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Team reportSerie A 2026

Sassuolo

A balanced-territory side, aggressive high-press out of possession, with a moderate attack. Currently #14 of 20 on 8 points (2-2-5, 14:22). Tactical profile below is built from 9 matches of ball-by-ball event data, contextualised against the league.

balanced-territoryaggressive high-pressmoderate attack
W
D
W
L
L
L
L
W
D
W
L
D
L
L
L
8
points
#14 of 20 · 9 games
14:22
goals
-8 GD
2-2-5
record
W-D-L
0.89
points/game
#14 in the league
1.22
xG for/game
rank #15
1.62
xG against/game
rank #15
#20
press rank
of 20 · most aggressive
47%
field tilt
#13
Sassuolo
League average
Expected goals for / game
1.221.43
Expected goals against / game
1.621.43
Field tilt
47%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 Sassuolo and how good was the season?
Read. Sassuolo currently sit #14 of 20 on 8 points (2W-2D-5L, 0.89 pts/game), scoring 14 and conceding 22 for a goal difference of -8. On the ball they are a balanced-territory team (47% field tilt, #13 in the league); off it they defend with a aggressive high-press (#20 of 20 for press intensity). Across the 9 matches of event data, they create 1.22 xG/game (#15) and concede 1.62 (#15), a net of -0.39 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

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

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

#teamPWDLGFGAGDPts
11Atalanta83141415-110
12Lecce8305914-59
13Bologna8224810-28
14Sassuolo92251422-88
15Monza82151518-37
16Genoa8215613-77
17Udinese8116918-94

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Sassuolo 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+'+0.78-2.22
Vision AI Model Insight
Sassuolo tend to fade after a strong start — first-half net xG +0.71, second-half -4.25. Their strongest period is 16-30' (net +0.78 xG); their most dangerous period to face is 46-60' (net -2.22 xG against them).

xG Race — the season, match by match

Expected goals piling up over 9 matches: Sassuolo 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 (-3.5 xG). Hover a point for that match.

05101611.014.5Atalanta (A) 1-2 · xG 2.25 to 0.81Torino (H) 2-1 · xG 1.69 to 0.99Bologna (A) 2-2 · xG 1.25 to 1.99Juventus (H) 3-2 · xG 0.82 to 1.13Monza (A) 1-2 · xG 1.56 to 1.69AC Milan (H) 1-1 · xG 0.93 to 1.24Frosinone (A) 2-4 · xG 1.50 to 2.13Como (A) 0-2 · xG 0.39 to 1.67Lazio (H) 2-6 · xG 0.62 to 2.90M1M2M3M4M5M6M7M8M9
SassuoloOpponents against Sassuolo

Tactical DNA

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

58
Build-Up
possession control from the back
40
Progression
moving the ball upfield with threat
43
Creation
manufacturing chances
18
Press
winning the ball high & hard
25
Solidity
resisting the opponent's threat
Genetic identity
Sassuolo are defined most by their Build-Up DNA (58/100 · average at possession control from the back), and least by their Press DNA (18/100). 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).

Possess30Disrupt42Finish52Press12Defend4
Possess
Deep buildup
30%
Possession
35%
Field tilt
26%
Disrupt
Central progression ~proxy
30%
Dribble tendency
61%
Progressive passes
35%
Finish
Final-third patience
57%
Shot quality
61%
Open-play xG
39%
Press
Forward press ~proxy
9%
High regains
22%
Pressing efficiency ~proxy
4%
Defend
Def-mid press ~proxy
4%
High line ~proxy
4%
PAdj defensive actions
4%
Sassuolo is defined most by Finish (52% in the league) and weakest on Defend (4%). 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 Sassuolo actually control, relative to the rest of the league?

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

Lazio: 56% tilt, 2.78 pts/gInter: 69% tilt, 2.75 pts/gRoma: 64% tilt, 2.33 pts/gAC Milan: 52% tilt, 2.25 pts/gComo: 62% tilt, 2.22 pts/gJuventus: 65% tilt, 1.75 pts/gFrosinone: 50% tilt, 1.75 pts/gTorino: 40% tilt, 1.44 pts/gCagliari: 33% tilt, 1.44 pts/gNapoli: 51% tilt, 1.38 pts/gAtalanta: 47% tilt, 1.25 pts/gLecce: 44% tilt, 1.12 pts/gBologna: 45% tilt, 1.00 pts/gSassuolo: 47% tilt, 0.89 pts/gGenoa: 39% tilt, 0.88 pts/gMonza: 48% tilt, 0.88 pts/gParma Calcio 1913: 34% tilt, 0.50 pts/gFiorentina: 50% tilt, 0.50 pts/gUdinese: 53% tilt, 0.50 pts/gVenezia: 54% tilt, 0.38 pts/gSassuolo33%45%57%69%0.41.22.02.8FIELD TILT %POINTS / GAME
Vision AI Model Insight
Sassuolo post 47% field tilt, ranking #13 of 20 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 0.89 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 Sassuolo has the ball, how much of that time is spent building, progressing and creating?

The share of Sassuolo'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: 29.6% of the time on the ball30%Progression: 44.1% of the time on the ball44%Chance creation: 24.5% of the time on the ball24%Attacking transition: 1.9% of the time on the ball44%PROGRESSION
PhaseShare of the time
Build-up29.6%
Progression44.1%
Chance creation24.5%
Attacking transition1.9%
Vision AI Model Insight
Progression is where Sassuolo spends most of its time on the ball (44% 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.

Armand Laurienté ↔ Josh Doig: 89 passes, 2.5 combined xTArmand Laurienté ↔ Darryl Bakola: 83 passes, 1.4 combined xTNemanja Matic ↔ Darryl Bakola: 78 passes, 0.2 combined xTJosh Doig ↔ Darryl Bakola: 71 passes, 0.3 combined xTArijanet Muric ↔ Fedde Leysen: 54 passes, -0.4 combined xTJosh Doig ↔ Fedde Leysen: 53 passes, -0.5 combined xTArmand Laurienté ↔ Kristian Thorstvedt: 46 passes, 1.1 combined xTDomenico Berardi ↔ Simone Cinquegrano: 43 passes, 0.5 combined xTNemanja Matic ↔ Domenico Berardi: 42 passes, 0.5 combined xTNemanja Matic ↔ Josh Doig: 42 passes, -0.1 combined xTFedde Leysen ↔ Darryl Bakola: 40 passes, 0.1 combined xTNemanja Matic ↔ Simone Cinquegrano: 38 passes, -0.3 combined xTNemanja Matic ↔ Armand Laurienté: 37 passes, 0.5 combined xTNemanja Matic ↔ Fedde Leysen: 35 passes, -0.3 combined xTNemanja Matic ↔ Vasilije Adzic: 34 passes, 0.4 combined xTKristian Thorstvedt ↔ Darryl Bakola: 33 passes, 0.3 combined xTNemanja Matic ↔ Kristian Thorstvedt: 32 passes, 0.3 combined xTArmand Laurienté ↔ Sebastiano Esposito: 32 passes, 0.6 combined xTDomenico Berardi ↔ Sebastiano Esposito: 28 passes, 0.5 combined xTDomenico Berardi ↔ Kristian Thorstvedt: 27 passes, 0.5 combined xTSebastiano Esposito ↔ Kristian Thorstvedt: 27 passes, 0.6 combined xTNemanja Matic ↔ Arijanet Muric: 25 passes, 0.1 combined xTDomenico Berardi ↔ Darryl Bakola: 24 passes, 0.5 combined xTArmand Laurienté ↔ Kieron Bowie: 24 passes, 1.3 combined xTArmand Laurienté — isolate this player's connectionsLaurientéJosh Doig — isolate this player's connectionsDoigKieron Bowie — isolate this player's connectionsBowieDarryl Bakola — isolate this player's connectionsBakolaNemanja Matic — isolate this player's connectionsMaticDomenico Berardi — isolate this player's connectionsBerardiKristian Thorstvedt — isolate this player's connectionsThorstvedtAlieu Fadera — isolate this player's connectionsFaderaArijanet Muric — isolate this player's connectionsMuricSimone Cinquegrano — isolate this player's connectionsCinquegranLuca Lipani — isolate this player's connectionsLipaniVasilije Adzic — isolate this player's connectionsAdzicFedde Leysen — isolate this player's connectionsLeysenBenja Domínguez — isolate this player's connectionsDomínguezSebastiano Esposito — isolate this player's connectionsEspositoAndrea Pinamonti — isolate this player's connectionsPinamonti
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Laurienté ↔ Doig
89p · 2.5xT
Laurienté ↔ Bakola
83p · 1.4xT
Matic ↔ Bakola
78p · 0.2xT
Doig ↔ Bakola
71p · 0.3xT
Muric ↔ Leysen
54p · -0.4xT
Doig ↔ Leysen
53p · -0.5xT
Laurienté ↔ Thorstvedt
46p · 1.1xT
Berardi ↔ Cinquegrano
43p · 0.5xT
Matic ↔ Berardi
42p · 0.5xT
Matic ↔ Doig
42p · -0.1xT
Vision AI Model Insight
Busiest connection: Armand Laurienté ↔ Josh Doig (89 passes). Most dangerous per pass: Armand Laurienté ↔ Kieron Bowie (0.05 xT/pass over 24 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Sassuolo had the ball

Every touch across 83 matches. Brighter means more touches.

Which Zones Do They Attack Through?

The question
Across the whole pitch, where does Sassuolo 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
4405
ACTIONS
4%5%12%7%4%8%7%10%10%11%5%3%2%4%7%PASSES
Carries
the ball moved with a player
974
ACTIONS
2%7%11%5%4%7%7%9%10%14%6%4%2%3%8%CARRIES
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (12.2% 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, 46% middle, 22% 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. Sassuolo leaned on their left (46%). The bars under the pitch put the league’s share beside theirs.

46%Left side20%Middle34%Right sideATTACKING →
Sassuolo
46%20%34%
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. Sassuolo made 365 this season (40.6 a match); 37% 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: 136 entries (37%)13637%LEFT WINGLeft half-space: 54 entries (15%)5415%LEFT HALF-SPACECentre: 44 entries (12%)4412%CENTRERight half-space: 38 entries (10%)3810%RIGHT HALF-SPACERight wing: 93 entries (25%)9325%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing13615.137%29%
Left half-space546.015%15%
Centre444.912%13%
Right half-space384.210%16%
Right wing9310.325%28%
Build-up2 sections

Build-Up — the pass map

The football question
How does Sassuolo 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.

1435build-up passes attempted
86%completed
28%reach the middle third
2%go long into the final third

Pass types

450CB · 37%
72Long Wide · 6%
19Long Central · 2%
525Wide → FB · 43%
162Central · 13%

Sequence success — build-up

62build-up sequences this season
21%succeed — reach the next third or a shot
34%turned over with nothing to show
CB450 · 37%
left: 233 passes, most from Caleta-Car233right: 217 passes, most from Caleta-Car217
Long Wide72 · 6%
left: 40 passes, most from Muric40right: 32 passes, most from Muric32
Long Central19 · 2%
left: 14 passes, most from Muric14right: 5 passes, most from Muric5
Wide → FB525 · 43%
left: 300 passes, most from Doig300right: 225 passes, most from Muric225
Central162 · 13%
left: 88 passes, most from Muric88right: 74 passes, most from Muric74
◆ Vision AI Insight
Sassuolo build predominantly down the left, with Muric as the fulcrum (203 build-up passes). Only 29% of their build-up passes actually advance a third — the rest is lateral circulation, the hallmark of a possession-controlling side that circulates patiently in midfield before progressing. Their single most-repeated pattern is C def → LHS def (85×).

Pass Explorer

Every pass of Sassuolo’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. 383 progressive passes across 9 matches (42.6/game).

Origin lane

Right wing
24%
Right half-space
13%
Central
15%
Left half-space
13%
Left wing
35%
Progression is left-dominant: 37% right side · 15% central · 48% left.

Who generates it

Armand Laurienté
64 · 17%
Josh Doig
37 · 10%
Nemanja Matic
35 · 9%
Arijanet Muric
31 · 8%
Domenico Berardi
27 · 7%
Top two — Armand Laurienté & Josh Doig — account for 26% of all progression.
PROGRESSION
42.6 prog passes/game
mostly left
→
PENETRATION
25% reach final third
22% reach the box
→
THREAT
the other 75% is recycled
progress ≠ danger
What came of it. 25% of progressive passes reached the final third and 22% the box; the rest was recycled in front of the block. 26% 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-spacesterile
Left wingefficient

Progression — the pass map

The football question
Once Sassuolo 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.

2011progression passes attempted
89%completed
15%break into the final third
13%go backward into the defensive third

Pass types

380CB · 21%
59Long Wide · 3%
22Long Central · 1%
1071Wide → FB · 60%
260Central · 15%

Sequence success — progression

99progression sequences this season
34%succeed — reach the next third or a shot
33%turned over with nothing to show
CB380 · 21%
left: 214 passes, most from Caleta-Car214right: 166 passes, most from Caleta-Car166
Long Wide59 · 3%
left: 33 passes, most from Doig33right: 26 passes, most from Cinquegrano26
Long Central22 · 1%
right: 13 passes, most from Matic13left: 9 passes, most from Berardi9
Wide → FB1071 · 60%
left: 646 passes, most from Doig646right: 425 passes, most from Cinquegrano425
Central260 · 15%
left: 135 passes, most from Bakola135right: 125 passes, most from Bakola125
◆ Vision AI Insight
Sassuolo progress predominantly down the left, with Matic the busiest midfield outlet (222 progression passes). Only 15% of passes that start in midfield actually break the final-third line — the rest (72%) is recycled back into midfield or (13%) 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 (120×) — 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)
13%
Progressive
1%
Neutral / sideways
47%
Safe / backward
39%
14% of passes are progressive-or-better; the remaining 86% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.

Carries Map — progressive ball-carries, squad-wide

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

240 progressive carries this season across the whole squad (25% of 969 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 45m. Most active carrier: Laurienté (43). Filter to one player below.

First (72)Second (71)Third (55)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 Sassuolo'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.

126shots
11.0xG
0.09xG per shot
4big chances (0.3+ xG)
13goals
#10key passes / game in the league
#7box entries / game in the league
Attacking transition: 30 shots (24%)24%30Settled attack: 74 shots (59%)59%74Set piece: 22 shots (17%)17%22126SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 24% of shots3023.430.11
Cut-back100.280.28
Long ball320.540.18
Pass into the box / short pass2002.130.11
Own creation (carry, dribble, rebound)600.490.08
Settled attack 59% of shots7496.200.08
Cross1001.210.12
Cut-back821.000.13
Long ball500.290.06
Pass into the box / short pass3642.330.06
Own creation (carry, dribble, rebound)1531.360.09
Set piece 17% of shots2221.370.06
Corner1811.270.07
Free kick410.100.03

Every attempt to create — and what came of it

Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.

Who sets the shots up

PlayerSet-upsxG createdGoals
Armand Laurienté91.751
Kieron Bowie100.821
Sebastiano Esposito80.790
Darryl Bakola70.702
Vasilije Adzic100.641

Who takes them

PlayerShotsxGGoals
Armand Laurienté281.790
Kieron Bowie131.571
Kristian Thorstvedt121.501
Domenico Berardi131.392
Vasilije Adzic121.293
Vision AI Model Insight
The biggest source of Sassuolo's chances, by xG, is settled attack (6.2 of 11.0 xG, 74 of 126 shots), mostly pass into the box / short pass. 30 of the 126 shots (24%) came within 15 seconds of winning the ball. 22 of the 126 shots came from set pieces; 13 goals from 11.0 xG (+2.0).

Chance Creation — the pass map

The football question
How does Sassuolo 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

2CB · 2%
9Long Wide · 9%
9Long Central · 9%
31Wide → FB · 33%
44Central · 46%

Sequence success — final-third

96final-third sequences this season
26%succeed — produce a shot
40%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
CB2 · 2%
Long Wide9 · 9%
right: 5 passes, most from Matic5left: 4 passes, most from Berardi4
Long Central9 · 9%
left: 7 passes, most from Laurienté7right: 2 passes, most from Berardi2
Wide → FB31 · 33%
left: 18 passes, most from Bowie18right: 13 passes, most from Adzic13
Central44 · 46%
left: 24 passes, most from Adzic24right: 20 passes, most from Bowie20

Who creates — volume × threat

12Adzic
10Laurienté
10Berardi
9Volpato
9Bowie
8Matic
8Esposito
95key passes #10 of 20
14.6box entries/game #7 of 20
31.2final-3rd entries/game #11 of 20
1.22xG/game #15 of 20
13goals #8 of 20
+2.0finishing vs xG #7 of 20
◆ Vision AI Insight
Sassuolo lean left — 40% of their key passes come from that flank and its half-space (38 of 95), most often from Doig (6). They funnel chances into the c of the final third, most often via RHS att → C att (10 key passes, most often from Adzic). Adzic is the primary source overall. They generate 1.22 xG a game and finish it clinical — they beat their xG, led by Vasilije Adzic (3G), Domenico Berardi (2G), Sebastiano Esposito (2G).

Crosses & Cutbacks — squad-wide

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

121 crosses: 44 found a team-mate (36%), 10 led to a shot (8%). 30 cut-backs: 16 found a team-mate (53%), 10 led to a shot (33%). 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 Sassuolo actually cross from?

121 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. 33% come from one territory, the byline left wing; 3 come from the half-spaces and 0 from the centre.

deep right wing: 3 crosses (2%)2%3deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 2 crosses (2%)2%2advanced right wing: 16 crosses (13%)13%16advanced right half-space: 1 crosses (1%)1%1advanced centre: 0 crosses (0%)advanced left half-space: 2 crosses (2%)2%2advanced left wing: 31 crosses (26%)26%31byline right wing: 26 crosses (21%)21%26byline right half-space: 0 crosses (0%)byline centre: 0 crosses (0%)byline left half-space: 0 crosses (0%)byline left wing: 40 crosses (33%)33%40
TerritoryCrossesShareLed to a shot
byline · left wing4033%6
advanced · left wing3126%2
byline · right wing2621%2
advanced · right wing1613%0
deep · right wing32%0
deep · left wing22%0
advanced · left half-space22%0
advanced · right half-space11%0
Finishing3 sections

Shot Map

126 shots for 11.0 xG (1.22/game, #15 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

Moderate attack. 14.0 shots/game at 0.087 xG/shot. Box entries 15/game (#7). Threat created 10.6 xT/game (#11).

Goal Sequences

The move behind each of Sassuolo’s 12 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 — 12 goals traced.

How Do They Score?

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

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

By situation

Open play
11 · 85%
Set pieces
2 · 15%
Penalties
0 · 0%

By finish

Right foot
5 · 38%
Left foot
7 · 54%
Header
1 · 8%
Vision AI Model Insight
13 goals scored. 85% come in open play; set pieces add 15%. 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

43 of 177 pass attempts lost here (24%).24%43/177Brempt35 of 220 pass attempts lost here (16%).16%35/220Muric74 of 550 pass attempts lost here (13%).13%74/550Muric26 of 291 pass attempts lost here (9%).9%26/291Leysen29 of 197 pass attempts lost here (15%).15%29/197Doig51 of 332 pass attempts lost here (15%).15%51/332Cinquegran32 of 314 pass attempts lost here (10%).10%32/314Berardi39 of 450 pass attempts lost here (9%).9%39/450Matic41 of 423 pass attempts lost here (10%).10%41/423Bakola56 of 492 pass attempts lost here (11%).11%56/492Doig60 of 230 pass attempts lost here (26%).26%60/230Cinquegran28 of 135 pass attempts lost here (21%).21%28/135Berardi19 of 101 pass attempts lost here (19%).19%19/101Matic41 of 171 pass attempts lost here (24%).24%41/171Laurienté76 of 322 pass attempts lost here (24%).24%76/322Laurientéattacking →

How they lose it

Incomplete pass — attacking third
224
Failed forward pass
152
Failed take-on
96
Lost in the defensive third
207
Their weakest zone is the right wing in the attacking third: 26% of 230 pass attempts there are lost (60 times). Separately, 34% 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 Sassuolo 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.

20
Pressing Index
/100 · passive
Intensity3
PPDA, high-press share, high-zone actions
Height10
how high up the pitch they defend
Effectiveness32
high recoveries & high-regain share
Disruption38
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
16%
RHS
19%
C
26%
LHS
21%
LW
17%
By third (high / mid / low regain)
Def 52%
Mid 36%
Att 12%
Read
Ranked #20 of 20 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 (18% high-press share) means that when they do defend, it is often deep. Of recoveries, 51% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#20/20lower = more intense; rank is what matters
Defensive actions / game130#20/20
High-press share18%#18/20def actions won high up
Defensive-action height (0–100)35.9#18/20avg pitch height of actions
High recoveries / game19.7#13/20ball won in mid+att third
High-recovery share51%#14/20share of recoveries won high
Opponent completion allowed87%#20/20lower = more disruptive
Opponent progressive allowed8.3%#5/20of 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 Sassuolo win it back with a defensive action?

Counted over the 282 opposition possessions that Sassuolo 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 Sassuolo step in. Sassuolo win it after 8.9 opponent passes in the first half-hour and after 6.3 after the hour mark (sooner).

PASSES THEY GET
7.1passes
median 4 · before Sassuolo win it
TIME THEY KEEP IT
21sec
median 11s · 31.3 wins per game
How many passes the opponent got in before the ball was won
35%
23%
13%
28%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
8.9
25s
15–30′
8.8
26s
30–45+′
6.8
19s
45–60′
5.7
16s
60–75′
6.6
21s
75–90+′
6.0
17s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Sassuolo 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 Sassuolo 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) 1,435 passes

nothing unusual in this zone

Width of use-0.4120.14
Wide-channel share-0.550.27
Side bias+0.552.21
Pass length-0.7719.94
Long-ball share-0.640.17
Forward gain per pass-0.618.80
Backward-pass share+0.550.22
Deep-pass share-0.400.25
Completion+0.690.85
Seconds between passes-0.722.89
Side used

left 30% · central 46% · right 24%

Progression (middle third) 2,011 passes

left-sided, shorter passing, circulating

Width of use+0.3226.25
Wide-channel share+0.400.43
Side bias+1.124.48
Pass length-1.0615.74
Long-ball share-0.800.07
Forward gain per pass-0.962.15
Backward-pass share+0.660.36
Deep-pass share-0.630.13
Completion+0.740.89
Seconds between passes-0.193.11
Side used

left 42% · central 29% · right 29%

Final third 959 passes

nothing unusual in this zone

Width of use+0.1131.88
Wide-channel share+0.080.59
Side bias+0.835.40
Pass length-0.2315.11
Long-ball share-0.120.09
Forward gain per pass-0.280.66
Backward-pass share+0.270.40
Deep-pass share-0.270.08
Completion+0.750.76
Seconds between passes+0.063.44
Side used

left 50% · central 15% · right 35%

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

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

Direct play share17%
#9 of 20 · reaches final third in ≤3 passes
Patient build-up share27%
#12 of 20 · spells of 6+ passes
Tempo (possession length)18.6s
#10 of 20 · shorter = faster tempo
Passes per possession4.6
#12 of 20
Counter-attack shots /game0.98
#15 of 20 · shot within 12s of a regain in own half
Press→shot /game2.40
#18 of 20 · shot within 8s of a high regain
Speed to final third after regain13.8s
#15 of 20 · lower = faster break

Sequence success — attacking transition

11attacking transition sequences this season
36%succeed — produce a shot
36%turned over with nothing to show

Sequence success — defensive transition

26defensive transition sequences this season
65%succeed — reach the next third or a shot
8%turned over with nothing to show
Vision AI Model Insight
Sassuolo are a direct, fast-break side: 17% of possessions reach the final third in 3 passes or fewer (#9 of 20), against 27% built patiently over 6+ passes (#12 of 20). Winning the ball back leads to a shot inside 12 seconds 0.98 times a game (#15), and a high regain converts to a shot within 8 seconds 2.40 times a game (#18 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 Sassuolo? 421 opponent progressive passes and 141 shots faced (14.5 xG against) across the season.

Opponent threat by lane (attacking into Sassuolo)

Right wing
30%
Right half-space
14%
Central
16%
Left half-space
13%
Left wing
27%
Where the danger came from. Opponents generated most of their threat through the right wing (30% of the danger conceded).

How Do They Concede?

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

Every goal Sassuolo conceded across the loaded matches — the opponent's shots in Sassuolo'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 (98 total)

1%3%5%5%4%2%14%18%13%23%10%Gianluca GaetanoGianluca ScamaccaNicola ZalewskiNicola ZalewskiCharles De KetelaereLazar SamardzicNikola KrstovicLazar SamardzicNikola VlasicChé AdamsKian Fitz-JimAlessio CacciamaniNiccolò FortiniSaúl CocoPietro ComuzzoKerim AlajbegovicEdon ZhegrovaEdon ZhegrovaRandal Kolo MuaniNicolò CambiaghiRoberto PiccoliFederico BernardeschiNicolò CambiaghiTommaso PobegaFederico BernardeschiJuan MirandaMarco LibraFederico BernardeschiJuan MirandaArtem DovbykLewis FergusonFrancisco ConceiçãoNico GonzálezDouglas LuizFrancisco ConceiçãoZeki ÇelikRandal Kolo MuaniZeki ÇelikBremerEdon ZhegrovaGiacomo CalòGiacomo CalòGiacomo CalòIlario MonterisiFarès GhedjemisGiacomo CalòGabriele BracagliaGiacomo CalòRomano SchmidGiorgi KvernadzePatrizio MasiniGiorgi KvernadzePatrizio MasiniRomano SchmidRomano SchmidRicardo MangasJay RobinsonEbenezer AkinsanmiroGustavo VarelaGustavo VarelaAdam BakouneJay RobinsonSamuele BirindelliSamuele BirindelliDiego MoreiraMario GilaSamuel ChukwuezePervis EstupiñánDiego MoreiraAdrien RabiotLuka ModricChristian PulisicPatrick CutroneLorenzo LucchesiDany MotaGustavo VarelaMaxence CaqueretYan CoutoMaxence CaqueretMartin BaturinaMaxence CaqueretYan CoutoKaikiMaxence CaqueretKaikiLucas da CunhaMattia ZaccagniKenneth TaylorMattia ZaccagniGustav IsaksenReda BelahyaneFisayo Dele-BashiruNuno TavaresMattia ZaccagniFisayo Dele-BashiruMatteo CancellieriMattia ZaccagniAndrea Pinamonti← own goal

By situation

Open play
18 · 82%
Set pieces
3 · 14%
Penalties
1 · 5%
Vision AI Model Insight
22 goals conceded. 82% come in open play; set pieces account for only 14%, so dead-ball defending is not the main issue. 18% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the left half-space of the attacking third (23% 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
11 g · 9.6 xG
Set pieces
2 g · 1.4 xG
Penalties
0 g
15% of goals come from set pieces (2 of 13), worth 1.4 xG from 22 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Sassuolo's corners go?

36 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 (15)

7%33%7%20%13%7%
Delivered into the box 87%Short 13%

Left side (21)

10%19%5%14%5%10%29%5%
Delivered into the box 95%Short 5%

Where opponents attack Sassuolo from set pieces

21 shots from opponent corners against Sassuolo, 3 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 (10)

30%40%20%10%
Shot 10Goals 2

Left flag (11)

9%18%18%27%9%18%
Shot 11Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • pass retention % — 85.24 (80th pct)
  • box entries /game — 14.56 (65th pct)
Weaknesses (bottom-third vs league)
  • press intensity (PPDA) — 8.61 (0th pct)
  • xG created /game — 1.22 (25th pct)
  • xG conceded /game — 1.62 (25th pct)
  • field tilt % — 46.64 (35th pct)
  • progression /game — 42.56 (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.

Atalanta
90%
Cagliari
66%
Udinese
43%
Bologna
42%
Torino
17%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (3m)1.332.670.33
vs mid-block opponents (3m)2.003.001.33
vs low-block opponents (3m)1.331.671.00

Behaviour — how Sassuolo actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents83%12%4810.414.3
vs mid-block opponents85%10%328.610.3
vs low-block opponents87%10%4812.719.0
Vision AI Model Insight
Facing a high press, retention drops to 83% vs 87% against a low block (4pt lower under pressure), and directness (long-ball share) sits at 12% when pressed vs 10% against a low block — their passing style barely changes regardless of how the opponent sets up, for better or worse.

Scouting Summary — the team in brief

In brief. Sassuolo are balanced-territory with a aggressive high-press. Their attack creates 1.22 xG a game and they concede 1.62 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 Sassuolo’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.

Sassuolo
across 9 matches this season
Progressive carriesat Atalanta · 1-2 · 2026-08-2363avg 41
Passesat Monza · 1-2 · 2026-09-18635avg 489
Pass accuracyat Frosinone · 2-4 · 2026-10-1680%avg 85%
Final-third entriesvs Torino · 2-1 · 2026-08-2959avg 41
Expected goalsat Atalanta · 1-2 · 2026-08-232.25avg 1.22
Progressive passesvs Lazio · 2-6 · 2026-10-2725avg 43
Defensive actionsvs AC Milan · 1-1 · 2026-10-11154avg 130
Threat from passingat Monza · 1-2 · 2026-09-188.54avg 5.30

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 Sassuolo’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).

+14.4on-ball value, 9 matches
Where the value came from
Passes4405 actions+3.67
Carries969 actions+1.52
Dribbles156 actions+0.56
Shots126 actions+5.59
Ball wins500 actions+3.02
Most on-ball value (OBV)ActionsOBVper 100
Armand Laurienté535+2.28+0.43
Domenico Berardi332+1.81+0.54
Darryl Bakola576+1.58+0.27
Kristian Thorstvedt286+1.42+0.50
Cas Odenthal259+1.32+0.51
Nemanja Matic596+0.92+0.16
Arijanet Muric324+0.89+0.28
Josh Doig453+0.86+0.19
123456
Biggest single movesOBV
1  Kieron Bowie · carry+0.584
2  Cas Odenthal · shot+0.362
3  Armand Laurienté · shot+0.324
4  Duje Caleta-Car · shot+0.280
5  Kristian Thorstvedt · take-on+0.273
6  Josh Doig · ball win+0.269

Set Pieces by Player

Who delivers Sassuolo’s dead balls and who finishes them this season. 36 corners taken, most by Armand Laurienté (14); 22 shots from corners and free kicks, 2 goals, led by Cas Odenthal (1 goals, 0.26 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
Armand Laurienté1411 (79%)4—0.112—
Domenico Berardi76 (86%)2—0.041—
Vasilije Adzic63 (50%)110.041—
Duje Caleta-Car——3—0.25——
Kieron Bowie——2—0.38——
Josh Doig——2—0.04——
Cas Odenthal——210.26——
Cristian Volpato55 (100%)——0.00——
Jay Idzes——1—0.06——
Kristian Thorstvedt——1—0.03——
Fedde Leysen——1—0.04——
Nemanja Matic——1—0.03——
Simone Cinquegrano——1—0.08——
Ignace Van der Brempt——1—0.01——

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
Arijanet MuricGK6608.3Shot-Stopping 83%
Nemanja MaticCM6046.3Successful Dribble 75%Ball-Carrying 73%Progression 59%Chance Creation 45%
Domenico BerardiW5454.5Box Threat 67%Chance Creation 30%Wide Delivery 16%Ball-Carrying 10%
Armand LaurientéW7504.3Chance Creation 53%Box Threat 53%Ball-Carrying 45%Wide Delivery 34%
Duje Ćaleta-CarCB4723.9Ball-Carrying 60%Ball-Winning 46%Progression 43%Aerial & Box Defending 34%
Darryl BakolaCM6363.4Successful Dribble 78%Ball-Carrying 67%Progression 60%Chance Creation 42%
Josh DoigFB7082.3Ball-Winning 42%Ball-Carrying 28%Wide Delivery 12%
Kieron BowieST5051.6Finishing 40%Ball-Carrying 26%Box Threat 25%Aerial Threat 0%
Simone CinquegranoFB5800.9Ball-Winning 33%Wide Delivery 6%Ball-Carrying 0%

Top Creators

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

playerposminkey P /90box entriesxT
Armand LaurientéF7501.203512.5
Domenico BerardiM5451.65165.6
Nemanja MaticM6041.19119.8
Vasilije AdzicM3732.9062.6
Darryl BakolaM6361.13107.2
Josh DoigD7080.76118.3
Sebastiano EspositoF3362.1463.7
Kieron BowieF5051.6041.1

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)
Armand LaurientéW75016 (44%)10 (70%)
Josh DoigFB7087 (57%)7 (43%)
Simone CinquegranoFB5804 (25%)6 (33%)
Domenico BerardiW5457 (14%)1 (100%)
Cristian VolpatoW2163 (33%)2 (50%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Darryl BakolaM63610221242
Nemanja MaticM60491121042
Josh DoigD70883131014
Simone CinquegranoD580797618
Duje Ćaleta-CarD472776719
Fedde LeysenD424769415
Domenico BerardiM5457411731
Armand LaurientéF750624023

Full Squad Data

Every player with 100+ minutes (22 players).

playerposappsmingoalsxGkey PprogdefxT
Armand LaurientéF975001.810646212.5
Josh DoigD970810.3637838.3
Arijanet MuricG766000.0131218.3
Darryl BakolaM863600.48251027.2
Nemanja MaticM860400.1835919.8
Simone CinquegranoD758000.4322794.9
Domenico BerardiM854521.41027745.6
Kieron BowieF950511.695471.1
Duje Ćaleta-CarD647200.3011774.1
Fedde LeysenD642400.119763.5
Kristian ThorstvedtM841911.5610543.6
Vasilije AdzicM737331.31215472.6
Cas OdenthalD434920.716503.2
Sebastiano EspositoF633620.4820443.7
Luca LipaniM831800.107562.2
Jay IdzesD326900.104361.5
Ignace Van der BremptD326600.0112382.4
Cristian VolpatoF521610.4916233.9
Benja DomínguezM619400.223270.7
Stefano TuratiG218600.00511.4
Rafa ObradorD413800.0012222.3
Fali CandéD212400.003161.4

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.

Armand Laurienté
Deep-lying playmaker · Midfielder
minutes750
goals · xG0 · 1.8
prog passes /907.7
key passes /901.20
def actions /907.4
pass accuracy83%
Josh Doig
Ball-playing defender · Defender
minutes708
goals · xG1 · 0.3
prog passes /904.7
key passes /900.76
def actions /9010.6
pass accuracy85%
Arijanet Muric
Goalkeeper · Goalkeeper
minutes660
goals · xG0 · 0.0
prog passes /904.2
key passes /900.14
def actions /902.9
pass accuracy83%
Darryl Bakola
Ball-winner / destroyer · Midfielder
minutes636
goals · xG0 · 0.4
prog passes /903.5
key passes /901.13
def actions /9014.4
pass accuracy89%
Nemanja Matic
Ball-winner / destroyer · Midfielder
minutes604
goals · xG0 · 0.1
prog passes /905.2
key passes /901.19
def actions /9013.6
pass accuracy86%
Simone Cinquegrano
Stopper / marker · Defender
minutes580
goals · xG0 · 0.4
prog passes /903.4
key passes /900.47
def actions /9012.3
pass accuracy82%
Domenico Berardi
Ball-winner / destroyer · Midfielder
minutes545
goals · xG2 · 1.4
prog passes /904.5
key passes /901.65
def actions /9012.2
pass accuracy76%
Kieron Bowie
Advanced creator · Attacking mid
minutes505
goals · xG1 · 1.6
prog passes /900.9
key passes /901.60
def actions /908.4
pass accuracy78%
Duje Ćaleta-Car
Stopper / marker · Defender
minutes472
goals · xG0 · 0.3
prog passes /902.1
key passes /900.00
def actions /9014.7
pass accuracy89%

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: press intensity (PPDA) (0th pct)
Sign a high-energy presser to lift defensive intensity. The data flags this because the press is passive (8.61, 0th percentile vs the league).
Need — bottom-third: xG created /game (25th pct)
Sign a higher-volume goalscorer or chance creator. The data flags this because the attack under-produces xG (1.22, 25th percentile vs the league).
Need — bottom-third: xG conceded /game (25th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.62, 25th percentile vs the league).
Vision AI · building report