FSFootyScout
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FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Amine Adli

Bayer Leverkusen · Left Attacking Midfield · MID

Matches observed23
Pass attempts465
Reliable sample

Actual completion

80.4%

374 completed passes

Pass difficulty

82.2%

How difficult a pass was to complete.

Actual vs. expected passing

-1.8 pp

-8.3 completions vs model expectation

Actual pass completion compared with the model's expected completion.

Player intelligence

Position profile

MID context · Each percentile is an empirical rank among eligible players in the same broad position group. Percentiles are not ratings.

102030405060708090Under-pressure pass rateProgressive pass rateLong-pass rateProgressive carry rateActual vs. expected passingCarrying impact / 100 carries
Style
Performance
0–100 empirical percentiles among eligible same-position peers.

Style

Tendencies describe what a player attempts; higher is not automatically better.

Pass difficulty

82.2%

0th percentile among MID players

n = 13 eligible peers · sample 465

Under-pressure pass rate

17.2%

67th percentile among MID players

n = 13 eligible peers · sample 465

Progressive pass rate

16.3%

67th percentile among MID players

n = 13 eligible peers · sample 465

Long-pass rate

5.6%

8th percentile among MID players

n = 13 eligible peers · sample 465

Average forward distance

-1.0 units

8th percentile among MID players

n = 13 eligible peers · sample 465

Positive forward distance / 100 passes

369.9 units

0th percentile among MID players

n = 13 eligible peers · sample 465

Final-third entries / 100 passes

6.237

25th percentile among MID players

n = 13 eligible peers · sample 465

Carry share of actions

48.1%

72nd percentile among MID players

n = 61 eligible peers · sample 858

Progressive carry rate

9.9%

88th percentile among MID players

n = 66 eligible peers · sample 413

Progressive action rate

13.1%

78th percentile among MID players

n = 61 eligible peers · sample 858

Under-pressure action rate

24.4%

60th percentile among MID players

n = 61 eligible peers · sample 858

Shots / observed match

1.17 / match

Unavailable among MID players

n = 5 eligible peers · sample 27

requires 10 eligible position peers

xG / shot

9.1%

Unavailable among MID players

n = 5 eligible peers · sample 27

requires 10 eligible position peers

Performance

Observed execution or model-derived output relative to opportunities.

Actual vs. expected passing

-1.8 pp

25th percentile among MID players

n = 13 eligible peers · sample 465

Under-pressure completion above expected

-0.5 pp

33rd percentile among MID players

n = 10 eligible peers · sample 80

Progressive completion above expected

-3.3 pp

Unavailable among MID players

n = 9 eligible peers · sample 76

requires 10 eligible position peers

Long-pass completion above expected

-7.6 pp

Unavailable among MID players

n = 9 eligible peers · sample 26

requires 10 eligible position peers

Goals above expected

1.547

Unavailable among MID players

n = 5 eligible peers · sample 27

requires 10 eligible position peers

Overall impact / 100 actions

-0.001

53rd percentile among MID players

n = 61 eligible peers · sample 858

Weak split-half stability in the current 34-match product cohort.

Passing impact / 100 passes

-0.237

11th percentile among MID players

n = 58 eligible peers · sample 445

Weak split-half stability in the current 34-match product cohort.

Carrying impact / 100 carries

0.254

92nd percentile among MID players

n = 66 eligible peers · sample 413

Moderate split-half stability; descriptive rather than latent ability.

Progressive-action impact / 100 actions

0.124

93rd percentile among MID players

n = 61 eligible peers · sample 858

Weak split-half stability in the current 34-match product cohort.

Under-pressure impact / 100 actions

0.094

93rd percentile among MID players

n = 61 eligible peers · sample 858

Weak split-half stability in the current 34-match product cohort.

Playing style

Safe Circulator

Position-relative style among eligible MID players.

Style separation0.289

↓Progressive-pass rate (lower)

↑Pass difficulty (higher)

↓Positive forward distance / 100 passes (lower)

↓Long-pass rate (lower)

Pass difficulty-0.85 z
Under-pressure pass rate+0.10 z
Progressive-pass rate+0.58 z
Long-pass rate-1.27 z
Positive forward distance / 100 passes-1.77 z
Carry share of actions+0.73 z

Bars are z-scores relative to eligible positional peers, not percentiles or ratings. Distance-based style separation, not a probability. Smaller values mean the player lies nearer the boundary between the two archetypes.

Leverkusen Role Fit

MID role

How closely a player's playing style matches this role. Compared with the observed role of Leverkusen's other MID contributors.

Role distance · lower is closer1.003
CloserFarther

Strongest alignment

  • Pressure Pass Rate
  • Carry Share Of Actions
  • Progressive Pass Rate

Largest difference

Positive Forward Distance Per 100 Passes

higher sampleObserved across 23 matchesRole: 34 matches · 9 contributors

Role Fit measures how closely a player's observed playing style resembles Bayer Leverkusen's observed positional-role style. It does not predict transfer success or future performance.

Expected Goals

Non-penalty shooting

Goals above expected is descriptive for this observed sample, not a definitive finishing-skill rating.

Reliable sample

Shots

27

16 matches observed

Goals

4

Total xG

2.5

Goals above expected

+1.5

xG / shot

0.1

14.8% goals / shot

Campos visualization

Shot map

Non-penalty xG is encoded by marker size and color. Preserved penalties have no modeled xG.

Shots27
Goals4
xG2.45
xG0.00 – 1.00
Foot
Header
Corner
Green outline = GoalNormal outline = Non-goal

Attacking impact

Impact of passes and carries

Measures how much each pass or carry changed the expected attacking value of a possession. Positive values improved the attack; negative values reduced it.

Reliable sample

Overall impact / 100 actions

-0.001

Passing impact / 100 passes

-0.237

Carrying impact / 100 carries

+0.254

Progressive-action impact / 100 actions

+0.124

Under-pressure impact / 100 actions

+0.094

858 actions · 445 passes · 413 carries · 47.8% increased attacking value

Campos visualization

Carry value map

Exact StatsBomb carry start/end locations. Green increases modeled possession value; coral decreases it.

Situational execution

Under pressure

80 attempts

Reliable sample
Actual
76.3%
Pass difficulty
76.8%
Actual vs. expected passing
-0.5 pp

Progressive passing

76 attempts

Reliable sample
Actual
51.3%
Pass difficulty
54.6%
Actual vs. expected passing
-3.3 pp

Long passing

26 attempts

Reliable sample
Actual
57.7%
Pass difficulty
65.3%
Actual vs. expected passing
-7.6 pp

Progression profile

Progressive-pass rate

16.3%

Pressure-pass rate

17.2%

Average forward distance

-1.0 m

Positive forward distance / 100

369.9 m

Final-third entries / 100

6.2

Campos visualization

Pass map

Attacking left to right. Switch between xPass execution difficulty and possession attacking impact.

Showing 1–200 of 465 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
99.2%
Outcome
Completed
Attacking impact
-0.0022
Value before
0.0140
Value after
0.0118
Length
9.4 m
Context
Standard
Event clocks are not retained in the pass API.

Similar playing styles

Style similarity compares position-relative playing style across passing and carrying tendencies. Scores are not ability ratings.

100 means identical observed profiles; 50 is about the median same-position playing style match. Not a probability.

#1 · Same position group

Florian Wirtz

Bayer Leverkusen · Left Attacking Midfield

Style similarity

73.8 / 100

Carry Share Of ActionsLong Pass RatePressure Pass Rate

Sample support: Higher · 23 limiting matches

Observed: 23 vs 32 matches

#2 · Same position group

Julian Brandt

Borussia Dortmund · Center Attacking Midfield

Style similarity

68.4 / 100

Pressure Pass RatePositive Forward Distance Per 100 Passes
Carry Share Of Actions

Sample support: Limited · 2 limiting matches

Observed: 23 vs 2 matches

#3 · Same position group

Yannick Gerhardt

Wolfsburg · Right Center Midfield

Style similarity

62.5 / 100

Expected Completion RateCarry Share Of ActionsPressure Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 23 vs 2 matches

#4 · Same position group

Mario Götze

Eintracht Frankfurt · Right Defensive Midfield

Style similarity

62.3 / 100

Progressive Pass RatePressure Pass RateExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 23 vs 2 matches

#5 · Same position group

Patrick Osterhage

Bochum · Center Defensive Midfield

Style similarity

61.4 / 100

Pressure Pass RateLong Pass RateCarry Share Of Actions

Sample support: Limited · 2 limiting matches

Observed: 23 vs 2 matches

#6 · Same position group

Jamal Musiala

Bayern Munich · Left Attacking Midfield

Style similarity

61.4 / 100

Long Pass RateProgressive Pass RateExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 23 vs 2 matches

Sample support uses the lower observed-match count in each pair. Lower coverage means a measured profile may vary more with additional matches; it never changes the style similarity or ranking.