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Player reportPremier League 2026

Amar Dedic

Newcastle
Defensive full-back FB
15.7 defensive actions/90 · low final-third share 25%
Capability Analysis
Ball-Winning51%vs 21 full-backs
"How actively does he win the ball back?"
Interceptions /900.5714%
Ball recoveries /904.7386%
Tackles /901.5138%
Duels won /901.3267%
Breaking Pressure
only 88 pressured-passing actions across 3 high-press matches -- not enough sample (needs 5+ matches and 12+ actions)
Wide Delivery2%vs 21 full-backs
"Does he create danger from wide areas -- crosses and cutbacks?"
Crosses /900.00%
Cross accuracy: 0.0%
Cutbacks /900.765%
Ball-Carrying48%vs 21 full-backs
"Does he advance the ball himself when the pass isn't on?"
Progressive carries /903.5952%
Carry distance /9078.01m43%
full-backoverlapping full-backprogressioncrossing
476
minutes
6 apps
79%
pass completion
215 passes
12
progressive passes
2.3/90
6
final-3rd entries
1.1/90
6
box entries
1.13/90
83
defensive actions
15.7/90
11
tackles + interceptions
38% tackle win
11
dribbles
36% won
Overview

The player

Who he is and how he compares with his peers.

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
Right Wing, Middle third — wide or inverted — mostly in the middle third (54% of his 215 passes)
79% completion · 215× in 6/6 matches
↓
PROGRESS
carry or combine up the flank
2.3 prog/90 · 12× in 5/6 matches
↓
DRIBBLE
beat his man up the line
36% won · 11× in 4/6 matches
↓
DELIVER
cross or cut-back into the box
4 key passes · 6× in 4/6 matches
↓
DEFEND
1v1 and cover on his side
83 def actions · lost 19% deep · 83× in 6/6 matches
Signature: receive wide/inverted → progress the flank → deliver into the box → recover to defend 1v1. Attack the space behind him in transition.
15

Where is he influential — vs where is he merely present?

Red fill = raw touch territory. Gold rings = zones where his influence (xT added, progression, line-breaks, key passes) outweighs how often he's actually there — one combined map instead of two separate maps to compare by eye. Red with no ring: present but not dangerous. A ring on faint red: rare touches, outsized impact.

own goal left, attacking →
36
passes / match
15.7
def actions / 90
22–49
pass range (matches)
17
clearances
Pass range = his fewest and most passes in any single match this season (22 at the low end, 49 at the high) — a measure of match-to-match involvement, not pass distance.
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

38 tracked carries (7.2/90, 15 progressive, 413m total) — the ball moving with his touches, a different signal from dribbles below (beating an opponent 1v1). even a player who rarely dribbles past a man can still carry the ball forward constantly in build-up; this is that.

24%26%26%11%8%3%3%
progressivelateral/short% of his 38 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 10m, longest 26m
By zone — where the carry started → where it ended
9Outside → Inside
8Inside → Inside
19Outside → Outside
2Inside → Outside
First (19)Second (18)Third (1)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →

Beaten in the tackle

How often an attacker gets past him in a 1v1 defensive duel — the closest signal the data has to "dribbled past" (no attacker-beat-defender field exists directly, so this counts tackles he attempted and lost).

8
tackle duels
3
won
5
beaten · 62%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 38%
OUTSIDE 62%
Tackle-duel location — 3 inside · 5 outside
Right Wing
5 · 62%
Right Half-Space
3 · 38%
Central
0 · 0%
Left Half-Space
0 · 0%
Left Wing
0 · 0%
Vision AI beaten in 5 of 8 tackle duels (62% loss rate) — a real defensive leak worth flagging.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →

Dribbles (1v1s)

Does he carry outside (overlap) or inside (invert into midfield)? Every carry by channel. Season rate: 2.08 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 0%
OUTSIDE 100%
Dribble location — 0 inside · 11 outside
Right Wing
10 · 91%
Right Half-Space
0 · 0%
Central
0 · 0%
Left Half-Space
0 · 0%
Left Wing
1 · 9%
Vision AI 100% of his carries are wide — an overlapping full-back who hugs the touchline.
07

How does he build & move the ball?

How does he escape the first line?

6%
vertical passes
6×
1%
switches
1×
20%
carries
19×
73%
short circulation
70×
Answer: he escapes the press primarily through carrying — stepping out with the ball; he almost never carries (19×), so pressing his passing lanes beats pressing him.

How he moves the ball — his 4 busiest progression routes, not where every pass starts and ends separately. Arrow width = how often, colour = xT gained, dashed = switch of play. The full breakdown is in the lane matrix below.

own goal left, attacking →
Lane transition matrix — when he receives in a lane, where does it go?
TO →RWRHSCLHSLWRW11853%6338%457%81%11%1RHS3432%1132%1132%113%1C128%117%233%442%5LHS425%125%125%125%1LW250%150%1FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: the right wing in the middle third → the right half-space in the middle third — 4 progressive passes (22% of his progression) at 0.009 xT each. He moves it inside.

His progression is inward: 72% of progressive passes move the ball toward the middle versus 0% going wider — he cuts in rather than holding width.

Only 4% of his passes switch play, so his threat is same-side — contain the flank he occupies and the route closes.

Quality behind the volume: 6 line-breaking passes and 6 final-third entries, 1.5 total xT added.

Origin and destination are measured on the same event row — no receiver inference. Receiver identity is not recoverable from this data source.
All passes — origin zone share
Filter: from to
3%16%28%19%18%5%0%1%4%1%1%0%1%1%
completedincomplete215 passes · any zone → any zone · own goal left, attacking →
215
passes
79%
completed
45
lost
Vision AIIn line with his 79% season completion rate.
06

How does he create chances?

4 key passes (0.76/90), 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 (4)assist (0)% of the selected group's key passes originating in each zone
08

Where does he become vulnerable?

52 times he gave the ball away. For a defender the danger is where — a loss in his own third can turn into a chance against; higher up it costs little.

14
attacking third (cheap)
28
middle third
10
own third (dangerous)
Vision AI 27% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 3.50 danger-index/90 · 0.356 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
09

What is his passing profile?

215
passes attempted
40%
mostly forward
50%
mostly short
Direction
Forward
85 · 40%
Sideways
52 · 24%
Backward
78 · 36%
Length (completed)
Short (<15m)
85 · 50%
Medium
77 · 45%
Long (>30m)
8 · 5%
03

Where Does He Receive?

The zones where Amar Dedic gets on the ball — his top three ball-collection areas highlighted (gold = primary). Reception is proxied by where his on-ball actions begin (no explicit receiver is recorded).

123
1 = primary, 2 = secondary, 3 = third · own goal left, attacking →
His collection zones
38%
Primary
Right Wing, Middle third
16%
Secondary
Right Wing, Attacking third
15%
Third
Right Wing, Defensive third
These are the zones where he collected the ball most.
04

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Amar Dedic actually gets on the ball. Hover any zone for its breakdown by action type, its share of all touches, and the exact coordinate range it covers.

Filter:
122113934173865414012
own goal left, attacking → · brighter + higher number = more touches

Passes only — completed vs incomplete, by zone

Same zone grid, restricted to passes so completed/incomplete and match filters actually mean something — a shot or a dribble has no "completed" in the pass sense.

3%16%28%19%18%5%0%1%4%1%1%0%1%1%
own goal left, attacking →
10

Every Pass This Season — completed vs incomplete

Every pass this season, plotted individually — green = completed, grey (dashed) = incomplete, gold = key pass. Filter by outcome or isolate one match below.

4Key pass
4Cross
1Cutback
12Progressive
25Long ball
5Switch
By zone — where the pass started → where it landed
55Outside → Inside
37Inside → Inside
65Outside → Outside
13Inside → Outside
By direction
85Forward
78Backward
52Sideways
own goal left, attacking →
02

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 →
How does he progress the ball forward?
His most common route for progressing play: he plays straight through the right wing, advancing it forward in the middle third — 2 passes worth 0.38 xT.
Where do his chances come from?
Of 4 key passes, his busiest route is a delivery where he plays inside from the right hs toward the central in the final third — 2 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 right half-space in the final third: 36% of his 14 touches there are lost (5 times).
16%5/32 lost30%3/10 lost—3 touches · too few—1 touch · too few—0 touches · too few22%18/80 lost25%6/24 lost11%1/9 lost—2 touches · too few—1 touch · too few17%6/35 lost36%5/14 lost—2 touches · too few—1 touch · too few—1 touch · too fewRWRHSCLHSLWDEFMIDATT
Out of possession

Out of possession

Where and how he defends and presses.

11

How & where does he defend?

83 defensive actions across the season (15.7/90). 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 →
8
tackles · 38% won
3
interceptions · 0.6/90
25
recoveries · 4.7/90
17
clearances · 3.2/90
5
blocks
30
avg action height
4
won high (att 3rd)
32
middle third
47
own third
Vision AI A deep-defending defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 36 proactive ball-wins (6.8/90), tackle success 38%. He defends mostly around the middle third.
12

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Amar Dedic still play out when the opponent presses high? His build-up quality split by press intensity — the key question for a ball-playing defender. Tiers of ~2-2 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 3.3, 2m)
73%
1.9
5.1
0.67
Mid press (PPDA 3.9, 2m)
79%
4.1
5.3
0.79
Low press (PPDA 6.0, 2m)
89%
0.7
3.5
1.00
Team

Team context

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

13

Impact on the Team

Newcastle's output per match with Amar Dedic (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. 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 (6)
WITHOUT (2)
Δ
goals against /match
2.00
1.00
+1.00
points /match
1.33
1.50
-0.17
goals for /match
1.67
1.00
+0.67
xG for /match
1.04
0.57
+0.47
14

His Share of the Team

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

category
share
him / team
ball recoveries
1%
25 / 1785
clearances
1%
17 / 1220
box entries
1%
8 / 580
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

16

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 233 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.

Overlapping full-back57%Inverted full-back39%
Why Overlapping full-back 57%: a weighted blend of crossing 76 (weight 30%) + transition 55 (weight 25%) + dribbling 60 (weight 20%) + final-third threat 25 (weight 25%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
through-balls
Strong
crossing
Average
box threat, dribbling, transition, build-up, defensive aggression, carrying, press resistance, ball-winning, retention
Weak
line-breaking, creativity, passing directness, territory (wide vs central), progression, final-third threat, receiving zones
Unknown
aerial ability, marking, off-ball running — not in event data
Through-balls ~proxy
87
Crossing
76
Box threat
65
Dribbling
60
Transition ~proxy
55
Build-up
53
Defensive aggression
51
Carrying
50
Press resistance ~proxy
48
Ball-winning
48
Retention
42
Line-breaking
36
Creativity
28
Passing directness
28
Territory (wide vs central)
28
Progression
27
Final-third threat
25
Receiving zones
16
17

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: 180 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 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.

Emil Holm Bologna · Serie A · 192 cm / 87 kg
62%
Driven by: receiving zones (20%), creativity (15%), progression (11%). Different mechanism — Dedic more via line-breaking; Holm more via defensive aggression, ball-winning.
Aihen Muñoz Real Sociedad · La Liga · 175 cm / 68 kg
52%
Driven by: receiving zones (22%), creativity (18%), progression (16%). Different mechanism — Dedic more via dribbling, through-balls; Muñoz more via passing directness, defensive aggression.
Valentin Rosier Osasuna · La Liga · 175 cm / 71 kg
50%
Driven by: creativity (23%), receiving zones (17%), through-balls (15%). Different mechanism — Dedic more via defensive aggression; Rosier more via passing directness, final-third threat.
Sebastian Sebulonsen Koln · Bundesliga · 187 cm / 78 kg
48%
Driven by: receiving zones (19%), final-third threat (15%), progression (15%). Different mechanism — Dedic more via crossing, through-balls; Sebulonsen more via passing directness.
Fredrik Oppegård Auxerre · Ligue 1 · 175 cm / 67 kg
48%
Driven by: progression (18%), final-third threat (17%), passing directness (16%). Different mechanism — Dedic more via transition, build-up; Oppegård more via territory (wide vs central).
Kristoffer Lund Koln · Bundesliga 25/26 · 184 cm / 65 kg
48%
Driven by: receiving zones (31%), crossing (25%), through-balls (14%). Different mechanism — Dedic more via build-up, defensive aggression; Lund more via final-third threat, passing directness.
18

Summary

Amar Dedic is an overlapping full-back: 2.3 progressive passes and 6 box entries, delivering 4 key passes. Overlap-first full-back. [1v1 recovery pace and off-ball overlap timing need tracking.]

Based on 6 matches (476 minutes) — an early read, treat with caution until more minutes are logged. He profiles as an overlapping full-back — best used in a system built around that identity. His biggest room for growth is final-third threat — even a modest improvement there would meaningfully lift his overall overlapping 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.

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