Thin sample this season. Frenkie de Jong has played 1 match (24 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, Middle third — mostly in the middle third (53% of his 19 passes)
89% completion · 19× in 1/1 matches
Signature: Only Receive shows a proven, repeatable pattern this season — too little evidence yet (1 match loaded) for a fuller signature chain.
Not a pattern: progress — 0× (insufficient confidence, hidden — not enough evidence yet); arrive — 0× (insufficient confidence, hidden — not enough evidence yet); create / finish — 1× (insufficient confidence, hidden — not enough evidence yet) — omitted from the signature rather than presented as one.
Team
Team context
How much of the team runs through him, and what changes without him.
Barcelona's output per match with Frenkie de Jong (1 matches) versus without him (9 matches). Insufficient evidence — the without-sample is only 9 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.
WITH (1)
WITHOUT (9)
Δ
goals for /match
1.00
4.33
-3.33
xG for /match
1.48
0.24
+1.24
goals against /match
2.00
1.00
+1.00
points /match
0.00
3.00
-3.00
03
His Share of the Team
Of everything Barcelona produced this season, the categories where the biggest share ran through Frenkie de Jong specifically — his share of the team total, not a per-90 rate.
category
share
him / team
final-third entries
7%
220 / 3033
half-space entries
6%
140 / 2302
expected assists (xA)
6%
2.0 / 35.0
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 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 controller85%Deep-lying playmaker83%Advanced playmaker (8)81%Box-to-box runner80%
Why Tempo controller 85%: a weighted blend of retention 98 (weight 35%) + build-up 68 (weight 30%) + press resistance 77 (weight 20%) + progression 78 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
box threat, through-balls, territory (wide vs central)
Unknown
aerial ability, marking, off-ball running — not in event data
Retention
98
Receiving zones
95
Passing directness
92
Creativity
88
Final-third threat
87
Transition ~proxy
87
Carrying
83
Progression
78
Ball-winning
78
Press resistance ~proxy
77
Build-up
68
Defensive aggression
66
Line-breaking
63
Crossing
58
Dribbling
44
Box threat
35
Through-balls ~proxy
29
Territory (wide vs central)
16
05
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: 181 cm / 74 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 La Liga, Bundesliga, Ligue 1, Premier League and Serie A, 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.
Aleksandar Pavlovic Bayern · Bundesliga · 188 cm / 78 kg
90%
Driven by: retention (15%), receiving zones (14%), transition (14%). Different mechanism — Jong more via passing directness, creativity; Pavlovic more via line-breaking.
Luka Modric AC Milan · Serie A · 172 cm / 66 kg
85%
Driven by: transition (15%), receiving zones (10%), creativity (9%). Different mechanism — Jong more via retention; Modric more via through-balls, line-breaking.
Pedri Barcelona · 174 cm / 68 kg
85%
Driven by: transition (12%), retention (12%), creativity (11%). Different mechanism — Jong more via passing directness; Pedri more via through-balls, dribbling.
Sandro Tonali Tottenham · Premier League · 181 cm / 79 kg
85%
Driven by: transition (17%), creativity (14%), passing directness (12%). Different mechanism — Jong more via retention, receiving zones; Tonali more via through-balls.
Angelo Stiller Stuttgart · Bundesliga · 183 cm / 77 kg
85%
Driven by: transition (13%), creativity (11%), receiving zones (11%). Different mechanism — Jong more via ball-winning; Stiller more via through-balls, line-breaking.
Vitinha PSG · Ligue 1 · 172 cm / 64 kg
83%
Driven by: transition (15%), retention (14%), receiving zones (11%). Different mechanism — Jong more via defensive aggression, ball-winning; Vitinha more via through-balls, line-breaking.
06
Summary
Frenkie de Jong is a tempo controller / deep-lying playmaker: 0.0 progressive passes, 0.00 key passes /90, 0 box entries, 0 goals from 0.10 xG. A box-to-box contributor across every phase.
Based on 1 matches (24 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a tempo controller / deep-lying playmaker — 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 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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