العربيةSeason2025/262026 · this seasonAll seasons
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Player reportPremier League 2026

Joelinton

Newcastle
Half-space creator CM
43% of actions in the half-spaces
central midtransition runnerprogressionbox-to-box
209
minutes
3 apps
4
progressive passes
1.7/90
82%
pass completion
92 passes
2
key passes
0.86/90
0
box entries
0.00/90
10
final-3rd entries
4.3/90
7
dribbles
86% won
18
possessions lost
2.33 danger/90
Overview

The player

Who he is and how he compares with his peers.

Thin sample this season. Joelinton has played 3 matches (209 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 (65% of his 92 passes)
82% completion · 92× in 3/3 matches
↓
PROGRESS
drive or pass into the final third
1.7 prog/90 · 4× in 2/3 matches
↓
CREATE / FINISH
cut-back or shot from inside
0.86 key passes /90 · 0 goals · 4× in 2/3 matches
Signature: Receive → Progress → Create / Finish — the only steps proven repeatable this season (3 of 4 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: arrive — 0× (insufficient confidence, hidden — not enough evidence yet) — 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.

04

How dangerous are his carries?

Real ball-carries

12 tracked carries (5.2/90, 1 progressive, 87m 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.

25%8%17%17%17%17%
progressivelateral/short% of his 12 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 6m, longest 16m
By zone — where the carry started → where it ended
1Outside → Inside
8Inside → Inside
3Outside → Outside
First (12)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →

Dribbles (1v1s)

Only 7 dribbles attempted this season — too little volume to map a location pattern.

02

How does he create chances?

2 key passes (0.86/90), 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:
50%50%
chance creation (2)assist (0)% of the selected group's key passes originating in each zone
05

Where does he become vulnerable?

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

5
attacking third (cheap)
12
middle third
1
own third (dangerous)
Vision AI 28% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 2.33 danger-index/90 · 0.301 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 2 key passes, his busiest route is a delivery where he plays straight through the right 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 middle third: 36% of his 11 touches there are lost (4 times).
—0 touches · too few—0 touches · too few—3 touches · too few—1 touch · too few—2 touches · too few—6 touches · too few10%1/10 lost8%1/13 lost20%4/20 lost36%4/11 lost—3 touches · too few—4 touches · too few—6 touches · too few—7 touches · too few—6 touches · too fewRWRHSCLHSLWDEFMIDATT
Out of possession

Out of possession

Where and how he defends and presses.

06

How & where does he defend?

44 defensive actions across the season (18.9/90). 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 →
3
tackles · 67% won
3
interceptions · 1.3/90
9
recoveries · 3.9/90
4
clearances · 1.7/90
1
blocks
48
avg action height
7
won high (att 3rd)
27
middle third
10
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 15 proactive ball-wins (6.5/90), tackle success 67%. He defends high, stepping out to intercept — suits a high line.
Team

Team context

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

07

Impact on the Team

Newcastle's output per match with Joelinton (3 matches) versus without him (5 matches). Insufficient evidence — the without-sample is only 5 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.

WITH (3)
WITHOUT (5)
Δ
goals for /match
1.00
1.80
-0.80
xG for /match
1.28
0.00
+1.28
goals against /match
1.67
1.80
-0.13
points /match
1.00
1.60
-0.60
08

His Share of the Team

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

category
share
him / team
interceptions
11%
33 / 304
ball recoveries
8%
129 / 1639
tackles
8%
46 / 594
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

09

Playing-Style Profile

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.

Transition runner58%Tempo controller56%Box-to-box runner48%Deep-lying playmaker47%
Why Transition runner 58%: a weighted blend of defensive aggression 72 (weight 30%) + transition 47 (weight 45%) + box threat 53 (weight 25%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
—
Strong
dribbling, ball-winning, press resistance, defensive aggression
Average
retention, receiving zones, passing directness, creativity, box threat, build-up, transition, crossing, territory (wide vs central)
Weak
final-third threat, carrying, line-breaking, progression, through-balls
Unknown
aerial ability, marking, off-ball running — not in event data
Dribbling
81
Ball-winning
75
Press resistance ~proxy
73
Defensive aggression
72
Retention
63
Receiving zones
61
Passing directness
55
Creativity
53
Box threat
53
Build-up
52
Transition ~proxy
47
Crossing
44
Territory (wide vs central)
42
Final-third threat
28
Carrying
24
Line-breaking
20
Progression
12
Through-balls ~proxy
8
10

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: 186 cm / 81 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 Premier League, Bundesliga, La Liga, Ligue 1 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.

Nelson Deossa Real Betis · La Liga · 185 cm / 71 kg
76%
Driven by: through-balls (17%), dribbling (17%), press resistance (14%). Different mechanism — Joelinton more via passing directness, build-up; Deossa more via carrying, box threat.
Gvidas Gineitis Torino · Serie A · 187 cm / 79 kg
75%
Driven by: progression (16%), through-balls (15%), defensive aggression (15%). Different mechanism — Joelinton more via retention, press resistance.
Mohamed Kaba Lecce · Serie A · 185 cm / 71 kg
74%
Driven by: ball-winning (18%), defensive aggression (16%), progression (15%). Different mechanism — Joelinton more via receiving zones, retention; Kaba more via passing directness, defensive aggression.
Quinten Timber Crystal Palace · Ligue 1 · 179 cm / 74 kg
71%
Driven by: through-balls (20%), dribbling (15%), line-breaking (13%). Different mechanism — Joelinton more via ball-winning; Timber more via carrying, progression.
Mandela Keita Parma Calcio 1913 · Serie A · 180 cm / 78 kg
71%
Driven by: through-balls (16%), progression (15%), ball-winning (14%). Different mechanism — Joelinton more via box threat, receiving zones; Keita more via carrying, build-up.
Lassana Coulibaly Lecce · Serie A · 183 cm / 77 kg
66%
Driven by: progression (22%), through-balls (17%), line-breaking (13%). Different mechanism — Joelinton more via receiving zones, creativity.
11

Summary

Joelinton is a transition runner / tempo controller: 1.7 progressive passes, 0.86 key passes /90, 0 box entries, 0 goals from 0.13 xG. A box-to-box contributor across every phase.

Based on 3 matches (209 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a transition runner / tempo controller — best used in a system built around that identity. His biggest room for growth is transition — even a modest improvement there would meaningfully lift his overall transition runner 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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