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 Wing, Middle third — wide or inverted — mostly in the middle third (46% of his 41 passes)
88% completion · 41× in 1/1 matches
↓
PROGRESS
carry or combine up the flank
2.3 prog/90 · 2× in 1/1 matches
↓
DRIBBLE
beat his man up the line
100% won · 1× in 1/1 matches
↓
DELIVER
cross or cut-back into the box
1 key passes · 1× in 1/1 matches
↓
DEFEND
1v1 and cover on his side
12 def actions · lost 40% deep · 12× in 1/1 matches
Signature: receive wide/inverted → progress the flank → deliver into the box → recover to defend 1v1. Attack the space behind him in transition.
In possession
In possession
What he does with the ball: build-up, progression, creation, carrying and finishing.
1 key passes (1.17/90), 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
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 wing toward the left hs 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 wing in the final third: 13% of his 15 touches there are lost (2 times).
Team
Team context
How much of the team runs through him, and what changes without him.
Fiorentina's output per match with Valde (1 matches) versus without him (37 matches). Insufficient evidence — the without-sample is only 37 matches; treat every Δ below as noise until more games exist. What his own defending should move — goals conceded and results — leads; attacking output (largely out of a defender's hands) is shown after, for context. A proper on-off model needs many more minutes.
WITH (1)
WITHOUT (37)
Δ
goals against /match
1.00
0.92
+0.08
points /match
3.00
2.24
+0.76
goals for /match
2.00
2.03
-0.03
xG for /match
1.55
0.00
+1.55
05
His Share of the Team
Of everything Fiorentina produced this season, the categories where the biggest share ran through Valde specifically — his share of the team total, not a per-90 rate.
category
share
him / team
clearances
3%
15 / 585
progressive passes
2%
41 / 1790
tackles
2%
10 / 501
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 232 full-backs 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.
Inverted full-back38%Overlapping full-back27%
Why Inverted full-back 38%: a weighted blend of progression 63 (weight 25%) + retention 43 (weight 30%) + build-up 32 (weight 35%) + press resistance 40 (weight 10%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
through-balls, territory (wide vs central), build-up, ball-winning, crossing
Unknown
aerial ability, marking, off-ball running — not in event data
Receiving zones
92
Line-breaking
72
Creativity
64
Carrying
63
Progression
63
Passing directness
62
Box threat
49
Transition ~proxy
48
Dribbling
44
Retention
43
Defensive aggression
42
Final-third threat
41
Press resistance ~proxy
40
Through-balls ~proxy
34
Territory (wide vs central)
34
Build-up
32
Ball-winning
21
Crossing
11
07
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 / 75 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.
Hugo Rincón Athletic Club · La Liga · 183 cm / 75 kg
53%
Driven by: receiving zones (24%), ball-winning (23%), line-breaking (11%). Different mechanism — Valde more via passing directness; Rincón more via crossing, territory (wide vs central).
Yukinari Sugawara Cagliari · 179 cm / 71 kg
53%
Driven by: ball-winning (29%), receiving zones (20%), line-breaking (10%). Different mechanism — Valde more via defensive aggression, carrying; Sugawara more via territory (wide vs central), crossing.
Djibril Sidibé Le Mans · Ligue 1 · 182 cm / 71 kg
44%
Driven by: crossing (23%), receiving zones (19%), creativity (14%). Different mechanism — Valde more via carrying, receiving zones; Sidibé more via through-balls, passing directness.
Abner Vinícius Lyon · Ligue 1 · 182 cm / 75 kg
43%
Driven by: ball-winning (40%), receiving zones (21%). Different mechanism — Valde more via carrying; Vinícius more via crossing, final-third threat.
Caio Henrique Monaco · Ligue 1 25/26 · 178 cm / 68 kg
43%
Driven by: ball-winning (26%), receiving zones (21%), line-breaking (10%). Different mechanism — Valde more via box threat; Henrique more via through-balls, crossing.
Jarell Quansah Leverkusen · Bundesliga · 190 cm / 83 kg
38%
Driven by: ball-winning (22%), crossing (22%), receiving zones (20%). Different mechanism — Valde more via territory (wide vs central), line-breaking; Quansah more via build-up, retention.
08
Summary
Valde is an inverted full-back: 2.3 progressive passes and 1 box entries, delivering 1 key passes. Inverted full-back. [1v1 recovery pace and off-ball overlap timing need tracking.]
Based on 1 matches (77 minutes) — an early read, treat with caution until more minutes are logged. He profiles as an inverted full-back — best used in a system built around that identity.
His biggest room for growth is build-up — even a modest improvement there would meaningfully lift his overall inverted full-back 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.
