العربيةSeason20262026 · this seasonAll seasons
Building the full report
Combining every season — this one is larger, give it a moment.
Vision AI ← BACK TO SEARCH
Player reportSerie A 2026

Omri Gandelman

Lecce
Half-space creator AM
41% of actions in the half-spaces
attacking midhalf-space creatorcreationbetween the lines
1049
minutes
21 apps
8
key passes
0.69/90
6
progressive passes
0.5/90
5
box entries
0.43/90
10
final-3rd entries
0.9/90
2
goals
1.14 xG
11
dribbles
18% won
63%
pass completion
253 passes
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 Half-Space, Middle third — between the lines — mostly in the middle third (59% of his 253 passes)
63% completion · 253× in 20/20 matches
↓
TURN / BEAT MAN
face forward in the pocket
18% won · 11× in 9/20 matches
↓
CREATE
through-ball, cut-back, key pass
0.69/90 · 8× in 6/20 matches
↓
FINISH
arrive and shoot from central zones
2 goals · 1.14 xG · 12× in 6/20 matches
Signature: receive between the lines → turn → create or finish.
17

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 →
13
passes / match
1.2
dribbles / match
2–35
pass range (matches)
1–2
dribble range (matches)
Pass range = his fewest and most passes in any single match this season (2 at the low end, 35 at the high) — a measure of match-to-match involvement, not pass distance. Dribble range works the same way, for dribbles/carries per match.
In possession

In possession

What he does with the ball: build-up, progression, creation, carrying and finishing.

07

How dangerous are his carries?

Real ball-carries

16 tracked carries (1.4/90, 3 progressive, 147m 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.

6%25%25%12%12%6%6%6%
progressivelateral/short% of his 16 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 6m, longest 27m
By zone — where the carry started → where it ended
8Inside → Inside
7Outside → Outside
1Inside → Outside
First (16)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →

Dribbles (1v1s)

Does he carry to create or drift wide? Dribbles by channel. Season rate: 0.94 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 82%
OUTSIDE 18%
Dribble location — 9 inside · 2 outside
Right Wing
2 · 18%
Right Half-Space
5 · 45%
Central
3 · 27%
Left Half-Space
1 · 9%
Left Wing
0 · 0%
Vision AI His carries cluster centrally — a central creator.
12

How does he build & move the ball?

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 →RWRHSCLHSLWRW6073%4422%135%3RHS4825%1238%1833%164%2C2910%328%838%1114%410%3LHS1513%247%740%6LW850%450%4FROM
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 wing in the middle third — 2 progressive passes (12% of his progression) at -0.004 xT each. He keeps it in the same lane.

His progression is inward: 41% of progressive passes move the ball toward the middle versus 6% 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: 5 line-breaking passes and 10 final-third entries, 0.8 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
1%3%13%26%15%5%2%2%5%9%5%2%1%3%4%4%2%
completedincomplete253 passes · any zone → any zone · own goal left, attacking →
253
passes
63%
completed
93
lost
Vision AIIn line with his 63% season completion rate.
02

How does he create chances?

8 key passes (0.69/90), 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:
25%25%25%25%
chance creation (8)assist (0)% of the selected group's key passes originating in each zone
Box deliveries — key passes reaching the final third, by flank
from the left (1)from the right (7)of 8 key passes landing in the final thirdattacking ↑ toward goal
09

Can he finish?

12 shots · 1.14 xG · 2 goals (+0.86 vs xG). Mostly left-footed. Circle size = xG.

shots  12
on target  7
goals  2
xG  1.14
xG on target  0.88
xG / shot  0.095
Where he shoots from — click an area of the box
04

Where does he become vulnerable?

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

27
attacking third (cheap)
67
middle third
8
own third (dangerous)
Vision AI 26% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 2.59 danger-index/90 · 0.296 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
10

What is his passing profile?

253
passes attempted
43%
mostly sideways
76%
mostly short
Direction
Forward
93 · 37%
Sideways
109 · 43%
Backward
51 · 20%
Length (completed)
Short (<15m)
121 · 76%
Medium
34 · 21%
Long (>30m)
5 · 3%
05

Where Does He Receive?

The zones where Omri Gandelman 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
22%
Primary
Right Half-Space, Middle third
21%
Secondary
Right Wing, Middle third
14%
Third
Right Wing, Attacking third
These are the zones where he collected the ball most.
06

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Omri Gandelman 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:
271094451226141621034674212
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.

1%3%13%26%15%5%2%2%5%9%5%2%1%3%4%4%2%
own goal left, attacking →
11

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.

8Key pass
1Cross
6Cutback
6Progressive
6Long ball
2Switch
By zone — where the pass started → where it landed
20Outside → Inside
68Inside → Inside
48Outside → Outside
24Inside → Outside
By direction
93Forward
51Backward
109Sideways
own goal left, attacking →
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 8 key passes, his busiest route is a delivery where he plays straight through the right hs in the final third — 3 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 middle third: 50% of his 14 touches there are lost (7 times).
—6 touches · too few—4 touches · too few12%1/8 lost—2 touches · too few—0 touches · too few42%23/55 lost44%24/55 lost32%6/19 lost50%7/14 lost—7 touches · too few29%10/35 lost30%6/20 lost36%5/14 lost30%3/10 lost—4 touches · too fewRWRHSCLHSLWDEFMIDATT
08

Crosses & Cutbacks

1 crosses (0.09/90, 0 completed) and 6 cutbacks (0.51/90, 2 completed) — two separate wide-delivery patterns into the box, each its own map with a completed/failed filter. Neither is a tagged event, so both are inferred from pass geometry — the intended end point of a failed attempt is still real data (an interception doesn’t erase where the ball was aimed): a cross is a pass aimed into the box starting from a wide channel; a cutback starts almost on the byline but is squared back rather than driven forward, aimed centrally around the box. The completed-cross count was checked against this platform’s own real match-level cross totals and lands within about 1 cross of the true count.

Crosses — close-up on the final third
Cutbacks — close-up on the final third
completedfailed (dashed)close-up on the box — attacking ↑ toward goal
Out of possession

Out of possession

Where and how he defends and presses.

14

How & where does he defend?

189 defensive actions across the season (16.2/90). 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 →
10
tackles · 60% won
4
interceptions · 0.3/90
21
recoveries · 1.8/90
15
clearances · 1.3/90
7
blocks
55
avg action height
50
won high (att 3rd)
111
middle third
28
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 35 proactive ball-wins (3.0/90), tackle success 60%. He defends high, stepping out to intercept — suits a high line.

Defensive work in the attacking half

Ball-wins in the attacking half only (own half vs. attacking half, a simple 2-way split, not the usual thirds) — the clearest single signal of how much he presses and recovers the ball high up the pitch.

134
attacking-half actions · 11.50/90
13

Against Different Pressing Intensities

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Omri Gandelman keep producing when the game is tight and the press is high? Tiers of ~7-7 matches — directional evidence, not proof.

press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 3.4, 7m)
0.46
1.3
0.42
0%
Mid press (PPDA 4.3, 7m)
0.23
0.5
0.23
0%
Low press (PPDA 5.2, 7m)
0.32
0.2
1.23
29%
Team

Team context

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

15

Impact on the Team

Lecce's output per match with Omri Gandelman (2 matches) versus without him (6 matches). Insufficient evidence — the without-sample is only 6 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.

WITH (2)
WITHOUT (6)
Δ
goals for /match
1.50
1.00
+0.50
xG for /match
1.55
1.19
+0.37
goals against /match
1.00
2.00
-1.00
points /match
1.50
1.00
+0.50
16

His Share of the Team

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

category
share
him / team
goals
5%
2 / 37
box entries
2%
11 / 453
half-space entries
2%
21 / 870
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

18

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 247 attacking 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.

Half-space creator9%Advanced playmaker (8)9%
Why Half-space creator 9%: a weighted blend of creativity 12 (weight 40%) + final-third threat 6 (weight 30%) + dribbling 4 (weight 15%) + box threat 4 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
passing directness
Strong
defensive aggression
Average
crossing
Weak
territory (wide vs central), transition, build-up, ball-winning, creativity, receiving zones, retention, press resistance, progression, final-third threat, line-breaking, dribbling, through-balls, box threat, carrying
Unknown
aerial ability, marking, off-ball running — not in event data
Passing directness
86
Defensive aggression
84
Crossing
43
Territory (wide vs central)
33
Transition ~proxy
28
Build-up
27
Ball-winning
22
Creativity
12
Receiving zones
10
Retention
8
Press resistance ~proxy
7
Progression
6
Final-third threat
6
Line-breaking
6
Dribbling
4
Through-balls ~proxy
4
Box threat
4
Carrying
3
19

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 / 84 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.

Brennan Johnson Everton · Premier League · 186 cm / 73 kg
92%
Driven by: press resistance (11%), box threat (10%), progression (9%). Different mechanism — Gandelman more via defensive aggression; Johnson more via through-balls, territory (wide vs central).
Jens Odgaard Bologna · 188 cm / 83 kg
91%
Driven by: progression (10%), creativity (10%), press resistance (8%). Different mechanism — Gandelman more via defensive aggression; Odgaard more via box threat, dribbling.
Ilyas Ansah Union Berlin · Bundesliga 25/26 · 194 cm / 84 kg
85%
Driven by: creativity (11%), box threat (10%), final-third threat (9%). Different mechanism — Gandelman more via passing directness; Ansah more via carrying, dribbling.
Kevin Schade Brentford · Premier League · 183 cm / 74 kg
85%
Driven by: press resistance (11%), retention (9%), dribbling (9%). Different mechanism — Schade more via box threat, ball-winning.
Unai Gómez Udinese · 183 cm / 75 kg
84%
Driven by: progression (8%), transition (8%). Different mechanism — Gandelman more via passing directness; Gómez more via box threat, dribbling.
Ismaïla Sarr Crystal Palace · Premier League · 185 cm / 76 kg
83%
Driven by: press resistance (13%), dribbling (10%), retention (8%). Different mechanism — Gandelman more via defensive aggression; Sarr more via box threat, transition.
20

Summary

Omri Gandelman is a half-space creator: 0.69 key passes /90, 0.5 progressive passes, 2 goals from 1.14 xG. A between-the-lines creator. [Off-ball movement into pockets needs tracking.]

Based on 21 matches (1049 minutes) — a reasonable read, still building toward a full-season sample. He profiles as a half-space creator — best used in a system built around that identity. His biggest room for growth is dribbling — even a modest improvement there would meaningfully lift his overall half-space creator 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.

Vision AI · building report