.56 (70th pct)
  • threat created /game — 11.88 (70th pct)
  • xG created /game — 1.46 (65th pct)
Weaknesses (bottom-third vs league)
  • none stand out

Style Archetype & Similar Teams

Team archetype: High-press possession side. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.

Como
86%
Juventus
85%
AC Milan
79%
Inter
75%
Napoli
61%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (3m)1.670.003.00
vs mid-block opponents (3m)2.001.332.33
vs low-block opponents (3m)3.671.003.00

Behaviour — how Lazio actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents81%12%4410.212.0
vs mid-block opponents83%10%4711.915.0
vs low-block opponents87%7%5213.515.7
Vision AI Model Insight
Facing a high press, retention drops to 81% vs 87% against a low block (6pt lower under pressure), and directness (long-ball share) sits at 12% when pressed vs 7% 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. Lazio are possession-dominant with a aggressive high-press. Their attack creates 1.46 xG a game and they concede 1.22 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 Lazio’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.

Lazio
across 9 matches this season
Expected goalsat Sassuolo · 6-2 · 2026-10-272.90avg 1.46
Defensive actionsat Sassuolo · 6-2 · 2026-10-27109avg 141
PPDAvs AC Milan · 2-2 · 2026-09-129.0avg 5.7
Pass accuracyat Sassuolo · 6-2 · 2026-10-2791%avg 84%
Progressive passesvs Parma Calcio 1913 · 2-1 · 2026-10-2472avg 48
Field tiltvs AC Milan · 2-2 · 2026-09-1236%avg 56%
Final-third entriesat Bologna · 1-0 · 2026-08-2424avg 47
Progressive carriesvs AC Milan · 2-2 · 2026-09-1223avg 46

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 Lazio’s last 9 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).

+16.9on-ball value, 9 matches
Where the value came from
Passes4739 actions+6.97
Carries1041 actions+0.24
Dribbles137 actions+0.52
Shots127 actions+6.55
Ball wins501 actions+2.65
Most on-ball value (OBV)ActionsOBVper 100
Mattia Zaccagni635+3.47+0.55
Nuno Tavares730+2.34+0.32
Reda Belahyane606+1.58+0.26
Davide Frattesi314+1.54+0.49
Kenneth Taylor563+1.43+0.25
Gustav Isaksen292+0.87+0.30
Tijjani Noslin185+0.86+0.46
Danilho Doekhi216+0.85+0.39
123456
Biggest single movesOBV
1  Davide Frattesi · shot+0.760
2  Mattia Zaccagni · shot+0.738
3  Mattia Zaccagni · shot+0.723
4  Nuno Tavares · pass+0.525
5  Mattia Zaccagni · pass+0.483
6  Mattia Zaccagni · pass+0.445

Set Pieces by Player

Who delivers Lazio’s dead balls and who finishes them this season. 45 corners taken, most by Mattia Zaccagni (21); 18 shots from corners and free kicks, 1 goals, led by Oliver Provstgaard (1 goals, 0.14 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
Mattia Zaccagni2114 (67%)4—0.0941/2
Nuno Tavares1513 (87%)2—0.061—
Danilho Doekhi——3—0.48——
Gustav Isaksen11 (100%)2—0.05——
Oliver Provstgaard——210.14——
Alfonso Pedraza54 (80%)——0.00——
Matteo Cancellieri21 (50%)1—0.03——
Tijjani Noslin10 (0%)1—0.08——
Romano Floriani Mussolini——1—0.04——
Nicolò Rovella——1—0.021—
Diogo Leite——1—0.03——
Davide Frattesi————0.00—0/1

Top Performers

Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 243 minutes). Coloured chips are that player's strongest capability blocks.

playerposminVision AI Scorecapability blocks
Josip SutaloCB4936.5Ball-Carrying 70%Ball-Winning 61%Aerial & Box Defending 48%Progression 34%
Nuno TavaresFB6806.0Ball-Carrying 80%Ball-Winning 52%Wide Delivery 44%
Mattia ZaccagniW8095.7Box Threat 60%Chance Creation 37%Wide Delivery 26%Ball-Carrying 25%
Kenneth TaylorCM7135.5Progression 60%Chance Creation 35%Ball-Carrying 30%Successful Dribble 26%
Reda BelahyaneCM7184.3Progression 60%Ball-Carrying 40%Successful Dribble 38%Chance Creation 35%
Oliver ProvstgaardCB6714.0Ball-Carrying 94%Progression 73%Ball-Winning 30%Aerial & Box Defending 15%
Christos MandasGK8503.9Shot-Stopping 39%
Gustav IsaksenW4903.4Box Threat 82%Ball-Carrying 46%Chance Creation 15%Wide Delivery 14%
Tijjani NoslinST5033.1Ball-Carrying 82%Finishing 38%Box Threat 30%Aerial Threat 0%
Romano Floriani MussoliniFB7583.1Wide Delivery 39%Ball-Winning 32%Ball-Carrying 21%

Top Creators

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

playerposminkey P /90box entriesxT
Mattia ZaccagniF8092.453213.3
Nuno TavaresD6801.852017.9
Kenneth TaylorM7131.14209.7
Davide FrattesiM7460.48103.5
Gustav IsaksenF4900.55104.3
Matteo CancellieriF3291.6472.5
Reda BelahyaneM7180.7558.5
Romano Floriani MussoliniD7580.5956.8

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)
Nuno TavaresFB68019 (21%)8 (25%)
Mattia ZaccagniW80916 (69%)9 (33%)
Romano Floriani MussoliniFB7586 (67%)6 (17%)
Matteo CancellieriW3296 (33%)1 (100%)
Gustav IsaksenW49006 (50%)
Alfonso PedrazaFB2051 (100%)1 (100%)
Andrea PinamontiW19001 (100%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Nuno TavaresD68011916338
Romano Floriani MussoliniD75811420825
Josip SutaloD49311041525
Reda BelahyaneM7189916449
Oliver ProvstgaardD6719871021
Kenneth TaylorM7139713736
Mattia ZaccagniF809969927
Davide FrattesiM7469616526

Full Squad Data

Every player with 100+ minutes (20 players).

playerposappsmingoalsxGkey PprogdefxT
Christos MandasG985000.00312710.7
Mattia ZaccagniF980923.322719613.3
Romano Floriani MussoliniD975810.45261146.8
Davide FrattesiM974632.6413963.5
Reda BelahyaneM871800.1626998.5
Kenneth TaylorM971320.6934979.7
Nuno TavaresD968010.6148911917.9
Oliver ProvstgaardD867110.3136989.5
Tijjani NoslinF850341.946531.3
Josip SutaloD649300.0081104.4
Gustav IsaksenF949031.1324694.3
Danilho DoekhiD433900.525581.8
Matteo CancellieriF632910.9610432.5
Alfonso PedrazaD820500.1313233.0
Diogo LeiteD419700.0016524.5
Andrea PinamontiF719010.533250.3
Fisayo Dele-BashiruM518810.234191.3
Boulaye DiaF215700.044110.9
Nicolò RovellaM213200.026261.6
Manuel LazzariD611100.023160.9

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.

Christos Mandas
Goalkeeper · Goalkeeper
minutes850
goals · xG0 · 0.0
prog passes /903.3
key passes /900.00
def actions /902.9
pass accuracy76%
Mattia Zaccagni
Creative forward · Forward
minutes809
goals · xG2 · 3.3
prog passes /907.9
key passes /902.45
def actions /9010.7
pass accuracy78%
Romano Floriani Mussolini
Stopper / marker · Defender
minutes758
goals · xG1 · 0.4
prog passes /903.1
key passes /900.59
def actions /9013.5
pass accuracy83%
Davide Frattesi
Ball-winner / destroyer · Midfielder
minutes746
goals · xG3 · 2.6
prog passes /901.6
key passes /900.48
def actions /9011.6
pass accuracy81%
Reda Belahyane
Ball-winner / destroyer · Midfielder
minutes718
goals · xG0 · 0.1
prog passes /903.3
key passes /900.75
def actions /9012.4
pass accuracy93%
Kenneth Taylor
Ball-winner / destroyer · Midfielder
minutes713
goals · xG2 · 0.6
prog passes /904.3
key passes /901.14
def actions /9012.2
pass accuracy86%
Nuno Tavares
Ball-playing defender · Defender
minutes680
goals · xG1 · 0.6
prog passes /9011.8
key passes /901.85
def actions /9015.8
pass accuracy80%
Oliver Provstgaard
Ball-playing defender · Defender
minutes671
goals · xG1 · 0.3
prog passes /904.8
key passes /900.13
def actions /9013.1
pass accuracy91%
Tijjani Noslin
Ball-winner / destroyer · Midfielder
minutes503
goals · xG4 · 1.9
prog passes /901.1
key passes /900.72
def actions /909.5
pass accuracy78%

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 — below-average: shots /game (45th pct)
Sign a shot-taking forward to raise shot volume. The data flags this because shot volume is low (14.11, 45th percentile vs the league).
Vision AI · building report