Combining every season — this one is larger, give it a moment.
Team reportSerie A 2026
Fiorentina
A balanced-territory side, aggressive high-press out of possession, with a moderate attack. Currently #18 of 20 on 4 points (1-1-6, 9:19). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.
In one read, what kind of team is Fiorentina and how good was the season?
Read. Fiorentina currently sit #18 of 20 on 4 points (1W-1D-6L, 0.50 pts/game), scoring 9 and conceding 19 for a goal difference of -10.
On the ball they are a balanced-territory team (50% field tilt, #10 in the league); off it they defend with a aggressive high-press (#13 of 20 for press intensity).
Across the 8 matches of event data, they create 1.39 xG/game (#9) and concede 1.55 (#15), a net of -0.17 xG/game — the underlying performance diverges from the actual goal difference.
Season Context — the league table
The question
Where did Fiorentina actually finish, and against whom?
The authoritative final table (full season), centred on Fiorentina.
#
team
P
W
D
L
GF
GA
GD
Pts
15
Monza
8
2
1
5
15
18
-3
7
16
Genoa
8
2
1
5
6
13
-7
7
17
Udinese
8
1
1
6
9
18
-9
4
18
Fiorentina
8
1
1
6
9
19
-10
4
19
Parma Calcio 1913
8
1
1
6
5
15
-10
4
20
Venezia
8
1
0
7
6
17
-11
3
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Fiorentina actually dominate for chances — and which periods hurt them?
Net xG (created minus conceded) in each 15-minute window, summed across the whole season's matches — above the line is time they dominate for chances, below is time it hurts them. Real on-clock shot timing.
dominant (net xG for)conceding (net xG against)
Vision AI Model Insight
Fiorentina tend to fade after a strong start — first-half net xG +0.12, second-half -1.44. Their strongest period is 46-60' (net +1.05 xG); their most dangerous period to face is 76-90+' (net -2.01 xG against them).
xG Race — the season, match by match
Expected goals piling up over 8 matches: Fiorentina 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 (-1.3 xG). Hover a point for that match.
FiorentinaOpponents against Fiorentina
Tactical DNA
The football question
In five genes, what is Fiorentina'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.
38
Build-Up
possession control from the back
35
Progression
moving the ball upfield with threat
58
Creation
manufacturing chances
42
Press
winning the ball high & hard
25
Solidity
resisting the opponent's threat
Genetic identity
Fiorentina are defined most by their Creation DNA (58/100 · average at manufacturing chances), and least by their Solidity DNA (25/100). Percentiles vs the 20 teams in the league.
The Playstyle Wheel
Fifteen style metrics across five domains — Possess, Disrupt, Finish, Press, Defend — each a percentile against the rest of the league. Metrics marked ~proxy use the closest available event-data signal where the standard definition needs data this feed doesn't carry (explicit pressure events, offside/keeper-sweep incidents).
Possess
Deep buildup
39%
Possession
52%
Field tilt
48%
Disrupt
Central progression ~proxy
61%
Dribble tendency
78%
Progressive passes
43%
Finish
Final-third patience
26%
Shot quality
48%
Open-play xG
52%
Press
Forward press ~proxy
35%
High regains
13%
Pressing efficiency ~proxy
22%
Defend
Def-mid press ~proxy
35%
High line ~proxy
22%
PAdj defensive actions
35%
Fiorentina is defined most by Disrupt (61% in the league) and weakest on Press (23%). Percentiles vs the 23 teams in the league this season.
In possession
In possession
How they keep the ball, build up, progress, create and finish, and where their attacks die.
How much of the pitch does Fiorentina actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Fiorentina'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; Fiorentina highlighted. Hover any dot for the team.
Vision AI Model Insight
Fiorentina post 50% field tilt, ranking #10 of 20 in the league — comfortably above the league mid-point for territorial control, and their 0.50 points/game sits below the league-average return — territory is genuinely converting into results.
Where the time goes — how long each phase lasts
The question
When Fiorentina has the ball, how much of that time is spent building, progressing and creating?
The share of Fiorentina's time on the ball spent in each phase of play, in the order the phases happen. A phase is where the ball is on the pitch (own third, middle third, final third); a transition or a set piece skips the build-up and is counted on its own.
Phase
Share of the time
Build-up
21.6%
Progression
45.9%
Chance creation
30.3%
Attacking transition
2.2%
Vision AI Model Insight
Progression is where Fiorentina spends most of its time on the ball (46% of its time on the ball).
Passing Network
The question
Who actually plays with whom — the real on-pitch connections, not just average positions?
Every pass linked to its likely receiver (the next same-team touch), aggregated into player-pair combinations at each player's average position. Line width = how often the pair combines; colour = threat generated per pass (blue low → red high). Hover a line for the pair, or click a player to isolate their connections.
width = passes between the paircolour = xT per pass: low → high
Top 10 combinations
Fagioli ↔ Jiménez
86p · 1.0xT
Ndour ↔ Jiménez
66p · 0.3xT
Ndour ↔ Mastantuono
66p · 0.2xT
Jiménez ↔ Mastantuono
66p · 0.5xT
Fagioli ↔ Valde
65p · 0.7xT
Fagioli ↔ Ndour
51p · 0.6xT
Fagioli ↔ Viery
48p · -0.0xT
Dragusin ↔ Jiménez
44p · 0.1xT
Fagioli ↔ Dragusin
42p · -0.2xT
Fagioli ↔ Mastantuono
35p · 1.1xT
Vision AI Model Insight
Busiest connection: Nicolò Fagioli ↔ Álex Jiménez (86 passes). Most dangerous per pass: David de Gea ↔ Mateo Pellegrino (0.14 xT/pass over 18 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Fiorentina had the ball
Every touch across 80 matches. Brighter means more touches.
Which Zones Do They Attack Through?
The question
Across the whole pitch, where does Fiorentina 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
3424
ACTIONS
Carries
the ball moved with a player
1020
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the middle third (10.6% of all actions). 62% of actions run through the inside lanes (centre + both half-spaces) versus 38% down the two wings — an inside-dominant, half-space build. By third: 25% defensive, 48% middle, 26% 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. Fiorentina leaned on their right (41%). The bars under the pitch put the league’s share beside theirs.
Fiorentina
35%24%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. Fiorentina made 331 this season (41.4 a match); 28% came into the right wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.
Channel
Entries
Per match
Share
League share
Left wing
79
9.9
24%
28%
Left half-space
54
6.8
16%
15%
Centre
46
5.8
14%
13%
Right half-space
59
7.4
18%
16%
Right wing
93
11.6
28%
28%
Build-up2 sections
Build-Up — the pass map
The football question
How does Fiorentina 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.
903build-up passes attempted
78%completed
33%reach the middle third
2%go long into the final third
Pass types
266CB · 38%
59Long Wide · 8%
18Long Central · 3%
289Wide → FB · 41%
73Central · 10%
Sequence success — build-up
39build-up sequences this season
23%succeed — reach the next third or a shot
46%turned over with nothing to show
CB266 · 38%
Long Wide59 · 8%
Long Central18 · 3%
Wide → FB289 · 41%
Central73 · 10%
◆ Vision AI Insight
Fiorentina build predominantly down the right, with Gea as the fulcrum (157 build-up passes). Only 35% 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 (47×).
Pass Explorer
Every pass of Fiorentina’s last 8 matches as an arrow, theirs first and the opponents’ with other team, each side attacking left to right (solid = completed, dashed grey = failed). Eight families per team — click any map to open it wide, then filter by channel or third, from one to another (or click a cell of the flow grids), by outcome, half, minute and passer. Channels: right wing, right half-space, centre, left half-space, left wing.
From channel
To channel
From third
To third
Outcome
Minutes
Channel to channel · click a cell
Third to third · click a cell
Progression4 sections
How They Progress — the mechanism
Not just how many progressive passes, but where they start, who plays them, and whether they actually penetrate. 336 progressive passes across 8 matches (42.0/game).
Origin lane
Right wing
28%
Right half-space
12%
Central
20%
Left half-space
11%
Left wing
29%
Progression is right-dominant: 40% right side · 20% central · 40% left.
Who generates it
David de Gea
41 · 12%
Valde
37 · 11%
Álex Jiménez
36 · 11%
Franco Mastantuono
29 · 9%
Radu Dragusin
26 · 8%
Top two — David de Gea & Valde — account for 23% of all progression.
PROGRESSION
42.0 prog passes/game
mostly right
→
PENETRATION
24% reach final third
20% reach the box
→
THREAT
the other 76% is recycled
progress ≠ danger
What came of it.24% of progressive passes reached the final third and 20% the box; the rest was recycled in front of the block. 23% of the progression ran through two players, mostly down the right side.
Which lanes actually create the threat
Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.
Per lane — volume vs threat
Right wingbalanced
Right half-spacebalanced
Centralbalanced
Left half-spacesterile
Left wingefficient
Progression — the pass map
The football question
Once Fiorentina 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.
1618progression passes attempted
87%completed
16%break into the final third
10%go backward into the defensive third
Pass types
381CB · 27%
38Long Wide · 3%
7Long Central · 0%
785Wide → FB · 56%
197Central · 14%
Sequence success — progression
89progression sequences this season
20%succeed — reach the next third or a shot
36%turned over with nothing to show
CB381 · 27%
Long Wide38 · 3%
Long Central7 · 0%
Wide → FB785 · 56%
Central197 · 14%
◆ Vision AI Insight
Fiorentina progress predominantly down the left, with Fagioli the busiest midfield outlet (227 progression passes). Only 16% of passes that start in midfield actually break the final-third line — the rest (74%) 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 RHS mid → RW mid (86×) — 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)
15%
Progressive
1%
Neutral / sideways
49%
Safe / backward
35%
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.
Where does Fiorentina actually progress the ball with their feet, not a pass?
245 progressive carries this season across the whole squad (26% of 952 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 16m, longest 47m. Most active carrier: Njie (27). Filter to one player below.
First (77)Second (63)Third (54)Fourth (51)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 Fiorentina'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.
123shots
11.1xG
0.09xG per shot
2big chances (0.3+ xG)
8goals
#8key passes / game in the league
#9box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition26% of shots
32
4
2.66
0.08
Cross
2
0
0.15
0.08
Long ball
3
1
0.26
0.09
Pass into the box / short pass
18
3
1.54
0.09
Own creation (carry, dribble, rebound)
9
0
0.71
0.08
Settled attack59% of shots
73
3
7.03
0.10
Cross
9
0
1.08
0.12
Cut-back
8
0
0.96
0.12
Long ball
4
0
0.45
0.11
Pass into the box / short pass
41
2
3.45
0.08
Own creation (carry, dribble, rebound)
11
1
1.08
0.10
Set piece15% of shots
18
1
1.43
0.08
Corner
14
1
1.33
0.10
Free kick
4
0
0.09
0.02
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
Player
Set-ups
xG created
Goals
Alieu Njie
12
1.61
0
Franco Mastantuono
11
0.99
0
Cher Ndour
8
0.90
2
Mateo Pellegrino
11
0.80
0
Álex Jiménez
8
0.63
1
Who takes them
Player
Shots
xG
Goals
Franco Mastantuono
29
2.28
3
Arthur Atta
11
1.24
0
Beto
6
1.20
0
Mateo Pellegrino
9
1.14
2
Alieu Njie
11
1.10
0
Vision AI Model Insight
The biggest source of Fiorentina's chances, by xG, is settled attack (7.0 of 11.1 xG, 73 of 123 shots), mostly pass into the box / short pass. 32 of the 123 shots (26%) came within 15 seconds of winning the ball. 18 of the 123 shots came from set pieces; 8 goals from 11.1 xG (-3.1).
Chance Creation — the pass map
The football question
How does Fiorentina 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
5CB · 6%
6Long Wide · 7%
6Long Central · 7%
38Wide → FB · 43%
33Central · 38%
Sequence success — final-third
44final-third sequences this season
30%succeed — produce a shot
36%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
CB5 · 6%
Long Wide6 · 7%
Long Central6 · 7%
Wide → FB38 · 43%
Central33 · 38%
Who creates — volume × threat
13Mastantuono
11Njie
9Pellegrino
8Jiménez
7Ndour
6Fagioli
5Gudmundsson
88key passes #8 of 20
13.2box entries/game #9 of 20
30.6final-3rd entries/game #11 of 20
1.39xG/game #9 of 20
8goals #13 of 20
-3.1finishing vs xG #17 of 20
◆ Vision AI Insight
Fiorentina lean right — 40% of their key passes come from that flank and its half-space (35 of 88), most often from Mastantuono (10). They funnel chances into the c of the final third, most often via RHS att → C att (14 key passes, most often from Mastantuono). Mastantuono is the primary source overall. They generate 1.39 xG a game and finish it wasteful — they under-perform their xG, led by Franco Mastantuono (3G), Álex Jiménez (2G), Mateo Pellegrino (2G).
Crosses & Cutbacks — squad-wide
The question
How does Fiorentina deliver into the box from wide areas, and what comes of it?
99 crosses: 32 found a team-mate (32%), 9 led to a shot (9%). 27 cut-backs: 15 found a team-mate (56%), 8 led to a shot (30%). A cross starts wide and is aimed into the box; a cut-back starts near the byline and is squared back. Grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball.
Crosses by Territory
The question
Which part of the final third does Fiorentina actually cross from?
99 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. 22% come from one territory, the advanced right wing; 5 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
advanced · right wing
22
22%
1
byline · right wing
22
22%
1
byline · left wing
20
20%
4
advanced · left wing
17
17%
1
deep · right wing
7
7%
0
deep · left wing
6
6%
1
byline · left half-space
3
3%
1
advanced · right half-space
2
2%
0
Finishing3 sections
Shot Map
123 shots for 11.1 xG (1.39/game, #9 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Moderate attack. 15.4 shots/game at 0.090 xG/shot. Box entries 13/game (#9). Threat created 10.3 xT/game (#12).
Goal Sequences
The move behind each of Fiorentina’s 9 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 — 9 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Fiorentina scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
7 · 88%
Set pieces
1 · 12%
Penalties
0 · 0%
By finish
Right foot
2 · 25%
Left foot
5 · 62%
Header
1 · 12%
Vision AI Model Insight
8 goals scored. 88% come in open play; set pieces add 12%. Open play is clearly their main route to goal.
When they lose it1 section
Ball-Loss Map — where attacks die
Every turnover has a location and a cause. This is a rate, not a raw count — the share of pass attempts from each zone that end in a turnover, so a zone they simply play through more often doesn't automatically look riskier. Grey cells are real zones with too few attempts to trust a rate.
Loss rate by zone
How they lose it
Incomplete pass — attacking third
241
Failed forward pass
165
Failed take-on
101
Lost in the defensive third
198
Their weakest zone is the left wing in the defensive third: 36% of 124 pass attempts there are lost (45 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.
How hard does Fiorentina press, where, and does it actually work — beyond a single PPDA number?
A composite Pressing Index built from four event-derived dimensions, each ranked against the league. Not one metric — intensity, height, effectiveness and opponent disruption together. The pitch shows every defensive action (the only five events this data records); the white line is the average height that feeds the score. Toggle by action type below, hover any dot for the player.
38
Pressing Index /100 · passive
Intensity47
PPDA, high-press share, high-zone actions
Height55
how high up the pitch they defend
Effectiveness8
high recoveries & high-regain share
Disruption55
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
19%
RHS
22%
C
24%
LHS
19%
LW
16%
By third (high / mid / low regain)
Def 48%
Mid 38%
Att 14%
Read
Ranked #13 of 20 for press intensity, this is a high press. 52% of defensive actions happen in the middle & attacking thirds, at an average height of 38. Of recoveries, 50% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#13/20
lower = more intense; rank is what matters
Defensive actions / game
143
#16/20
High-press share
22%
#8/20
def actions won high up
Defensive-action height (0–100)
38.3
#9/20
avg pitch height of actions
High recoveries / game
17.8
#20/20
ball won in mid+att third
High-recovery share
50%
#17/20
share of recoveries won high
Opponent completion allowed
85%
#16/20
lower = more disruptive
Opponent progressive allowed
7.6%
#2/20
of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.
How long they keep it — passes and seconds until the ball is won
The question
Once the opponent has the ball, how many passes and how many seconds pass before Fiorentina win it back with a defensive action?
Counted over the 220 opposition possessions that Fiorentina 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 Fiorentina step in. Fiorentina win it after 7.7 opponent passes in the first half-hour and after 5.2 after the hour mark (sooner).
PASSES THEY GET
5.7passes
median 3 · before Fiorentina win it
TIME THEY KEEP IT
16sec
median 8s · 27.5 wins per game
How many passes the opponent got in before the ball was won
42%
25%
12%
20%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
8.1
22s
15–30′
7.4
22s
30–45+′
4.5
13s
45–60′
4.5
13s
60–75′
5.2
15s
75–90+′
5.2
14s
average passesaverage seconds
Attitude in each third
Every other style number here says how much Fiorentina 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 Fiorentina 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) 903 passes
slower, less recycling
Width of use-0.1820.62
Wide-channel share-0.070.30
Side bias-0.020.07
Pass length+0.1023.05
Long-ball share+0.200.25
Forward gain per pass+0.4113.22
Backward-pass share-0.870.16
Deep-pass share+0.350.32
Completion-0.200.78
Seconds between passes+1.124.00
Side used
left 26% · central 48% · right 26%
Progression (middle third) 1,618 passes
nothing unusual in this zone
Width of use-0.0525.46
Wide-channel share-0.180.39
Side bias-0.52-2.00
Pass length-0.8116.09
Long-ball share-0.420.08
Forward gain per pass-0.063.51
Backward-pass share-0.240.32
Deep-pass share-0.160.15
Completion+0.390.87
Seconds between passes-0.163.12
Side used
left 33% · central 30% · right 37%
Final third 903 passes
played inside, narrow, central
Width of use-0.9029.39
Wide-channel share-1.010.50
Side bias-0.10-1.16
Pass length-0.4414.79
Long-ball share-0.500.08
Forward gain per pass+0.261.39
Backward-pass share-0.240.37
Deep-pass share-0.000.09
Completion+0.480.74
Seconds between passes-0.033.38
Side used
left 39% · central 19% · right 42%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Fiorentina'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 Fiorentina win or lose the ball, what actually happens in the seconds after?
Reconstructed from the full timestamped event stream: real possession spells (not zone-clustered), and shots that follow a regain within a fixed window. This phase of play needs ordered, per-event timestamps — which every match here carries.
Direct play share16%
#15 of 20 · reaches final third in ≤3 passes
Patient build-up share30%
#8 of 20 · spells of 6+ passes
Tempo (possession length)19.6s
#14 of 20 · shorter = faster tempo
Passes per possession4.8
#10 of 20
Counter-attack shots /game1.13
#5 of 20 · shot within 12s of a regain in own half
Press→shot /game3.02
#9 of 20 · shot within 8s of a high regain
Speed to final third after regain14.5s
#17 of 20 · lower = faster break
Sequence success — defensive transition
10defensive transition sequences this season
60%succeed — reach the next third or a shot
20%turned over with nothing to show
Vision AI Model Insight
Fiorentina are a patient build-up side: 16% of possessions reach the final third in 3 passes or fewer (#15 of 20), against 30% built patiently over 6+ passes (#8 of 20). Winning the ball back leads to a shot inside 12 seconds 1.13 times a game (#5), and a high regain converts to a shot within 8 seconds 3.02 times a game (#9 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 Fiorentina? 315 opponent progressive passes and 118 shots faced (12.4 xG against) across the season.
Opponent threat by lane (attacking into Fiorentina)
Right wing
33%
Right half-space
15%
Central
18%
Left half-space
9%
Left wing
25%
Where the danger came from. Opponents generated most of their threat through the right wing (33% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Fiorentina actually come from — open play, dead balls, and who supplies them?
Every goal Fiorentina conceded across the loaded matches — the opponent's shots in Fiorentina's own matches — plus every individual opponent key pass faced, each drawn as its own real arrow (not zone-clustered) with the % share of each zone behind it.
Where the goals go in
Every opponent key pass against them (91 total)
By situation
Open play
16 · 84%
Set pieces
2 · 11%
Penalties
1 · 5%
Vision AI Model Insight
19 goals conceded. 84% come in open play; set pieces account for only 11%, so dead-ball defending is not the main issue. 11% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right wing of the attacking third (21% of key passes faced) — that is the zone to shut off.
Context
Shape and tactics
Set pieces, strengths and weaknesses, and who they resemble.
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.
Open play
7 g · 9.7 xG
Set pieces
1 g · 1.4 xG
Penalties
0 g
12% of goals come from set pieces (1 of 8), worth 1.4 xG from 18 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Fiorentina's corners go?
38 corners taken this season, split by which flag they were taken from — arrows from the flag, dots at the delivery point, shaded by % of that side's corners landing in each zone (same treatment as the concede map below). No swing-direction (inswinger/outswinger) data is recorded here, only a start and end point per pass, which cannot show how the ball curved — so this shows what is genuinely knowable: where it lands, and short vs actually delivered. Tap or hover a dot for who took it and the match; filter to one match below and the shading recomputes for just that game.
Right side (20)
Delivered into the box 90%Short 10%
Left side (18)
Delivered into the box 94%Short 6%
Where opponents attack Fiorentina from set pieces
16 shots from opponent corners against Fiorentina, 2 conceded, split by the flag the corner came from — arrows from the flag, dots where the shot was taken (gold = goal), shaded by the % of that flag's shots in each zone. Tap or hover a shot for who took it, the minute and the match; filter to one match and the shading recomputes for just that game.
Right flag (9)
Shot 9Goals 2
Left flag (7)
Shot 7Goals 0
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
shots /game — 15.38 (65th pct)
Weaknesses (bottom-third vs league)
xG conceded /game — 1.55 (25th pct)
pass retention % — 81.05 (25th pct)
progression /game — 42.00 (30th pct)
press intensity (PPDA) — 5.71 (35th pct)
Style Archetype & Similar Teams
Team archetype: Direct / counter high-press. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.
Lecce
80%
Frosinone
77%
Monza
71%
Parma Calcio 1913
68%
Genoa
63%
Performance vs Opponent Styles
The question
Not just how Fiorentina 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 Fiorentina's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (2m)
1.00
2.00
0.00
vs mid-block opponents (2m)
2.00
2.50
1.50
vs low-block opponents (4m)
0.75
2.50
0.25
Behaviour — how Fiorentina actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
79%
16%
34
8.7
8.5
vs mid-block opponents
80%
13%
54
12.5
23.5
vs low-block opponents
82%
11%
40
10.0
10.5
Vision AI Model Insight
Facing a high press, retention drops to 79% vs 82% against a low block (3pt lower under pressure), and directness (long-ball share) sits at 16% when pressed vs 11% 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. Fiorentina are balanced-territory with a aggressive high-press.
Their attack creates 1.39 xG a game and they concede 1.55 a game.
[Event-data based — no tracking, so off-ball structure and marking scheme need video.]
For each of ten match numbers, the one match this season that departed furthest from Fiorentina’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.
Expected goalsat Venezia · 4-2 · 2026-09-112.95avg 1.39
Field tiltat Inter · 1-2 · 2026-10-2518%avg 50%
Final-third entriesat Inter · 1-2 · 2026-10-2520avg 41
PPDAvs Frosinone · 0-3 · 2026-08-293.1avg 5.7
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 Fiorentina’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).
+12.3on-ball value, 8 matches
Where the value came from
Passes3424 actions+3.91
Carries952 actions+1.33
Dribbles175 actions+0.50
Shots123 actions+4.75
Ball wins418 actions+1.86
Most on-ball value (OBV)
Actions
OBV
per 100
Franco Mastantuono
423
+2.30
+0.54
Alieu Njie
229
+1.31
+0.57
Nicolò Fagioli
656
+1.18
+0.18
Mateo Pellegrino
145
+1.04
+0.72
Álex Jiménez
435
+0.97
+0.22
Arthur Atta
273
+0.97
+0.36
Cher Ndour
433
+0.86
+0.20
David de Gea
277
+0.58
+0.21
Biggest single moves
OBV
1 Albert Gudmundsson · pass
+0.465
2 Álex Jiménez · pass
+0.454
3 Marin Pongracic · shot
+0.339
4 Alieu Njie · pass
+0.326
5 Franco Mastantuono · take-on
+0.275
6 Nicolò Fagioli · pass
+0.248
Set Pieces by Player
Who delivers Fiorentina’s dead balls and who finishes them this season. 38 corners taken, most by Franco Mastantuono (11); 18 shots from corners and free kicks, 1 goals, led by Marin Pongracic (1 goals, 0.29 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.
Player
Corners taken
Into the box
Set-piece shots
Goals
xG
Free-kick shots
Penalties
Franco Mastantuono
11
10 (91%)
3
—
0.08
3
—
Nicolò Fagioli
10
7 (70%)
—
—
0.00
—
—
Arthur Atta
1
0 (0%)
2
—
0.46
—
—
Wilfried Gnonto
6
6 (100%)
—
—
0.00
—
—
Pote
3
3 (100%)
1
—
0.02
—
—
Radu Dragusin
—
—
2
—
0.19
—
—
Luca Ranieri
—
—
2
—
0.09
—
—
Marin Pongracic
—
—
2
1
0.29
—
—
Álex Jiménez
2
1 (50%)
1
—
0.03
—
—
Albert Gudmundsson
4
3 (75%)
—
—
0.00
—
—
Christ Inao Oulaï
—
—
1
—
0.02
—
—
Dodô
—
—
1
—
0.01
—
—
Rolando Mandragora
—
—
1
—
0.01
1
—
Mateo Pellegrino
—
—
1
—
0.17
—
—
Top Performers
Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 216 minutes). Coloured chips are that player's strongest capability blocks.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Franco Mastantuono
M
623
1.88
17
6.4
Alieu Njie
F
463
2.14
8
1.7
Álex Jiménez
D
524
1.37
9
7.4
Cher Ndour
M
687
0.92
9
5.1
Nicolò Fagioli
M
668
0.81
10
9.0
Mateo Pellegrino
F
570
1.42
6
1.4
Wilfried Gnonto
M
238
1.13
9
2.9
Valde
D
479
0.94
6
6.5
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.
player
pos
min
crosses (completed)
cutbacks (completed)
Franco Mastantuono
W
623
8 (38%)
6 (67%)
Álex Jiménez
FB
524
4 (25%)
4 (25%)
Valde
FB
479
5 (0%)
3 (33%)
Alieu Njie
W
463
2 (0%)
4 (75%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Radu Dragusin
D
760
149
7
17
24
Cher Ndour
M
687
106
12
7
37
Nicolò Fagioli
M
668
100
16
7
37
Franco Mastantuono
M
623
96
12
6
22
Álex Jiménez
D
524
75
14
2
25
Viery
D
432
71
10
3
14
Mateo Pellegrino
F
570
71
2
0
8
Alieu Njie
F
463
67
6
1
17
Full Squad Data
Every player with 100+ minutes (20 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
David de Gea
G
8
760
0
0.0
1
41
15
8.6
Radu Dragusin
D
8
760
0
0.2
1
26
149
7.4
Cher Ndour
M
8
687
0
0.6
7
10
106
5.1
Nicolò Fagioli
M
8
668
0
0.7
6
25
100
9.0
Franco Mastantuono
M
8
623
3
2.3
13
29
96
6.4
Mateo Pellegrino
F
8
570
2
1.1
9
4
71
1.4
Álex Jiménez
D
7
524
2
0.4
8
36
75
7.4
Valde
D
7
479
0
0.3
5
37
65
6.5
Alieu Njie
F
6
463
0
1.2
11
12
67
1.7
Viery
D
7
432
0
0.0
1
19
71
4.9
Arthur Atta
M
5
341
0
1.2
4
18
27
3.8
Luca Ranieri
D
4
309
0
0.1
1
10
46
2.4
Marco Brescianini
M
6
263
0
0.0
1
6
37
1.3
Wilfried Gnonto
M
6
238
0
0.3
3
13
31
2.9
Marin Pongracic
D
5
221
1
0.3
0
8
42
2.6
Beto
F
6
206
0
1.2
0
1
29
0.3
João Mário
D
4
203
0
0.0
2
18
37
3.9
Christ Inao Oulaï
M
4
169
0
0.1
4
1
31
1.4
Dodô
D
4
161
0
0.0
1
6
15
2.0
Pote
M
5
139
0
0.4
5
7
10
1.4
Player Role Architecture
The question
Who does what — and what tactical job does each key player actually perform?
The nine most-used players (450+ minutes), each with the role their event fingerprint points to — not just their listed position.
David de Gea
Goalkeeper · Goalkeeper
minutes760
goals · xG0 · 0.0
prog passes /904.9
key passes /900.12
def actions /901.8
pass accuracy67%
Radu Dragusin
Stopper / marker · Defender
minutes760
goals · xG0 · 0.2
prog passes /903.1
key passes /900.12
def actions /9017.6
pass accuracy88%
Cher Ndour
Ball-winner / destroyer · Midfielder
minutes687
goals · xG0 · 0.6
prog passes /901.3
key passes /900.92
def actions /9013.9
pass accuracy85%
Nicolò Fagioli
Ball-winner / destroyer · Midfielder
minutes668
goals · xG0 · 0.7
prog passes /903.4
key passes /900.81
def actions /9013.5
pass accuracy84%
Franco Mastantuono
Ball-winner / destroyer · Midfielder
minutes623
goals · xG3 · 2.3
prog passes /904.2
key passes /901.88
def actions /9013.9
pass accuracy78%
Mateo Pellegrino
Ball-winner / destroyer · Midfielder
minutes570
goals · xG2 · 1.1
prog passes /900.6
key passes /901.42
def actions /9011.2
pass accuracy69%
Álex Jiménez
Ball-playing defender · Defender
minutes524
goals · xG2 · 0.4
prog passes /906.2
key passes /901.37
def actions /9012.9
pass accuracy77%
Valde
Ball-playing defender · Defender
minutes479
goals · xG0 · 0.3
prog passes /907.0
key passes /900.94
def actions /9012.2
pass accuracy78%
Alieu Njie
Ball-winner / destroyer · Midfielder
minutes463
goals · xG0 · 1.2
prog passes /902.3
key passes /902.14
def actions /9013.0
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 — bottom-third: xG conceded /game (25th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.55, 25th percentile vs the league).
Need — bottom-third: pass retention % (25th pct)
Sign a secure ball-retaining midfielder. The data flags this because possession is turned over cheaply (81.05, 25th percentile vs the league).
Need — bottom-third: progression /game (30th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (42.00, 30th percentile vs the league).