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.
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.
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
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:
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).
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.
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.
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 / 1868
Recruitment
Style and verdict
Style profile, closest comparables, and the summary.
Not raw event counts — football style scores: weighted models scored 0–100 against the 383 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 controller53%Deep-lying playmaker47%Transition runner41%Box-to-box runner33%
Why Tempo controller 53%: a weighted blend of retention 60 (weight 35%) + press resistance 68 (weight 20%) + build-up 44 (weight 30%) + progression 28 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
aerial ability, marking, off-ball running — not in event data
Dribbling
73
Press resistance ~proxy
68
Carrying
62
Retention
60
Box threat
60
Territory (wide vs central)
58
Transition ~proxy
50
Build-up
44
Passing directness
42
Crossing
41
Final-third threat
30
Progression
28
Defensive aggression
25
Ball-winning
25
Receiving zones
21
Creativity
17
Through-balls ~proxy
14
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, defensive aggression.
Lucas Bergvall Tottenham · Premier League · 187 cm / 75 kg
78%
Driven by: creativity (21%), 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 (20%), ball-winning (14%), line-breaking (14%). 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 (19%), creativity (17%), 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 (11%). Different mechanism — Brescianini more via box threat, passing directness; Sadiki more via through-balls.
Marco Palestra Chelsea · Premier League · 186 cm / 80 kg
72%
Driven by: creativity (17%), defensive aggression (16%), receiving zones (14%). Different mechanism — Brescianini more via box threat, passing directness; Palestra more via territory (wide vs central), through-balls.
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.