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Player reportLigue 1 2026

Abdallah Sima

Lens
Pressing forward ST
5.6 high defensive actions/90
strikerfalse 9box threatfinishing
385
minutes
5 apps
1
goals
0.86 xG
0.9
xG
9 shots
9
shots
0.10 xG/shot
2
box entries
0.47/90
4
key passes
0.94/90
7
dribbles
43% won
73%
pass completion
89 passes
Overview

The player

Who he is and how he compares with his peers.

Thin sample this season. Abdallah Sima has played 5 matches (385 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.

LINK
lay-off and combine
4 key passes · 73% completion · 89× in 5/5 matches
↓
FINISH
shoot from central zones
0.86 xG · 9× in 4/5 matches
↓
CONVERT
goals vs expected
1 goals (+0.1 vs xG) · 1× in 4/5 matches
Signature: Link → Finish → Convert — 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: receive / move — 2× (low confidence, shown as a number only, no tactical conclusion drawn) — 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.

07

How dangerous are his carries?

Real ball-carries

26 tracked carries (6.1/90, 6 progressive, 275m 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.

4%4%23%4%8%8%8%8%4%27%4%
progressivelateral/short% of his 26 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 7m, longest 67m
By zone — where the carry started → where it ended
3Outside → Inside
9Inside → Inside
13Outside → Outside
1Inside → Outside
First (16)Second (10)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.

03

How does he create chances?

4 key passes (0.94/90), 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 (4)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 (2)from the right (2)of 4 key passes landing in the final thirdattacking ↑ toward goal
06

Where does he become vulnerable?

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

22
attacking third (cheap)
6
middle third
0
own third (dangerous)
Vision AI 79% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 0.93 danger-index/90 · 0.142 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
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 →
Where do his chances come from?
Of 4 key passes, his busiest route is a delivery where he plays straight through the left hs 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 central in the final third: 70% of his 10 touches there are lost (7 times).
—0 touches · too few—0 touches · too few—0 touches · too few—2 touches · too few—0 touches · too few12%1/8 lost—5 touches · too few25%2/8 lost9%1/11 lost11%1/9 lost—4 touches · too few56%5/9 lost70%7/10 lost44%4/9 lost21%3/14 lostRWRHSCLHSLWDEFMIDATT
05

Does he carry inside or outside — his ball-carries across the pitch

Four arrows, one per movement class of his ball-carries: outside→inside (cutting in with the ball), inside→outside (carrying wide), outside→outside (down the touchline) and inside→inside (through the middle). Each count is measured from the carry's real start and end coordinates.

own goal left, attacking →
Across 26 ball-carries, his dominant tendency is that he drives along the touchline (50%). He carries from outside into the middle 3 times and out toward the touchline 1 — a genuine inside forward who cuts in with the ball.
04

What happens right after he carries the ball

Every carry's end point matched against his own very next pass or shot in the same match, when one starts almost exactly there — the direct continuation of that touch, not a separate stat. “No clean link” means no pass or shot of his own started close enough to count (often the carry ended in a tackle or a loss); it isn't a claim about exactly what happened, only that nothing traceable followed.

Shot
0 · 0%
Progressive / key pass
2 · 8%
Simple pass
15 · 58%
No clean link
9 · 35%
Of 26 carries, 0% flow straight into a shot of his own, 8% into a key or progressive pass — a genuine end product to the carry, not just ball retention. 35% have no clean link to a next touch of his own close to where the carry ended.
Out of possession

Out of possession

Where and how he defends and presses.

08

How & where does he defend?

56 defensive actions across the season (13.1/90). 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 →
4
tackles · 75% won
4
interceptions · 0.9/90
10
recoveries · 2.3/90
3
clearances · 0.7/90
2
blocks
58
avg action height
24
won high (att 3rd)
24
middle third
8
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 18 proactive ball-wins (4.2/90), tackle success 75%. 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.

36
attacking-half actions · 8.42/90
Team

Team context

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

09

Impact on the Team

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

WITH (5)
WITHOUT (3)
Δ
goals for /match
1.80
2.33
-0.53
xG for /match
1.95
0.00
+1.95
goals against /match
1.80
1.00
+0.80
points /match
0.80
3.00
-2.20
10

His Share of the Team

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

category
share
him / team
goals
11%
1 / 9
shots
9%
39 / 445
expected goals (xG)
8%
4.1 / 52.4
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

11

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 299 strikers 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.

False 975%Target man71%Poacher69%Pressing forward68%
Why False 9 75%: a weighted blend of build-up 81 (weight 25%) + progression 85 (weight 20%) + creativity 56 (weight 30%) + box threat 65 (weight 25%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
line-breaking, territory (wide vs central)
Strong
progression, build-up, carrying, through-balls, ball-winning, final-third threat, crossing
Average
transition, box threat, retention, creativity, defensive aggression, receiving zones, press resistance, dribbling
Weak
passing directness
Unknown
aerial ability, marking, off-ball running — not in event data
Line-breaking
88
Territory (wide vs central)
86
Progression
85
Build-up
81
Carrying
81
Through-balls ~proxy
78
Ball-winning
76
Final-third threat
75
Crossing
72
Transition ~proxy
67
Box threat
65
Retention
65
Creativity
56
Defensive aggression
54
Receiving zones
53
Press resistance ~proxy
52
Dribbling
43
Passing directness
18
12

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 / 79 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 Ligue 1, Bundesliga, La Liga, 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.

Jhon Arias Wolves · Premier League 25/26 · 168 cm / 82 kg
85%
Driven by: build-up (14%), ball-winning (11%), progression (11%). Different mechanism — Sima more via box threat; Arias more via ball-winning, crossing.
Eddie Nketiah Crystal Palace · Premier League · 175 cm / 72 kg
80%
Driven by: build-up (15%), ball-winning (12%), progression (12%). Different mechanism — Sima more via receiving zones, box threat; Nketiah more via passing directness, crossing.
Tidiam Gomis RBL · Bundesliga · 182 cm / 71 kg
80%
Driven by: carrying (14%), territory (wide vs central) (13%), progression (12%). Different mechanism — Sima more via ball-winning, build-up; Gomis more via dribbling, carrying.
Ibrahim Mbaye Aston Villa · Premier League · 185 cm / 65 kg
79%
Driven by: progression (12%), line-breaking (10%), carrying (10%). Different mechanism — Sima more via box threat; Mbaye more via receiving zones, creativity.
Désiré Doué PSG · 181 cm / 79 kg
78%
Driven by: progression (12%), ball-winning (10%), line-breaking (10%). Different mechanism — Doué more via receiving zones, dribbling.
Mikel Oyarzabal Real Sociedad · La Liga · 181 cm / 79 kg
77%
Driven by: build-up (14%), progression (13%), carrying (10%). Different mechanism — Oyarzabal more via passing directness, dribbling.
13

Summary

Abdallah Sima is a false 9 / target man: 1 goals from 0.86 xG (+0.14 vs expected), 9 shots, 2 box entries. A clinical finisher. [Off-ball runs, aerials and hold-up under contact need tracking/aerial data.]

Based on 5 matches (385 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a false 9 / target man — best used in a system built around that identity. His biggest room for growth is creativity — even a modest improvement there would meaningfully lift his overall false 9 profile.
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