Vision AI ← BACK TO SEARCHSeason2025/262026 · this seasonAll seasons
Building the full report
Combining every season — this one is larger, give it a moment.
Team reportSerie A 2026

Inter

A possession-dominant side, aggressive high-press out of possession, with a high-volume attack. Currently #2 of 20 on 22 points (7-1-0, 23:10). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

possession-dominantaggressive high-presshigh-volume attack
W
W
D
W
W
D
D
W
W
W
W
D
W
W
W
22
points
#2 of 20 · 8 games
23:10
goals
+13 GD
7-1-0
record
W-D-L
2.75
points/game
#2 in the league
2.59
xG for/game
rank #1
0.96
xG against/game
rank #2
#4
press rank
of 20 · most aggressive
69%
field tilt
#1
Inter
League average
Expected goals for / game
2.591.43
Expected goals against / game
0.961.43
Field tilt
69%50%
Pass retention
88%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 Inter and how good was the season?
Read. Inter currently sit #2 of 20 on 22 points (7W-1D-0L, 2.75 pts/game), scoring 23 and conceding 10 for a goal difference of +13. On the ball they are a possession-dominant team (69% field tilt, #1 in the league); off it they defend with a aggressive high-press (#4 of 20 for press intensity). Across the 8 matches of event data, they create 2.59 xG/game (#1) and concede 0.96 (#2), a net of +1.63 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

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

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

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

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Inter 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+'+5.39
Vision AI Model Insight
Inter tend to come alive after the break — first-half net xG +2.45, second-half +10.55. Their strongest period is 76-90+' (net +5.39 xG); their most dangerous period to face is 31-45' (net +0.12 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Inter 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 (+13.0 xG). Hover a point for that match.

07152220.77.7Monza (H) 4-1 · xG 1.17 to 0.96Cagliari (A) 1-0 · xG 2.89 to 0.49Napoli (H) 3-2 · xG 4.13 to 1.95Udinese (H) 5-3 · xG 2.43 to 0.66Roma (A) 2-2 · xG 2.23 to 1.72Parma Calcio 1913 (H) 3-0 · xG 2.20 to 0.52Bologna (A) 3-1 · xG 2.41 to 1.03Fiorentina (H) 2-1 · xG 3.22 to 0.32M1M2M3M4M5M6M7M8
InterOpponents against Inter

Tactical DNA

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

95
Build-Up
possession control from the back
95
Progression
moving the ball upfield with threat
95
Creation
manufacturing chances
88
Press
winning the ball high & hard
90
Solidity
resisting the opponent's threat
Genetic identity
Inter are defined most by their Build-Up DNA (95/100 · elite at possession control from the back), and least by their Press DNA (88/100). 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).

Possess94Disrupt35Finish80Press84Defend80
Possess
Deep buildup
96%
Possession
91%
Field tilt
96%
Disrupt
Central progression ~proxy
9%
Dribble tendency
0%
Progressive passes
96%
Finish
Final-third patience
52%
Shot quality
91%
Open-play xG
96%
Press
Forward press ~proxy
74%
High regains
91%
Pressing efficiency ~proxy
87%
Defend
Def-mid press ~proxy
70%
High line ~proxy
96%
PAdj defensive actions
74%
Inter is defined most by Possess (94% in the league) and weakest on Disrupt (35%). 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 Inter actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Inter'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; Inter 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/gInter33%45%57%69%0.41.22.02.8FIELD TILT %POINTS / GAME
Vision AI Model Insight
Inter post 69% field tilt, ranking #1 of 20 in the league — a genuinely territory-dominant side, and their 2.75 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 Inter has the ball, how much of that time is spent building, progressing and creating?

The share of Inter'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: 24.3% of the time on the ball24%Progression: 48.2% of the time on the ball48%Chance creation: 25.6% of the time on the ball26%Attacking transition: 2.0% of the time on the ball48%PROGRESSION
PhaseShare of the time
Build-up24.3%
Progression48.2%
Chance creation25.6%
Attacking transition2.0%
Vision AI Model Insight
Progression is where Inter spends most of its time on the ball (48% 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.

Manuel Akanji ↔ Alessandro Bastoni: 142 passes, -0.7 combined xTFederico Dimarco ↔ Alessandro Bastoni: 132 passes, 0.4 combined xTManuel Akanji ↔ Yann Bisseck: 88 passes, -0.4 combined xTYann Bisseck ↔ Andy Diouf: 83 passes, -0.1 combined xTNicolò Barella ↔ Yann Bisseck: 80 passes, 0.9 combined xTJosep Martínez ↔ Alessandro Bastoni: 77 passes, -0.2 combined xTPiotr Zielinski ↔ Alessandro Bastoni: 73 passes, 0.3 combined xTManuel Akanji ↔ Josep Martínez: 64 passes, -0.2 combined xTNicolò Barella ↔ Andy Diouf: 59 passes, 1.1 combined xTNicolò Barella ↔ Manuel Akanji: 58 passes, -0.0 combined xTFederico Dimarco ↔ Carlos Augusto: 54 passes, 0.0 combined xTAlessandro Bastoni ↔ Petar Sucic: 53 passes, 0.1 combined xTPiotr Zielinski ↔ Nicolò Barella: 52 passes, 0.4 combined xTPiotr Zielinski ↔ Manuel Akanji: 52 passes, 0.1 combined xTHakan Çalhanoglu ↔ Yann Bisseck: 51 passes, -0.3 combined xTJosep Martínez ↔ Yann Bisseck: 51 passes, -0.1 combined xTHakan Çalhanoglu ↔ Manuel Akanji: 50 passes, 0.5 combined xTManuel Akanji ↔ Andy Diouf: 45 passes, -0.1 combined xTHakan Çalhanoglu ↔ Alessandro Bastoni: 44 passes, 0.3 combined xTNicolò Barella ↔ Alessandro Bastoni: 43 passes, 0.2 combined xTAlessandro Bastoni ↔ Carlos Augusto: 43 passes, 0.1 combined xTFederico Dimarco ↔ Petar Sucic: 42 passes, 0.9 combined xTPiotr Zielinski ↔ Yann Bisseck: 38 passes, 0.3 combined xTHakan Çalhanoglu ↔ Carlos Augusto: 37 passes, 0.7 combined xTDavide Frattesi — isolate this player's connectionsFrattesiFederico Dimarco — isolate this player's connectionsDimarcoPiotr Zielinski — isolate this player's connectionsZielinskiYann Bisseck — isolate this player's connectionsBisseckMarcus Thuram — isolate this player's connectionsThuramManuel Akanji — isolate this player's connectionsAkanjiJosep Martínez — isolate this player's connectionsMartínezAlessandro Bastoni — isolate this player's connectionsBastoniAndy Diouf — isolate this player's connectionsDioufPetar Sucic — isolate this player's connectionsSucicNicolò Barella — isolate this player's connectionsBarellaFrancesco Pio Esposito — isolate this player's connectionsEspositoSimone Cinquegrano — isolate this player's connectionsCinquegranAnge-Yoan Bonny — isolate this player's connectionsBonnyCarlos Augusto — isolate this player's connectionsAugustoHakan Çalhanoglu — isolate this player's connectionsÇalhanoglu
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Akanji ↔ Bastoni
142p · -0.7xT
Dimarco ↔ Bastoni
132p · 0.4xT
Akanji ↔ Bisseck
88p · -0.4xT
Bisseck ↔ Diouf
83p · -0.1xT
Barella ↔ Bisseck
80p · 0.9xT
Martínez ↔ Bastoni
77p · -0.2xT
Zielinski ↔ Bastoni
73p · 0.3xT
Akanji ↔ Martínez
64p · -0.2xT
Barella ↔ Diouf
59p · 1.1xT
Barella ↔ Akanji
58p · -0.0xT
Vision AI Model Insight
Busiest connection: Manuel Akanji ↔ Alessandro Bastoni (142 passes). Most dangerous per pass: Federico Dimarco ↔ Petar Sucic (0.02 xT/pass over 42 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Inter 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 Inter 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
5262
ACTIONS
2%5%10%4%3%8%10%11%12%9%5%5%3%5%7%PASSES
Carries
the ball moved with a player
1263
ACTIONS
2%3%11%6%2%10%10%13%12%9%5%4%2%4%8%CARRIES
Vision AI Model Insight
Their single busiest zone is the left half-space of the middle third (12.0% of all actions). 65% of actions run through the inside lanes (centre + both half-spaces) versus 35% down the two wings — an inside-dominant, half-space build. By third: 24% defensive, 51% middle, 25% 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. Inter leaned on their left (42%). The bars under the pitch put the league’s share beside theirs.

42%Left side23%Middle35%Right sideATTACKING →
Inter
42%23%35%
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. Inter made 482 this season (60.2 a match); 32% 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: 154 entries (32%)15432%LEFT WINGLeft half-space: 99 entries (21%)9921%LEFT HALF-SPACECentre: 62 entries (13%)6213%CENTRERight half-space: 82 entries (17%)8217%RIGHT HALF-SPACERight wing: 85 entries (18%)8518%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing15419.232%29%
Left half-space9912.421%15%
Centre627.813%13%
Right half-space8210.217%16%
Right wing8510.618%28%
Build-up2 sections

Build-Up — the pass map

The football question
How does Inter 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.

1272build-up passes attempted
91%completed
27%reach the middle third
1%go long into the final third

Pass types

364CB · 31%
76Long Wide · 7%
20Long Central · 2%
481Wide → FB · 42%
217Central · 19%

Sequence success — build-up

88build-up sequences this season
17%succeed — reach the next third or a shot
39%turned over with nothing to show
CB364 · 31%
right: 210 passes, most from Bisseck210left: 154 passes, most from Akanji154
Long Wide76 · 7%
left: 43 passes, most from Martínez43right: 33 passes, most from Martínez33
Long Central20 · 2%
left: 12 passes, most from Martínez12right: 8 passes, most from Martínez8
Wide → FB481 · 42%
left: 288 passes, most from Martínez288right: 193 passes, most from Martínez193
Central217 · 19%
left: 111 passes, most from Bastoni111right: 106 passes, most from Martínez106
◆ Vision AI Insight
Inter build predominantly down the left, with Martínez as the fulcrum (237 build-up passes). Only 28% 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 (101×).

Pass Explorer

Every pass of Inter’s last 8 matches as an arrow, theirs first and the opponents’ with other team, each side attacking left to right (solid = completed, dashed grey = failed). Eight families per team — click any map to open it wide, then filter by channel or third, from one to another (or click a cell of the flow grids), by outcome, half, minute and passer. Channels: right wing, right half-space, centre, left half-space, left wing.

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. 505 progressive passes across 8 matches (63.1/game).

Origin lane

Right wing
26%
Right half-space
16%
Central
10%
Left half-space
14%
Left wing
34%
Progression is left-dominant: 42% right side · 10% central · 48% left.

Who generates it

Federico Dimarco
75 · 15%
Nicolò Barella
70 · 14%
Alessandro Bastoni
61 · 12%
Carlos Augusto
31 · 6%
Manuel Akanji
28 · 6%
Top two — Federico Dimarco & Nicolò Barella — account for 29% of all progression.
PROGRESSION
63.1 prog passes/game
mostly left
→
PENETRATION
27% reach final third
27% reach the box
→
THREAT
the other 73% is recycled
progress ≠ danger
What came of it. 27% of progressive passes reached the final third and 27% the box; the rest was recycled in front of the block. 29% 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
Centralsterile
Left half-spacesterile
Left wingefficient

Progression — the pass map

The football question
Once Inter 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.

2663progression passes attempted
91%completed
15%break into the final third
9%go backward into the defensive third

Pass types

616CB · 25%
87Long Wide · 4%
13Long Central · 1%
1315Wide → FB · 54%
397Central · 16%

Sequence success — progression

194progression sequences this season
33%succeed — reach the next third or a shot
30%turned over with nothing to show
CB616 · 25%
right: 384 passes, most from Bisseck384left: 232 passes, most from Akanji232
Long Wide87 · 4%
left: 47 passes, most from Çalhanoglu47right: 40 passes, most from Bastoni40
Long Central13 · 1%
left: 9 passes, most from Bastoni9right: 4 passes, most from Bastoni4
Wide → FB1315 · 54%
left: 811 passes, most from Bastoni811right: 504 passes, most from Barella504
Central397 · 16%
left: 219 passes, most from Bastoni219right: 178 passes, most from Bastoni178
◆ Vision AI Insight
Inter progress predominantly down the right, with Bastoni the busiest midfield outlet (297 progression passes). Only 15% of passes that start in midfield actually break the final-third line — the rest (76%) is recycled back into midfield or (9%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LHS mid → LW mid (151×) — press that lane and midfield progression stalls.

Decision Quality — not all completed passes are equal

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

Excellent (high xT gain)
14%
Progressive
2%
Neutral / sideways
45%
Safe / backward
39%
16% of passes are progressive-or-better; the remaining 84% 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 Inter actually progress the ball with their feet, not a pass?

307 progressive carries this season across the whole squad (24% of 1263 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 14m, longest 53m. Most active carrier: Bastoni (45). Filter to one player below.

First (117)Second (76)Third (70)Fourth (44)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 Inter'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.

185shots
20.7xG
0.11xG per shot
12big chances (0.3+ xG)
23goals
#1key passes / game in the league
#1box entries / game in the league
Attacking transition: 34 shots (18%)18%34Settled attack: 111 shots (60%)60%111Set piece: 40 shots (22%)22%40185SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 18% of shots3443.030.09
Cross700.880.13
Cut-back210.310.15
Pass into the box / short pass1821.390.08
Own creation (carry, dribble, rebound)710.460.07
Settled attack 60% of shots1111411.710.11
Cross2021.670.08
Cut-back1221.120.09
Long ball410.280.07
Pass into the box / short pass5366.300.12
Own creation (carry, dribble, rebound)2232.350.11
Set piece 22% of shots4055.940.15
Corner3434.240.12
Free kick400.110.03
Penalty221.590.79

Every attempt to create — and what came of it

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

Who sets the shots up

PlayerSet-upsxG createdGoals
Federico Dimarco121.881
Nicolò Barella121.662
Andy Diouf151.584
Carlos Augusto91.122
Piotr Zielinski51.122

Who takes them

PlayerShotsxGGoals
Lautaro Martínez254.614
Marcus Thuram283.465
Francesco Pio Esposito172.162
Ange-Yoan Bonny111.412
Piotr Zielinski121.322
Vision AI Model Insight
The biggest source of Inter's chances, by xG, is settled attack (11.7 of 20.7 xG, 111 of 185 shots), mostly pass into the box / short pass. 34 of the 185 shots (18%) came within 15 seconds of winning the ball. 40 of the 185 shots came from set pieces; 23 goals from 20.7 xG (+2.3).

Chance Creation — the pass map

The football question
How does Inter 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

11CB · 9%
5Long Wide · 4%
13Long Central · 10%
33Wide → FB · 26%
66Central · 52%

Sequence success — final-third

154final-third sequences this season
38%succeed — produce a shot
23%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
CB11 · 9%
right: 7 passes, most from Akanji7left: 4 passes, most from Bisseck4
Long Wide5 · 4%
right: 3 passes, most from Martínez3left: 2 passes, most from Bastoni2
Long Central13 · 10%
right: 8 passes, most from Dimarco8left: 5 passes, most from Dimarco5
Wide → FB33 · 26%
left: 18 passes, most from Esposito18right: 15 passes, most from Diouf15
Central66 · 52%
left: 34 passes, most from Dimarco34right: 32 passes, most from Diouf32

Who creates — volume × threat

18Dimarco
16Barella
15Diouf
12Çalhanoglu
9Augusto
7Bastoni
7Martínez
128key passes #1 of 20
26.6box entries/game #1 of 20
47.2final-3rd entries/game #2 of 20
2.59xG/game #1 of 20
23goals #1 of 20
+2.3finishing vs xG #8 of 20
◆ Vision AI Insight
Inter lean left — 45% of their key passes come from that flank and its half-space (57 of 128), most often from Dimarco (14). They funnel chances into the c of the final third, most often via LHS att → C att (20 key passes, most often from Dimarco). Dimarco is the primary source overall. They generate 2.59 xG a game and finish it clinical — they beat their xG, led by Marcus Thuram (5G), Lautaro Martínez (4G), Hakan Çalhanoglu (3G).

Crosses & Cutbacks — squad-wide

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

134 crosses: 67 found a team-mate (50%), 25 led to a shot (19%). 37 cut-backs: 26 found a team-mate (70%), 14 led to a shot (38%). 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 Inter actually cross from?

134 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. 28% come from one territory, the byline left wing; 7 come from the half-spaces and 0 from the centre.

deep right wing: 8 crosses (6%)6%8deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 1 crosses (1%)1%1deep left wing: 8 crosses (6%)6%8advanced right wing: 23 crosses (17%)17%23advanced right half-space: 0 crosses (0%)advanced centre: 0 crosses (0%)advanced left half-space: 1 crosses (1%)1%1advanced left wing: 33 crosses (25%)25%33byline right wing: 18 crosses (13%)13%18byline right half-space: 3 crosses (2%)2%3byline centre: 0 crosses (0%)byline left half-space: 2 crosses (1%)1%2byline left wing: 37 crosses (28%)28%37
TerritoryCrossesShareLed to a shot
byline · left wing3728%7
advanced · left wing3325%7
advanced · right wing2317%5
byline · right wing1813%5
deep · right wing86%0
deep · left wing86%1
byline · right half-space32%0
byline · left half-space21%0
deep · left half-space11%0
advanced · left half-space11%0
Finishing3 sections

Shot Map

185 shots for 20.7 xG (2.59/game, #1 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

High-volume attack. 23.1 shots/game at 0.112 xG/shot. Box entries 27/game (#1). Threat created 15.4 xT/game (#1).

Goal Sequences

The move behind each of Inter’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 Inter scored across the loaded matches, broken down by how it was created and finished.

By situation

Open play
18 · 78%
Set pieces
3 · 13%
Penalties
2 · 9%

By finish

Right foot
13 · 57%
Left foot
8 · 35%
Header
2 · 9%
Vision AI Model Insight
23 goals scored. 78% 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

16 of 127 pass attempts lost here (13%).13%16/127Bisseck15 of 237 pass attempts lost here (6%).6%15/237Martínez36 of 509 pass attempts lost here (7%).7%36/509Martínez15 of 234 pass attempts lost here (6%).6%15/234Bastoni32 of 165 pass attempts lost here (19%).19%32/165Dimarco38 of 417 pass attempts lost here (9%).9%38/417Barella43 of 550 pass attempts lost here (8%).8%43/550Barella43 of 588 pass attempts lost here (7%).7%43/588Barella52 of 635 pass attempts lost here (8%).8%52/635Sucic59 of 473 pass attempts lost here (12%).12%59/473Bastoni43 of 249 pass attempts lost here (17%).17%43/249Barella50 of 242 pass attempts lost here (21%).21%50/242Diouf31 of 173 pass attempts lost here (18%).18%31/173Esposito55 of 286 pass attempts lost here (19%).19%55/286Dimarco84 of 377 pass attempts lost here (22%).22%84/377Dimarcoattacking →

How they lose it

Incomplete pass — attacking third
263
Failed forward pass
176
Failed take-on
46
Lost in the defensive third
114
Their weakest zone is the left wing in the attacking third: 22% of 377 pass attempts there are lost (84 times). Separately, 43% 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 Inter 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.

84
Pressing Index
/100 · elite
Intensity83
PPDA, high-press share, high-zone actions
Height95
how high up the pitch they defend
Effectiveness78
high recoveries & high-regain share
Disruption82
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
17%
RHS
19%
C
23%
LHS
22%
LW
17%
By third (high / mid / low regain)
Def 38%
Mid 44%
Att 19%
Read
Ranked #4 of 20 for press intensity, this is a high press. 62% of defensive actions happen in the middle & attacking thirds, at an average height of 43. Of recoveries, 60% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#4/20lower = more intense; rank is what matters
Defensive actions / game136#18/20
High-press share27%#2/20def actions won high up
Defensive-action height (0–100)43.1#1/20avg pitch height of actions
High recoveries / game24.9#5/20ball won in mid+att third
High-recovery share60%#4/20share of recoveries won high
Opponent completion allowed81%#4/20lower = more disruptive
Opponent progressive allowed7.9%#3/20of 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 Inter win it back with a defensive action?

Counted over the 256 opposition possessions that Inter 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 Inter step in. Inter win it after 5.5 opponent passes in the first half-hour and after 3.4 after the hour mark (sooner).

PASSES THEY GET
4.6passes
median 3 · before Inter win it
TIME THEY KEEP IT
14sec
median 7s · 32.0 wins per game
How many passes the opponent got in before the ball was won
43%
30%
16%
11%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.1
19s
15–30′
4.8
16s
30–45+′
5.3
18s
45–60′
4.9
14s
60–75′
3.5
11s
75–90+′
3.3
10s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Inter 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 Inter 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) 1,272 passes

safer, circulating, playing short

Width of use-0.7519.44
Wide-channel share-0.820.25
Side bias+0.190.86
Pass length-0.7120.16
Long-ball share-0.820.15
Forward gain per pass-0.957.33
Backward-pass share+0.510.22
Deep-pass share-0.890.20
Completion+1.390.91
Seconds between passes-0.133.25
Side used

left 28% · central 46% · right 26%

Progression (middle third) 2,663 passes

safer

Width of use-0.6424.22
Wide-channel share-0.720.35
Side bias+0.461.88
Pass length-0.5616.44
Long-ball share-0.840.07
Forward gain per pass-0.462.90
Backward-pass share+0.060.34
Deep-pass share-0.750.12
Completion+1.040.91
Seconds between passes-0.163.12
Side used

left 36% · central 32% · right 32%

Final third 1,327 passes

safer, played inside, narrow, central

Width of use-0.9829.20
Wide-channel share-1.090.49
Side bias+0.795.14
Pass length-0.3015.00
Long-ball share-0.610.07
Forward gain per pass-0.370.55
Backward-pass share+0.290.41
Deep-pass share-0.350.08
Completion+1.290.80
Seconds between passes-0.533.00
Side used

left 48% · central 19% · right 34%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Inter'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 Inter 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%
#10 of 20 · reaches final third in ≤3 passes
Patient build-up share39%
#1 of 20 · spells of 6+ passes
Tempo (possession length)24.0s
#20 of 20 · shorter = faster tempo
Passes per possession6.3
#1 of 20
Counter-attack shots /game1.07
#6 of 20 · shot within 12s of a regain in own half
Press→shot /game3.74
#2 of 20 · shot within 8s of a high regain
Speed to final third after regain13.3s
#11 of 20 · lower = faster break

Sequence success — attacking transition

11attacking transition sequences this season
36%succeed — produce a shot
45%turned over with nothing to show

Sequence success — defensive transition

37defensive transition sequences this season
76%succeed — reach the next third or a shot
8%turned over with nothing to show
Vision AI Model Insight
Inter are a patient build-up side: 17% of possessions reach the final third in 3 passes or fewer (#10 of 20), against 39% built patiently over 6+ passes (#1 of 20). Winning the ball back leads to a shot inside 12 seconds 1.07 times a game (#6), and a high regain converts to a shot within 8 seconds 3.74 times a game (#2 of 20) — a genuine transition weapon.
Defending the box2 sections

Vulnerability Map — how opponents hurt them

The report flipped: where do opponents create their threat against Inter? 250 opponent progressive passes and 84 shots faced (7.7 xG against) across the season.

Opponent threat by lane (attacking into Inter)

Right wing
29%
Right half-space
19%
Central
19%
Left half-space
7%
Left wing
26%
Where the danger came from. Opponents generated most of their threat through the right wing (29% of the danger conceded).

How Do They Concede?

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

Every goal Inter conceded across the loaded matches — the opponent's shots in Inter'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 (51 total)

2%2%8%4%2%6%10%31%12%16%8%Patrick CutroneOmari ForsonAndrea CarboniManga Foe OndoaMathis MoutMichel AdopoAlieu FaderaAlessandro RomanoMichel AdopoMichel AdopoAlisson SantosAntonio VergaraGiovanni Di LorenzoLeonardo SpinazzolaMatteo PolitanoGiovanni Di LorenzoLeonardo SpinazzolaKevin De BruyneHassane KamaraUnai GómezKeinan DavisLewis FergusonTommaso PobegaArthur TheateJay EnemNadir ZorteaTommaso PobegaTommaso PobegaFranco MastantuonoNicolò FagioliMateo PellegrinoSandi LovricNahuel MolinaDonyell MalenDonyell MalenMatías SouléPaulo DybalaNahuel MolinaPaulo DybalaPaulo DybalaDonyell MalenPaulo DybalaPaulo DybalaMandela KeitaMandela KeitaNesta ElphegeEmanuele ValeriMariano TroiloMandela KeitaMandela KeitaValde← own goal

By situation

Open play
9 · 90%
Set pieces
1 · 10%
Penalties
0 · 0%
Vision AI Model Insight
10 goals conceded. 90% come in open play; set pieces account for only 10%, so dead-ball defending is not the main issue. 10% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right half-space of the attacking third (31% 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
18 g · 14.7 xG
Set pieces
3 g · 4.4 xG
Penalties
2 g
13% of goals come from set pieces (3 of 23), worth 4.4 xG from 38 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Inter's corners go?

46 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 (23)

13%9%35%4%22%9%
Delivered into the box 91%Short 9%

Left side (23)

22%26%9%13%4%4%4%13%
Delivered into the box 96%Short 4%

Where opponents attack Inter from set pieces

13 shots from opponent corners against Inter, 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 (6)

33%17%33%17%
Shot 6Goals 0

Left flag (7)

14%29%29%29%
Shot 7Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • xG created /game — 2.59 (95th pct)
  • field tilt % — 69.04 (95th pct)
  • progression /game — 63.12 (95th pct)
  • box entries /game — 26.62 (95th pct)
  • threat created /game — 15.36 (95th 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.

Roma
94%
Napoli
87%
Como
87%
Lazio
73%
Juventus
69%

Performance vs Opponent Styles

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

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)2.502.002.00
vs mid-block opponents (2m)2.500.503.00
vs low-block opponents (4m)3.251.253.00

Behaviour — how Inter actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents85%11%5814.225.0
vs mid-block opponents88%8%5615.527.5
vs low-block opponents90%8%6915.927.0
Vision AI Model Insight
Facing a high press, retention drops to 85% vs 90% against a low block (4pt lower under pressure), and directness (long-ball share) sits at 11% when pressed vs 8% against a low block — a mild adjustment, not a wholesale change.

Scouting Summary — the team in brief

In brief. Inter are possession-dominant with a aggressive high-press. Their attack creates 2.59 xG a game and they concede 0.96 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 Inter’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.

Inter
across 8 matches this season
Field tiltat Roma · 2-2 · 2026-09-1942%avg 69%
Passesat Roma · 2-2 · 2026-09-19512avg 658
Final-third entriesvs Fiorentina · 2-1 · 2026-10-2586avg 60
Expected goalsvs Napoli · 3-2 · 2026-09-054.13avg 2.59
PPDAat Roma · 2-2 · 2026-09-196.7avg 4.6
Progressive carriesat Roma · 2-2 · 2026-09-1946avg 65
Threat from passingvs Fiorentina · 2-1 · 2026-10-2510.53avg 8.34
Defensive actionsat Bologna · 3-1 · 2026-10-17108avg 136

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 Inter’s last 8 matches added up: where the value came from, who produced it, and the six biggest single moves. OBV only measures what a player does with the ball: it shows who added the most on-ball value, not who was the most important player (defending off the ball, positioning and pressing are not in it).

+21.3on-ball value, 8 matches
Where the value came from
Passes5262 actions+7.69
Carries1263 actions-0.04
Dribbles92 actions+0.44
Shots185 actions+10.69
Ball wins482 actions+2.55
Most on-ball value (OBV)ActionsOBVper 100
Lautaro Martínez197+3.67+1.86
Marcus Thuram187+2.15+1.15
Piotr Zielinski504+2.04+0.41
Andy Diouf391+1.51+0.39
Alessandro Bastoni773+1.32+0.17
Nicolò Barella621+1.29+0.21
Hakan Çalhanoglu424+1.25+0.29
Federico Dimarco477+1.17+0.25
123456
Biggest single movesOBV
1  Hakan Çalhanoglu · shot+0.662
2  Piotr Zielinski · shot+0.613
3  Federico Dimarco · pass+0.545
4  Piotr Zielinski · pass+0.511
5  Lautaro Martínez · shot+0.440
6  Lautaro Martínez · shot+0.422

Set Pieces by Player

Who delivers Inter’s dead balls and who finishes them this season. 46 corners taken, most by Federico Dimarco (20); 38 shots from corners and free kicks, 3 goals, led by Lautaro Martínez (2 goals, 1.67 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
Federico Dimarco2018 (90%)2—0.051—
Hakan Çalhanoglu139 (69%)1—0.0311/1
Manuel Akanji——6—1.06——
Nicolò Barella128 (67%)1—0.021—
Lautaro Martínez——521.67——
Henrikh Mkhitaryan——5—0.18——
Piotr Zielinski——210.08—1/1
Francesco Pio Esposito——3—0.35——
John Stones——2—0.13——
Yann Bisseck——2—0.18——
Carlos Augusto——2—0.12——
Aleksandar Stankovic11 (100%)1—0.031—
Alessandro Bastoni——1—0.07——
Benjamin Pavard——1—0.05——

Top Performers

Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 216 minutes). Coloured chips are that player's strongest capability blocks.

playerposminVision AI Scorecapability blocks
Alessandro BastoniFB5668.0Ball-Carrying 88%Ball-Winning 70%Wide Delivery 38%
Marcus ThuramST4777.5Finishing 86%Box Threat 81%Ball-Carrying 77%Aerial Threat 0%
Piotr ZielinskiCM4577.2Ball-Carrying 85%Progression 82%Successful Dribble 74%Chance Creation 51%
Nicolò BarellaAM6477.0Ball-Carrying 83%Chance Creation 66%Box Threat 60%
Federico DimarcoW4907.0Chance Creation 58%Box Threat 56%Wide Delivery 46%Ball-Carrying 22%
Manuel AkanjiCB6177.0Progression 88%Ball-Carrying 82%Ball-Winning 58%Aerial & Box Defending 9%
Yann BisseckCB5807.0Progression 87%Ball-Carrying 71%Ball-Winning 42%Aerial & Box Defending 10%
Francesco Pio EspositoST4793.6Box Threat 54%Finishing 35%Ball-Carrying 8%Aerial Threat 0%
Andy DioufW5542.5Ball-Carrying 60%Chance Creation 43%Wide Delivery 30%Box Threat 18%
Josep MartínezGK6542.5Shot-Stopping 25%

Top Creators

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

playerposminkey P /90box entriesxT
Federico DimarcoM4903.313314.0
Nicolò BarellaM6472.233114.7
Andy DioufM5542.44205.8
Alessandro BastoniD5661.111613.6
Hakan ÇalhanogluM2953.66117.1
Carlos AugustoM3852.10106.4
Francesco Pio EspositoF4791.32121.8
Marcus ThuramF4771.32122.5

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)
Federico DimarcoW49018 (78%)7 (71%)
Alessandro BastoniFB56614 (50%)2 (50%)
Andy DioufW55408 (50%)
Ange-Yoan BonnyW19105 (20%)

Defensive Volume Leaders

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

playerposmindef actionstacklesinterceptrecoveries
Manuel AkanjiD617118141424
Yann BisseckD58097121126
Alessandro BastoniD5668714533
Carlos AugustoM385783811
Nicolò BarellaM647667332
Andy DioufM5546212226
Marcus ThuramF47760804
Petar SucicM396549123

Full Squad Data

Every player with 100+ minutes (21 players).

playerposappsmingoalsxGkey PprogdefxT
Josep MartínezG765400.0020235.9
Nicolò BarellaM764710.716706614.7
Manuel AkanjiD761701.35281188.9
Yann BisseckD758010.5526977.7
Alessandro BastoniD756600.27618713.6
Andy DioufM755400.31524625.8
Federico DimarcoM849000.818754414.0
Francesco Pio EspositoF847922.275471.8
Marcus ThuramF747753.579602.5
Piotr ZielinskiM745721.3525428.4
Petar SucicM739610.6421546.3
Carlos AugustoM638520.9931786.4
Lautaro MartínezF536344.6713392.9
Hakan ÇalhanogluM629531.01222527.1
Henrikh MkhitaryanM424500.6416393.8
Benjamin PavardD321800.0111373.3
Luis HenriqueM521600.2227254.7
Ange-Yoan BonnyF719121.402310.4
Curtis JonesM416700.1310312.3
John StonesD310700.100290.8
Ivan ProvedelG110000.00320.8

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.

Josep Martínez
Goalkeeper · Goalkeeper
minutes654
goals · xG0 · 0.0
prog passes /902.8
key passes /900.00
def actions /903.2
pass accuracy89%
Nicolò Barella
Advanced creator · Attacking mid
minutes647
goals · xG1 · 0.7
prog passes /909.7
key passes /902.23
def actions /909.2
pass accuracy86%
Manuel Akanji
Stopper / marker · Defender
minutes617
goals · xG0 · 1.3
prog passes /904.1
key passes /900.73
def actions /9017.2
pass accuracy95%
Yann Bisseck
Stopper / marker · Defender
minutes580
goals · xG1 · 0.5
prog passes /904.0
key passes /900.78
def actions /9015.1
pass accuracy92%
Alessandro Bastoni
Ball-playing defender · Defender
minutes566
goals · xG0 · 0.2
prog passes /909.7
key passes /901.11
def actions /9013.8
pass accuracy90%
Andy Diouf
Advanced creator · Attacking mid
minutes554
goals · xG0 · 0.3
prog passes /903.9
key passes /902.44
def actions /9010.1
pass accuracy89%
Federico Dimarco
Advanced creator · Attacking mid
minutes490
goals · xG0 · 0.8
prog passes /9013.8
key passes /903.31
def actions /908.1
pass accuracy81%
Francesco Pio Esposito
Poacher / finisher · Forward
minutes479
goals · xG2 · 2.2
prog passes /900.9
key passes /901.32
def actions /908.8
pass accuracy69%
Marcus Thuram
Poacher / finisher · Forward
minutes477
goals · xG5 · 3.5
prog passes /901.7
key passes /901.32
def actions /9011.3
pass accuracy77%
Vision AI · building report