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Team reportSerie A 2026

Roma

A possession-dominant side, aggressive high-press out of possession, with a high-volume attack. Currently #3 of 20 on 21 points (6-3-0, 23:8). Tactical profile below is built from 9 matches of ball-by-ball event data, contextualised against the league.

possession-dominantaggressive high-presshigh-volume attack
D
W
W
W
W
W
W
W
W
W
D
D
W
D
W
21
points
#3 of 20 · 9 games
23:8
goals
+15 GD
6-3-0
record
W-D-L
2.33
points/game
#3 in the league
1.99
xG for/game
rank #2
1.33
xG against/game
rank #9
#2
press rank
of 20 · most aggressive
64%
field tilt
#3
Roma
League average
Expected goals for / game
1.991.43
Expected goals against / game
1.331.43
Field tilt
64%50%
Pass retention
84%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 Roma and how good was the season?
Read. Roma currently sit #3 of 20 on 21 points (6W-3D-0L, 2.33 pts/game), scoring 23 and conceding 8 for a goal difference of +15. On the ball they are a possession-dominant team (64% field tilt, #3 in the league); off it they defend with a aggressive high-press (#2 of 20 for press intensity). Across the 9 matches of event data, they create 1.99 xG/game (#2) and concede 1.33 (#9), a net of +0.66 xG/game — the underlying performance diverges from the actual goal difference.

Season Context — the league table

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

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

#teamPWDLGFGAGDPts
1Lazio9810227+1525
2Inter87102310+1322
3Roma9630238+1521
4Como9621178+920
5AC Milan8530167+918
6Frosinone84221713+414

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Roma 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+'+3.32-0.91
Vision AI Model Insight
Roma tend to fade after a strong start — first-half net xG +5.00, second-half +0.93. Their strongest period is 16-30' (net +3.32 xG); their most dangerous period to face is 46-60' (net -0.91 xG against them).

xG Race — the season, match by match

Expected goals piling up over 9 matches: Roma 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 (+5.9 xG). Hover a point for that match.

06131917.912.0Fiorentina (H) 4-0 · xG 2.61 to 0.39Lecce (A) 4-0 · xG 2.15 to 1.18Atalanta (H) 2-1 · xG 3.16 to 0.63Torino (A) 2-0 · xG 1.88 to 0.98Inter (H) 2-2 · xG 1.72 to 2.23Como (A) 0-0 · xG 0.63 to 1.75Genoa (H) 2-0 · xG 1.40 to 0.62Napoli (A) 3-3 · xG 1.79 to 1.88Cagliari (H) 4-2 · xG 2.55 to 2.30M1M2M3M4M5M6M7M8M9
RomaOpponents against Roma

Tactical DNA

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

68
Build-Up
possession control from the back
85
Progression
moving the ball upfield with threat
88
Creation
manufacturing chances
88
Press
winning the ball high & hard
55
Solidity
resisting the opponent's threat
Genetic identity
Roma are defined most by their Creation DNA (88/100 · elite at manufacturing chances), and least by their Solidity DNA (55/100). 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).

Possess74Disrupt59Finish80Press91Defend90
Possess
Deep buildup
61%
Possession
78%
Field tilt
83%
Disrupt
Central progression ~proxy
65%
Dribble tendency
26%
Progressive passes
87%
Finish
Final-third patience
96%
Shot quality
78%
Open-play xG
65%
Press
Forward press ~proxy
91%
High regains
87%
Pressing efficiency ~proxy
96%
Defend
Def-mid press ~proxy
91%
High line ~proxy
91%
PAdj defensive actions
87%
Roma is defined most by Press (91% in the league) and weakest on Disrupt (59%). 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 Roma actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Roma'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; Roma 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/gRoma33%45%57%69%0.41.22.02.8FIELD TILT %POINTS / GAME
Vision AI Model Insight
Roma post 64% field tilt, ranking #3 of 20 in the league — a genuinely territory-dominant side, and their 2.33 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 Roma has the ball, how much of that time is spent building, progressing and creating?

The share of Roma'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: 21.2% of the time on the ball21%Progression: 44.7% of the time on the ball45%Chance creation: 30.8% of the time on the ball31%Attacking transition: 3.3% of the time on the ball45%PROGRESSION
PhaseShare of the time
Build-up21.2%
Progression44.7%
Chance creation30.8%
Attacking transition3.3%
Vision AI Model Insight
Progression is where Roma spends most of its time on the ball (45% 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.

Mario Hermoso ↔ Wesley: 111 passes, 0.3 combined xTBryan Cristante ↔ Matías Soulé: 71 passes, 1.0 combined xTBryan Cristante ↔ Gianluca Mancini: 70 passes, 0.8 combined xTGianluca Mancini ↔ Emanuele Lulli: 66 passes, 0.1 combined xTBryan Cristante ↔ Evan Ndicka: 60 passes, 0.5 combined xTPaulo Dybala ↔ Emanuele Lulli: 57 passes, 1.0 combined xTBryan Cristante ↔ Wesley: 49 passes, 0.6 combined xTNahuel Molina ↔ Mario Hermoso: 45 passes, 0.2 combined xTBryan Cristante ↔ Niccolò Pisilli: 43 passes, 0.4 combined xTBryan Cristante ↔ Nahuel Molina: 41 passes, 0.5 combined xTEvan Ndicka ↔ Mario Hermoso: 41 passes, 0.1 combined xTMatías Soulé ↔ Wesley: 41 passes, 1.4 combined xTBryan Cristante ↔ Paulo Dybala: 40 passes, 1.4 combined xTBryan Cristante ↔ Mario Hermoso: 40 passes, -0.0 combined xTBryan Cristante ↔ Emanuele Lulli: 40 passes, 0.0 combined xTPaulo Dybala ↔ Gianluca Mancini: 40 passes, 0.7 combined xTNahuel Molina ↔ Matías Soulé: 40 passes, 1.4 combined xTPaulo Dybala ↔ Nahuel Molina: 35 passes, 1.4 combined xTMario Hermoso ↔ Niccolò Pisilli: 34 passes, 0.2 combined xTMatías Soulé ↔ Emanuele Lulli: 33 passes, 0.6 combined xTEvan Ndicka ↔ Niccolò Pisilli: 31 passes, -0.1 combined xTMario Hermoso ↔ Matías Soulé: 31 passes, 0.4 combined xTPaulo Dybala ↔ Wesley: 30 passes, 1.1 combined xTGianluca Mancini ↔ Evan Ndicka: 28 passes, -0.1 combined xTMatías Soulé — isolate this player's connectionsSouléAlessandro Romano — isolate this player's connectionsRomanoWesley — isolate this player's connectionsWesleyGianluca Mancini — isolate this player's connectionsManciniMario Hermoso — isolate this player's connectionsHermosoDonyell Malen — isolate this player's connectionsMalenNahuel Molina — isolate this player's connectionsMolinaEvan Ndicka — isolate this player's connectionsNdickaSantiago Castro — isolate this player's connectionsCastroZeki Çelik — isolate this player's connectionsÇelikBryan Cristante — isolate this player's connectionsCristanteNiccolò Pisilli — isolate this player's connectionsPisilliEmanuele Lulli — isolate this player's connectionsLulliDaniele Ghilardi — isolate this player's connectionsGhilardiRodrigo Mora — isolate this player's connectionsMoraPaulo Dybala — isolate this player's connectionsDybala
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Hermoso ↔ Wesley
111p · 0.3xT
Cristante ↔ Soulé
71p · 1.0xT
Cristante ↔ Mancini
70p · 0.8xT
Mancini ↔ Lulli
66p · 0.1xT
Cristante ↔ Ndicka
60p · 0.5xT
Dybala ↔ Lulli
57p · 1.0xT
Cristante ↔ Wesley
49p · 0.6xT
Molina ↔ Hermoso
45p · 0.2xT
Cristante ↔ Pisilli
43p · 0.4xT
Cristante ↔ Molina
41p · 0.5xT
Vision AI Model Insight
Busiest connection: Mario Hermoso ↔ Wesley (111 passes). Most dangerous per pass: Paulo Dybala ↔ Nahuel Molina (0.04 xT/pass over 35 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Roma 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 Roma 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
5256
ACTIONS
3%4%9%4%4%10%9%9%9%11%8%5%3%4%7%PASSES
Carries
the ball moved with a player
1320
ACTIONS
2%4%7%5%4%9%10%10%10%12%10%4%2%4%7%CARRIES
Vision AI Model Insight
Their single busiest zone is the left wing of the middle third (11.0% of all actions). 58% of actions run through the inside lanes (centre + both half-spaces) versus 42% down the two wings — an inside-dominant, half-space build. By third: 25% defensive, 48% middle, 27% 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. Roma leaned on their right (41%). The bars under the pitch put the league’s share beside theirs.

39%Left side21%Middle41%Right sideATTACKING →
Roma
39%21%41%
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. Roma made 516 this season (57.3 a match); 34% 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: 177 entries (34%)17734%LEFT WINGLeft half-space: 61 entries (12%)6112%LEFT HALF-SPACECentre: 50 entries (10%)5010%CENTRERight half-space: 72 entries (14%)7214%RIGHT HALF-SPACERight wing: 156 entries (30%)15630%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing17719.734%29%
Left half-space616.812%15%
Centre505.610%13%
Right half-space728.014%16%
Right wing15617.330%28%
Build-up2 sections

Build-Up — the pass map

The football question
How does Roma 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.

1316build-up passes attempted
84%completed
29%reach the middle third
0%go long into the final third

Pass types

245CB · 22%
69Long Wide · 6%
3Long Central · 0%
610Wide → FB · 55%
177Central · 16%

Sequence success — build-up

115build-up sequences this season
17%succeed — reach the next third or a shot
38%turned over with nothing to show
CB245 · 22%
right: 123 passes, most from Ndicka123left: 122 passes, most from Ndicka122
Long Wide69 · 6%
right: 40 passes, most from Gollini40left: 29 passes, most from Gollini29
Long Central3 · 0%
left: 2 passes, most from Soulé2
Wide → FB610 · 55%
left: 333 passes, most from Hermoso333right: 277 passes, most from Mancini277
Central177 · 16%
left: 91 passes, most from Hermoso91right: 86 passes, most from Hermoso86
◆ Vision AI Insight
Roma build predominantly down the left, with Ndicka as the fulcrum (157 build-up passes). Only 30% 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 (83×).

Pass Explorer

Every pass of Roma’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. 496 progressive passes across 9 matches (55.1/game).

Origin lane

Right wing
34%
Right half-space
13%
Central
8%
Left half-space
14%
Left wing
31%
Progression is right-dominant: 47% right side · 8% central · 45% left.

Who generates it

Wesley
69 · 14%
Matías Soulé
64 · 13%
Paulo Dybala
50 · 10%
Nahuel Molina
45 · 9%
Bryan Cristante
34 · 7%
Top two — Wesley & Matías Soulé — account for 27% of all progression.
PROGRESSION
55.1 prog passes/game
mostly right
→
PENETRATION
24% reach final third
26% reach the box
→
THREAT
the other 76% is recycled
progress ≠ danger
What came of it. 24% of progressive passes reached the final third and 26% the box; the rest was recycled in front of the block. 27% of the progression ran through two players, mostly down the right side.

Which lanes actually create the threat

Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.

Per lane — volume vs threat
Right wingefficient
Right half-spacebalanced
Centralbalanced
Left half-spacebalanced
Left wingbalanced

Progression — the pass map

The football question
Once Roma 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.

2523progression passes attempted
87%completed
18%break into the final third
10%go backward into the defensive third

Pass types

272CB · 12%
81Long Wide · 4%
16Long Central · 1%
1468Wide → FB · 67%
359Central · 16%

Sequence success — progression

278progression sequences this season
37%succeed — reach the next third or a shot
31%turned over with nothing to show
CB272 · 12%
right: 145 passes, most from Ghilardi145left: 127 passes, most from Ndicka127
Long Wide81 · 4%
left: 43 passes, most from Cristante43right: 38 passes, most from Hermoso38
Long Central16 · 1%
left: 9 passes, most from Hermoso9right: 7 passes, most from Koulierakis7
Wide → FB1468 · 67%
left: 797 passes, most from Hermoso797right: 671 passes, most from Cristante671
Central359 · 16%
left: 180 passes, most from Cristante180right: 179 passes, most from Cristante179
◆ Vision AI Insight
Roma progress predominantly down the left, with Cristante the busiest midfield outlet (297 progression passes). Only 18% of passes that start in midfield actually break the final-third line — the rest (72%) is recycled back into midfield or (10%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LW mid → LHS mid (133×) — press that lane and midfield progression stalls.

Decision Quality — not all completed passes are equal

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

Excellent (high xT gain)
14%
Progressive
1%
Neutral / sideways
50%
Safe / backward
35%
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 Roma actually progress the ball with their feet, not a pass?

320 progressive carries this season across the whole squad (24% of 1320 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 52m. Most active carrier: Cristante (45). Filter to one player below.

First (96)Second (88)Third (74)Fourth (62)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 Roma'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.

171shots
17.9xG
0.10xG per shot
9big chances (0.3+ xG)
23goals
#2key passes / game in the league
#2box entries / game in the league
Attacking transition: 49 shots (29%)29%49Settled attack: 93 shots (54%)54%93Set piece: 29 shots (17%)17%29171SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 29% of shots4945.750.12
Cross310.200.07
Cut-back711.290.18
Long ball100.100.10
Pass into the box / short pass2923.760.13
Own creation (carry, dribble, rebound)900.410.05
Settled attack 54% of shots93169.970.11
Cross1210.980.08
Cut-back1421.410.10
Long ball300.170.06
Pass into the box / short pass51106.070.12
Own creation (carry, dribble, rebound)1331.330.10
Set piece 17% of shots2932.160.07
Corner2632.090.08
Free kick300.070.02

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
Paulo Dybala193.446
Wesley181.942
Emanuele Lulli81.401
Rodrigo Mora81.311
Donyell Malen131.062

Who takes them

PlayerShotsxGGoals
Donyell Malen305.537
Matías Soulé251.983
Santiago Castro151.691
Paulo Dybala211.500
Rodrigo Mora131.212
Vision AI Model Insight
The biggest source of Roma's chances, by xG, is settled attack (10.0 of 17.9 xG, 93 of 171 shots), mostly pass into the box / short pass. 49 of the 171 shots (29%) came within 15 seconds of winning the ball. 29 of the 171 shots came from set pieces; 23 goals from 17.9 xG (+5.1).

Chance Creation — the pass map

The football question
How does Roma 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 · 2%
5Long Wide · 4%
8Long Central · 6%
46Wide → FB · 35%
69Central · 53%

Sequence success — final-third

204final-third sequences this season
28%succeed — produce a shot
32%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 · 2%
left: 3 passes, most from Ghilardi3
Long Wide5 · 4%
right: 3 passes, most from Malen3left: 2 passes, most from Dybala2
Long Central8 · 6%
left: 5 passes, most from Dybala5right: 3 passes, most from Dybala3
Wide → FB46 · 35%
left: 23 passes, most from Wesley23right: 23 passes, most from Malen23
Central69 · 53%
right: 35 passes, most from Dybala35left: 34 passes, most from Soulé34

Who creates — volume × threat

22Dybala
18Wesley
15Soulé
12Malen
12Molina
8Lulli
8Pisilli
131key passes #2 of 20
20.9box entries/game #2 of 20
44.3final-3rd entries/game #4 of 20
1.99xG/game #2 of 20
23goals #1 of 20
+5.1finishing vs xG #2 of 20
◆ Vision AI Insight
Roma lean right — 43% of their key passes come from that flank and its half-space (56 of 131), most often from Dybala (13). They funnel chances into the c of the final third, most often via RHS att → C att (22 key passes, most often from Lulli). Dybala is the primary source overall. They generate 1.99 xG a game and finish it clinical — they beat their xG, led by Donyell Malen (7G), Matías Soulé (3G), Niccolò Pisilli (3G).

Crosses & Cutbacks — squad-wide

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

137 crosses: 59 found a team-mate (43%), 19 led to a shot (14%). 53 cut-backs: 27 found a team-mate (51%), 18 led to a shot (34%). 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 Roma actually cross from?

137 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 byline right wing; 6 come from the half-spaces and 0 from the centre.

deep right wing: 6 crosses (4%)4%6deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 4 crosses (3%)3%4advanced right wing: 28 crosses (20%)20%28advanced right half-space: 2 crosses (1%)1%2advanced centre: 0 crosses (0%)advanced left half-space: 1 crosses (1%)1%1advanced left wing: 24 crosses (18%)18%24byline right wing: 41 crosses (30%)30%41byline right half-space: 2 crosses (1%)1%2byline centre: 0 crosses (0%)byline left half-space: 1 crosses (1%)1%1byline left wing: 28 crosses (20%)20%28
TerritoryCrossesShareLed to a shot
byline · right wing4130%6
advanced · right wing2820%2
byline · left wing2820%7
advanced · left wing2418%4
deep · right wing64%0
deep · left wing43%0
advanced · right half-space21%0
byline · right half-space21%0
advanced · left half-space11%0
byline · left half-space11%0
Finishing3 sections

Shot Map

171 shots for 17.9 xG (1.99/game, #2 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

High-volume attack. 19.0 shots/game at 0.105 xG/shot. Box entries 21/game (#2). Threat created 13.2 xT/game (#3).

Goal Sequences

The move behind each of Roma’s 23 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 — 23 goals traced.

How Do They Score?

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

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

By situation

Open play
20 · 87%
Set pieces
3 · 13%
Penalties
0 · 0%

By finish

Right foot
12 · 52%
Left foot
7 · 30%
Header
4 · 17%
Vision AI Model Insight
23 goals scored. 87% come in open play; set pieces add 13%. 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

45 of 171 pass attempts lost here (26%).26%45/171Roon31 of 227 pass attempts lost here (14%).14%31/227Svilar72 of 490 pass attempts lost here (15%).15%72/490Svilar30 of 228 pass attempts lost here (13%).13%30/228Hermoso34 of 200 pass attempts lost here (17%).17%34/200Wesley86 of 502 pass attempts lost here (17%).17%86/502Dybala55 of 477 pass attempts lost here (12%).12%55/477Cristante56 of 472 pass attempts lost here (12%).12%56/472Roon53 of 499 pass attempts lost here (11%).11%53/499Hermoso77 of 573 pass attempts lost here (13%).13%77/573Wesley92 of 415 pass attempts lost here (22%).22%92/415Lulli57 of 257 pass attempts lost here (22%).22%57/257Dybala34 of 159 pass attempts lost here (21%).21%34/159Cristante70 of 235 pass attempts lost here (30%).30%70/235Wesley66 of 351 pass attempts lost here (19%).19%66/351Molinaattacking →

How they lose it

Incomplete pass — attacking third
319
Failed forward pass
211
Failed take-on
83
Lost in the defensive third
212
Their weakest zone is the left half-space in the attacking third: 30% of 235 pass attempts there are lost (70 times). Separately, 37% 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 Roma 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.

82
Pressing Index
/100 · elite
Intensity83
PPDA, high-press share, high-zone actions
Height85
how high up the pitch they defend
Effectiveness95
high recoveries & high-regain share
Disruption58
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
20%
RHS
16%
C
28%
LHS
21%
LW
16%
By third (high / mid / low regain)
Def 40%
Mid 45%
Att 15%
Read
Ranked #2 of 20 for press intensity, this is a high press. 60% of defensive actions happen in the middle & attacking thirds, at an average height of 41. Of recoveries, 61% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#2/20lower = more intense; rank is what matters
Defensive actions / game154#5/20
High-press share24%#3/20def actions won high up
Defensive-action height (0–100)41.3#3/20avg pitch height of actions
High recoveries / game31.0#1/20ball won in mid+att third
High-recovery share61%#1/20share of recoveries won high
Opponent completion allowed80%#2/20lower = more disruptive
Opponent progressive allowed9.4%#15/20of 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 Roma win it back with a defensive action?

Counted over the 349 opposition possessions that Roma 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 Roma step in. Roma win it after 4.6 opponent passes in the first half-hour and after 4.2 after the hour mark (sooner).

PASSES THEY GET
4.5passes
median 3 · before Roma win it
TIME THEY KEEP IT
13sec
median 8s · 38.8 wins per game
How many passes the opponent got in before the ball was won
44%
31%
17%
9%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
5.2
17s
15–30′
4.2
13s
30–45+′
4.5
15s
45–60′
4.8
12s
60–75′
4.2
11s
75–90+′
4.2
11s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Roma 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 Roma 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) 1,316 passes

nothing unusual in this zone

Width of use+0.0921.18
Wide-channel share-0.090.30
Side bias+0.150.72
Pass length-0.1822.05
Long-ball share-0.510.18
Forward gain per pass-0.449.54
Backward-pass share-0.090.20
Deep-pass share-0.550.23
Completion+0.470.83
Seconds between passes-0.543.00
Side used

left 30% · central 43% · right 27%

Progression (middle third) 2,523 passes

touchline to touchline

Width of use+0.8927.46
Wide-channel share+0.700.45
Side bias+0.331.36
Pass length-0.0917.09
Long-ball share-0.420.08
Forward gain per pass+0.183.88
Backward-pass share-0.570.31
Deep-pass share-0.400.14
Completion+0.370.87
Seconds between passes-0.443.00
Side used

left 39% · central 25% · right 35%

Final third 1,417 passes

nothing unusual in this zone

Width of use-0.1931.14
Wide-channel share-0.280.56
Side bias-0.28-2.45
Pass length-0.2215.13
Long-ball share-0.740.07
Forward gain per pass+0.001.04
Backward-pass share+0.110.39
Deep-pass share-0.250.08
Completion+0.840.77
Seconds between passes-0.093.33
Side used

left 39% · central 14% · right 46%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Roma'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 Roma 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%
#11 of 20 · reaches final third in ≤3 passes
Patient build-up share30%
#8 of 20 · spells of 6+ passes
Tempo (possession length)18.0s
#9 of 20 · shorter = faster tempo
Passes per possession4.8
#9 of 20
Counter-attack shots /game0.91
#16 of 20 · shot within 12s of a regain in own half
Press→shot /game3.09
#8 of 20 · shot within 8s of a high regain
Speed to final third after regain11.8s
#6 of 20 · lower = faster break

Sequence success — attacking transition

19attacking transition sequences this season
37%succeed — produce a shot
26%turned over with nothing to show

Sequence success — defensive transition

73defensive transition sequences this season
67%succeed — reach the next third or a shot
10%turned over with nothing to show
Vision AI Model Insight
Roma are a patient build-up side: 17% of possessions reach the final third in 3 passes or fewer (#11 of 20), against 30% built patiently over 6+ passes (#8 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 3.09 times a game (#8 of 20) — a modest but real source of chances.
Defending the box2 sections

Vulnerability Map — how opponents hurt them

The report flipped: where do opponents create their threat against Roma? 385 opponent progressive passes and 108 shots faced (12.0 xG against) across the season.

Opponent threat by lane (attacking into Roma)

Right wing
20%
Right half-space
13%
Central
32%
Left half-space
8%
Left wing
27%
Where the danger came from. Opponents generated most of their threat through the central (32% of the danger conceded).

How Do They Concede?

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

Every goal Roma conceded across the loaded matches — the opponent's shots in Roma'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 (72 total)

1%6%11%1%3%11%14%17%19%17%Arthur AttaMateo PellegrinoJoão MárioÁlex JiménezCher NdourCharles De KetelaereLazar SamardzicRaoul BellanovaCharles De KetelaereGianluca GaetanoOlaf GorterSantiago PierottiLassana CoulibalyAmar FatahIvan IlicKian Fitz-JimNikola VlasicDaniel BragançaEmirhan IlkhanMilutin OsmajicAlessandro MarcandalliAlessandro MarcandalliSamuel WiafePietro ComuzzoLautaro MartínezCurtis JonesMarcus ThuramCurtis JonesCarlos AugustoNicolò BarellaPetar SucicYann BisseckNicolò BarellaNicolò BarellaPetar SucicKaikiLucas da CunhaAssane DiaoAssane DiaoJacobo RamónNico PazJesús RodríguezMáximo PerroneLuis MillaLuis MillaNico PazMatteo PolitanoRasmus HøjlundMatteo PolitanoRasmus HøjlundFrank AnguissaMathías OliveraGiovaneRafa MarínMathías OliveraRasmus HøjlundAlieu FaderaAdam ObertAdam ObertAlieu FaderaAlessandro DeiolaMichel AdopoAlessandro DeiolaM'Bala NzolaAdam ObertAlessandro RomanoAdam ObertAdam ObertMichel AdopoDaniel MaldiniAdam ObertYanis Massolin← own goal

By situation

Open play
6 · 75%
Set pieces
1 · 12%
Penalties
1 · 12%
Vision AI Model Insight
8 goals conceded. 75% come in open play; set pieces account for only 12%, so dead-ball defending is not the main issue. 12% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the left half-space of the attacking third (19% 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
20 g · 15.7 xG
Set pieces
3 g · 2.2 xG
Penalties
0 g
13% of goals come from set pieces (3 of 23), worth 2.2 xG from 29 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Roma's corners go?

54 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 (34)

26%12%24%9%6%6%
Delivered into the box 82%Short 18%

Left side (20)

5%35%20%5%5%5%10%10%
Delivered into the box 95%Short 5%

Where opponents attack Roma from set pieces

22 shots from opponent corners against Roma, 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 (10)

50%20%20%10%
Shot 10Goals 0

Left flag (12)

8%8%8%42%25%8%
Shot 12Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • xG created /game — 1.99 (90th pct)
  • press intensity (PPDA) — 4.48 (90th pct)
  • box entries /game — 20.89 (90th pct)
  • field tilt % — 63.73 (85th pct)
  • progression /game — 55.11 (85th 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.

Inter
94%
Como
78%
Napoli
77%
Juventus
66%
Lazio
60%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (3m)1.330.002.33
vs mid-block opponents (3m)3.001.671.67
vs low-block opponents (3m)3.331.003.00

Behaviour — how Roma actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents79%14%399.711.7
vs mid-block opponents84%10%5012.622.7
vs low-block opponents86%7%7617.228.3
Vision AI Model Insight
Facing a high press, retention drops to 79% vs 86% against a low block (7pt lower under pressure), and directness (long-ball share) sits at 14% 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. Roma are possession-dominant with a aggressive high-press. Their attack creates 1.99 xG a game and they concede 1.33 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 Roma’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.

Roma
across 9 matches this season
Field tiltat Como · 0-0 · 2026-10-1123%avg 64%
PPDAat Como · 0-0 · 2026-10-117.4avg 4.5
Threat from passingvs Atalanta · 2-1 · 2026-09-0514.87avg 7.52
Final-third entriesat Como · 0-0 · 2026-10-1125avg 57
Progressive passesvs Atalanta · 2-1 · 2026-09-0597avg 55
Passesat Como · 0-0 · 2026-10-11384avg 584
Expected goalsat Como · 0-0 · 2026-10-110.63avg 1.99
Defensive actionsvs Genoa · 2-0 · 2026-10-17178avg 154

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 Roma’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).

+22.1on-ball value, 9 matches
Where the value came from
Passes5256 actions+10.80
Carries1320 actions-0.01
Dribbles164 actions+0.87
Shots171 actions+7.01
Ball wins652 actions+3.44
Most on-ball value (OBV)ActionsOBVper 100
Paulo Dybala477+3.90+0.82
Matías Soulé620+2.94+0.47
Donyell Malen230+2.65+1.15
Mario Hermoso570+1.64+0.29
Wesley532+1.53+0.29
Bryan Cristante725+1.35+0.19
Emanuele Lulli381+1.23+0.32
Rodrigo Mora204+1.23+0.60
123456
Biggest single movesOBV
1  Paulo Dybala · pass+0.627
2  Paulo Dybala · pass+0.511
3  Paulo Dybala · pass+0.464
4  Gianluca Mancini · pass+0.461
5  Rodrigo Mora · pass+0.461
6  Donyell Malen · shot+0.449

Set Pieces by Player

Who delivers Roma’s dead balls and who finishes them this season. 54 corners taken, most by Paulo Dybala (21); 29 shots from corners and free kicks, 3 goals, led by Leonardo Balerdi (1 goals, 0.47 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
Paulo Dybala2113 (62%)1—0.021—
Matías Soulé1713 (76%)2—0.052—
Evan Ndicka——4—0.23——
Bryan Cristante——4—0.24——
Nahuel Molina54 (80%)2—0.05——
Donyell Malen——3—0.35——
Leonardo Balerdi——310.47——
Niccolò Pisilli86 (75%)——0.00——
Manu Koné——2—0.08——
Mario Hermoso——210.20——
Santiago Castro——210.12——
Konstantinos Koulierakis——2—0.25——
Rodrigo Mora11 (100%)1—0.04——
Gianluca Mancini——1—0.08——

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
Mile SvilarGK4706.9Shot-Stopping 69%
Donyell MalenST5626.7Box Threat 93%Finishing 90%Ball-Carrying 66%Aerial Threat 0%
WesleyCM5976.7Progression 68%Chance Creation 51%Ball-Carrying 47%Successful Dribble 26%
Emanuele LulliW4886.5Ball-Carrying 57%Chance Creation 47%Wide Delivery 44%Box Threat 22%
Paulo DybalaAM5006.2Chance Creation 60%Box Threat 54%Ball-Carrying 34%
Bryan CristanteCM6275.7Ball-Carrying 69%Progression 66%Successful Dribble 50%Chance Creation 42%
Evan NdickaCB5715.5Ball-Winning 62%Ball-Carrying 41%Progression 36%Aerial & Box Defending 34%
Matías SouléAM6245.2Ball-Carrying 69%Box Threat 29%Chance Creation 25%
Gianluca ManciniFB6634.8Ball-Winning 58%Wide Delivery 44%Ball-Carrying 41%
Mario HermosoFB5814.7Ball-Winning 70%Wide Delivery 38%Ball-Carrying 33%

Top Creators

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

playerposminkey P /90box entriesxT
Paulo DybalaM5003.963510.8
Matías SouléM6242.163011.9
WesleyM5972.712411.0
Nahuel MolinaM3972.72147.8
Emanuele LulliM4881.48125.9
Rodrigo MoraM2942.14122.7
Donyell MalenF5621.9272.8
Niccolò PisilliM4181.7294.1

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)
Emanuele LulliW4883 (0%)7 (43%)
Gianluca ManciniFB6633 (33%)5 (20%)
Mario HermosoFB58101 (100%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Bryan CristanteM62713617737
Evan NdickaD57113041132
Mario HermosoD581124141943
Gianluca ManciniD663101141025
Leonardo BalerdiD36092121022
WesleyM5979014536
Matías SouléM624797334
Emanuele LulliM4887211431

Full Squad Data

Every player with 100+ minutes (21 players).

playerposappsmingoalsxGkey PprogdefxT
Gianluca ManciniD866300.65261017.2
Bryan CristanteM762700.813413612.1
Matías SouléM962432.015647911.9
WesleyM859700.418699011.0
Mario HermosoD858110.55341249.5
Evan NdickaD757100.41111304.1
Donyell MalenF856275.5129362.8
Paulo DybalaM650001.522505910.8
Emanuele LulliM748820.6830725.9
Mile SvilarG547000.006162.7
Manu KonéM641920.6613654.6
Niccolò PisilliM841830.9813534.1
Nahuel MolinaM739700.11245647.8
Marten de RoonM638500.0217594.8
Pierluigi GolliniG438000.009183.0
Leonardo BalerdiD636020.7012923.5
Santiago CastroF731411.722440.8
Rodrigo MoraM729421.2711282.7
Devyne RenschM622000.0211301.6
Konstantinos KoulierakisD419300.3015383.6
Daniele GhilardiD618900.026442.1

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.

Gianluca Mancini
Stopper / marker · Defender
minutes663
goals · xG0 · 0.6
prog passes /903.5
key passes /900.68
def actions /9013.7
pass accuracy88%
Bryan Cristante
Ball-winner / destroyer · Midfielder
minutes627
goals · xG0 · 0.8
prog passes /904.9
key passes /900.14
def actions /9019.5
pass accuracy87%
Matías Soulé
Creative forward · Forward
minutes624
goals · xG3 · 2.0
prog passes /909.2
key passes /902.16
def actions /9011.4
pass accuracy83%
Wesley
Advanced creator · Attacking mid
minutes597
goals · xG0 · 0.4
prog passes /9010.4
key passes /902.71
def actions /9013.6
pass accuracy80%
Mario Hermoso
Ball-playing defender · Defender
minutes581
goals · xG1 · 0.5
prog passes /905.3
key passes /900.77
def actions /9019.2
pass accuracy88%
Evan Ndicka
Stopper / marker · Defender
minutes571
goals · xG0 · 0.4
prog passes /901.7
key passes /900.16
def actions /9020.5
pass accuracy93%
Donyell Malen
Creative forward · Forward
minutes562
goals · xG7 · 5.5
prog passes /901.4
key passes /901.92
def actions /905.8
pass accuracy85%
Paulo Dybala
Creative forward · Forward
minutes500
goals · xG0 · 1.5
prog passes /909.0
key passes /903.96
def actions /9010.6
pass accuracy76%
Emanuele Lulli
Advanced creator · Attacking mid
minutes488
goals · xG2 · 0.6
prog passes /905.5
key passes /901.48
def actions /9013.3
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: pass retention % (50th pct)
Sign a secure ball-retaining midfielder. The data flags this because possession is turned over cheaply (83.68, 50th percentile vs the league).
Vision AI · building report