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Player reportSerie A 2026

Marco Brescianini

Fiorentina
Half-space creator CM
42% of actions in the half-spaces
central midtempo controllerprogressionbox-to-box
263
minutes
6 apps
3
progressive passes
1.0/90
85%
pass completion
78 passes
1
key passes
0.34/90
2
box entries
0.68/90
3
final-3rd entries
1.0/90
6
dribbles
50% won
15
possessions lost
1.61 danger/90
Overview

The player

Who he is and how he compares with his peers.

Thin sample this season. Marco Brescianini has played 6 matches (263 min) so far, so sections that need a bigger sample to say anything reliable are not shown here — they are missing on purpose, not broken. See all seasons combined →
01

What Patterns Define Him?

His repeatable signature. A step only appears if its reliability score (sample size × match coverage) reaches at least Medium confidence — pattern mining, not anecdotes.

RECEIVE
Left Half-Space, Attacking third — mostly in the middle third (53% of his 78 passes)
85% completion · 78× in 6/6 matches
↓
PROGRESS
drive or pass into the final third
1.0 prog/90 · 3× in 2/6 matches
Signature: Receive → Progress — the only steps proven repeatable this season (2 of 4 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: arrive — 2× (low confidence, shown as a number only, no tactical conclusion drawn); create / finish — 2× (low confidence, shown as a number only, no tactical conclusion drawn) — omitted from the signature rather than presented as one.
In possession

In possession

What he does with the ball: build-up, progression, creation, carrying and finishing.

05

How dangerous are his carries?

Real ball-carries

26 tracked carries (8.9/90, 6 progressive, 264m total) — the ball moving with his touches, a different signal from dribbles below (beating an opponent 1v1). this counts every touch-carry, not just his dribble attempts below — a fuller picture of how much of his ball-carrying is control-and-move rather than beating a man.

4%4%15%8%4%4%4%19%27%8%4%
progressivelateral/short% of his 26 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 8m, longest 26m
By zone — where the carry started → where it ended
2Outside → Inside
18Inside → Inside
3Outside → Outside
3Inside → Outside
First (24)Second (2)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →

Dribbles (1v1s)

Only 6 dribbles attempted this season — too little volume to map a location pattern.

02

How does he create chances?

1 key passes (0.34/90), 0 of them assists — where his chance creation specifically comes from, 18 zones (6×3), showing his share of key passes originating there.

Chance creation — key pass origin zone share
Filter:
100%
chance creation (1)assist (0)% of the selected group's key passes originating in each zone
07

Where does he become vulnerable?

15 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.

6
attacking third (cheap)
5
middle third
4
own third (dangerous)
Vision AI 40% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 1.61 danger-index/90 · 0.313 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
03

Tactical patterns — how his football actually looks

Three clustered sequence diagrams from his own event data — his three busiest routes: the way he progresses, the pattern behind his chances, and where a turnover turns dangerous.

own goal left, attacking →
Where do his chances come from?
Of 1 key passes, his busiest route is a delivery where he plays inside from the left hs toward the central in the final third — 1 times. The receiver isn't identifiable in this data, only where the pass started and ended.
Where does he lose the ball most?
This is a RATE, not a raw count — the share of his touches in each zone that end in a turnover, so a zone he simply plays in more often doesn't automatically look riskier. His weakest zone is the left half-space in the final third: 17% of his 12 touches there are lost (2 times).
—0 touches · too few—3 touches · too few—4 touches · too few—3 touches · too few—4 touches · too few—1 touch · too few—1 touch · too few8%1/12 lost15%2/13 lost14%2/14 lost—2 touches · too few—0 touches · too few—1 touch · too few17%2/12 lost12%1/8 lostRWRHSCLHSLWDEFMIDATT
04

Does he carry inside or outside — his ball-carries across the pitch

Four arrows, one per movement class of his ball-carries: outside→inside (cutting in with the ball), inside→outside (carrying wide), outside→outside (down the touchline) and inside→inside (through the middle). Each count is measured from the carry's real start and end coordinates.

own goal left, attacking →
Across 26 ball-carries, his dominant tendency is that he carries through central areas (69%). He carries from outside into the middle 2 times and out toward the touchline 3 — a width-holder who drives down the line.
06

What happens right after he carries the ball

Every carry's end point matched against his own very next pass or shot in the same match, when one starts almost exactly there — the direct continuation of that touch, not a separate stat. “No clean link” means no pass or shot of his own started close enough to count (often the carry ended in a tackle or a loss); it isn't a claim about exactly what happened, only that nothing traceable followed.

Shot
1 · 4%
Progressive / key pass
0 · 0%
Simple pass
21 · 81%
No clean link
4 · 15%
Of 26 carries, 4% flow straight into a shot of his own, 0% into a key or progressive pass — a genuine end product to the carry, not just ball retention. 15% have no clean link to a next touch of his own close to where the carry ended.
Out of possession

Out of possession

Where and how he defends and presses.

09

How & where does he defend?

37 defensive actions across the season (12.7/90). Where he wins the ball, and how — the core question for a defender. Aerial duels are not recorded for this competition, so aerial dominance is not measured here.

click a card to isolate that action type · own goal left, attacking →
4
tackles · 25% won
5
interceptions · 1.7/90
9
recoveries · 3.1/90
6
clearances · 2.1/90
2
blocks
31
avg action height
1
won high (att 3rd)
14
middle third
22
own third
Vision AI A deep-defending defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 18 proactive ball-wins (6.2/90), tackle success 25%. He defends mostly around the middle third.
08

Against Different Pressing Intensities

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Marco Brescianini keep producing when the game is tight and the press is high? Tiers of ~2-2 matches — directional evidence, not proof.

press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 3.4, 2m)
0.10
0.0
0.00
0%
Mid press (PPDA 3.9, 2m)
1.86
2.9
0.00
100%
Low press (PPDA 4.4, 2m)
0.53
2.1
1.03
100%
Team

Team context

How much of the team runs through him, and what changes without him.

10

Impact on the Team

Fiorentina's output per match with Marco Brescianini (6 matches) versus without him (2 matches). Insufficient evidence — the without-sample is only 2 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.

WITH (6)
WITHOUT (2)
Δ
goals for /match
1.17
1.00
+0.17
xG for /match
1.47
1.15
+0.32
goals against /match
2.67
1.50
+1.17
points /match
0.50
0.50
+0.00
11

His Share of the Team

Of everything Fiorentina produced this season, the categories where the biggest share ran through Marco Brescianini specifically — his share of the team total, not a per-90 rate.

category
share
him / team
clearances
3%
31 / 973
ball recoveries
3%
56 / 1758
final-third entries
3%
56 / 1869
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

12

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 382 central mids in the pool (min 450 min). This is what separates players who post similar numbers but play differently. Proxy dimensions are inferred from on-ball data; true off-ball running / under-pressure context is not measured.

Tempo controller54%Deep-lying playmaker48%Transition runner42%Box-to-box runner33%
Why Tempo controller 54%: a weighted blend of retention 61 (weight 35%) + press resistance 68 (weight 20%) + build-up 45 (weight 30%) + progression 29 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
—
Strong
dribbling
Average
press resistance, carrying, retention, box threat, territory (wide vs central), transition, build-up, passing directness, crossing
Weak
final-third threat, progression, defensive aggression, ball-winning, receiving zones, creativity, through-balls, line-breaking
Unknown
aerial ability, marking, off-ball running — not in event data
Dribbling
72
Press resistance ~proxy
68
Carrying
62
Retention
61
Box threat
59
Territory (wide vs central)
58
Transition ~proxy
51
Build-up
45
Passing directness
44
Crossing
42
Final-third threat
30
Progression
29
Defensive aggression
26
Ball-winning
26
Receiving zones
21
Creativity
17
Through-balls ~proxy
15
Line-breaking
7
13

Similar Players — in style space

Closest comparables measured on the style scores above, within the same position family — so it separates how players are alike, not just how much they touch the ball. Each line explains the shared strength and the divergent mechanism. A light physical-profile term (height / weight; this player: 188 cm / 80 kg) is included at a quarter of one style axis's weight — enough to break ties between stylistic twins, not to override style. Scope: pooled across the Serie A, Bundesliga, La Liga, Ligue 1 and Premier League, percentiled within each player's own league before comparing — a match from another league is marked with its league name.

Style, not quality: a high match here means two players tend to produce the ball in similar ways — it is not a ranking, a scouting recommendation, or a claim that they are equally good.

Alex Král Union Berlin · Bundesliga 25/26 · 187 cm / 80 kg
79%
Driven by: line-breaking (17%), creativity (15%), through-balls (14%). Different mechanism — Brescianini more via build-up, box threat; Král more via ball-winning, dribbling.
Lucas Bergvall Tottenham · Premier League · 187 cm / 75 kg
78%
Driven by: creativity (22%), line-breaking (14%), receiving zones (12%). Different mechanism — Brescianini more via retention, build-up; Bergvall more via defensive aggression, dribbling.
Isak Vural Pisa 25/26 · 175 cm
76%
Driven by: creativity (21%), line-breaking (14%), ball-winning (13%). Different mechanism — Brescianini more via passing directness, territory (wide vs central).
Archie Gray Tottenham · Premier League · 187 cm / 70 kg
75%
Driven by: defensive aggression (18%), creativity (18%), line-breaking (16%). Different mechanism — Brescianini more via box threat, carrying; Gray more via passing directness, territory (wide vs central).
Noah Sadiki Sunderland · Premier League · 173 cm / 74 kg
72%
Driven by: creativity (16%), line-breaking (14%), defensive aggression (10%). Different mechanism — Brescianini more via box threat, passing directness; Sadiki more via through-balls.
Patrick Osterhage Freiburg · Bundesliga · 187 cm / 80 kg
72%
Driven by: creativity (21%), line-breaking (17%), through-balls (11%). Different mechanism — Brescianini more via dribbling, territory (wide vs central); Osterhage more via build-up.
14

Summary

Marco Brescianini is a tempo controller: 1.0 progressive passes, 0.34 key passes /90, 2 box entries, 0 goals from 0.03 xG. A box-to-box contributor across every phase.

Based on 6 matches (263 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a tempo controller — best used in a system built around that identity. His biggest room for growth is progression — even a modest improvement there would meaningfully lift his overall tempo controller profile.
✨ This report is interactive

Click any stat card to filter its map, hover a dot for the exact match, and use the dropdowns to slice passes zone-to-zone. Nothing here is static.

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