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FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Adam Hložek

Bayer Leverkusen · Right Attacking Midfield · MID

Matches observed19
Pass attempts155
Reliable sample

Actual completion

84.5%

131 completed passes

Pass difficulty

84.5%

How difficult a pass was to complete.

Actual vs. expected passing

+0.0 pp

+0.1 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

84.5%

42nd percentile among MID players

n = 13 eligible peers · sample 155

Under-pressure pass rate

31.6%

100th percentile among MID players

n = 13 eligible peers · sample 155

Progressive pass rate

9.7%

33rd percentile among MID players

n = 13 eligible peers · sample 155

Long-pass rate

8.4%

33rd percentile among MID players

n = 13 eligible peers · sample 155

Average forward distance

-0.7 units

17th percentile among MID players

n = 13 eligible peers · sample 155

Positive forward distance / 100 passes

438.8 units

17th percentile among MID players

n = 13 eligible peers · sample 155

Final-third entries / 100 passes

4.516

8th percentile among MID players

n = 13 eligible peers · sample 155

Carry share of actions

52.7%

92nd percentile among MID players

n = 61 eligible peers · sample 315

Progressive carry rate

7.2%

77th percentile among MID players

n = 66 eligible peers · sample 166

Progressive action rate

7.6%

47th percentile among MID players

n = 61 eligible peers · sample 315

Under-pressure action rate

46.7%

100th percentile among MID players

n = 61 eligible peers · sample 315

Shots / observed match

1.00 / match

Unavailable among MID players

n = 5 eligible peers · sample 19

requires 20 shots

xG / shot

14.4%

Unavailable among MID players

n = 5 eligible peers · sample 19

requires 20 shots

Performance

Observed execution or model-derived output relative to opportunities.

Actual vs. expected passing

+0.0 pp

58th percentile among MID players

n = 13 eligible peers · sample 155

Under-pressure completion above expected

+1.8 pp

67th percentile among MID players

n = 10 eligible peers · sample 49

Progressive completion above expected

+2.3 pp

Unavailable among MID players

n = 9 eligible peers · sample 15

requires 20 progressive passes

Long-pass completion above expected

-5.8 pp

Unavailable among MID players

n = 9 eligible peers · sample 13

requires 20 long passes

Goals above expected

-0.739

Unavailable among MID players

n = 5 eligible peers · sample 19

requires 20 shots

Overall impact / 100 actions

-0.020

43rd percentile among MID players

n = 61 eligible peers · sample 315

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

Passing impact / 100 passes

-0.146

35th percentile among MID players

n = 58 eligible peers · sample 149

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

Carrying impact / 100 carries

0.093

55th percentile among MID players

n = 66 eligible peers · sample 166

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

Progressive-action impact / 100 actions

0.143

97th percentile among MID players

n = 61 eligible peers · sample 315

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

Under-pressure impact / 100 actions

0.052

75th percentile among MID players

n = 61 eligible peers · sample 315

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

Playing style

Safe Circulator

Position-relative style among eligible MID players.

Style separation0.302

↓Progressive-pass rate (lower)

↑Pass difficulty (higher)

↓Positive forward distance / 100 passes (lower)

↓Long-pass rate (lower)

Pass difficulty-0.36 z
Under-pressure pass rate+2.60 z
Progressive-pass rate-0.44 z
Long-pass rate-0.75 z
Positive forward distance / 100 passes-1.22 z
Carry share of actions+2.01 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 closer1.507
CloserFarther

Strongest alignment

  • Long Pass Rate
  • Progressive Pass Rate
  • Expected Completion Rate

Largest difference

Pressure Pass Rate

higher sampleObserved across 19 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.

Limited sample

Shots

19

9 matches observed

Goals

2

Total xG

2.7

Goals above expected

-0.7

xG / shot

0.1

10.5% goals / shot

Limited sample: fewer than 20 non-penalty shots.

Campos visualization

Shot map

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

Shots19
Goals2
xG2.74
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

-0.020

Passing impact / 100 passes

-0.146

Carrying impact / 100 carries

+0.093

Progressive-action impact / 100 actions

+0.143

Under-pressure impact / 100 actions

+0.052

315 actions · 149 passes · 166 carries · 50.8% 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

49 attempts

Reliable sample
Actual
83.7%
Pass difficulty
81.8%
Actual vs. expected passing
+1.8 pp

Progressive passing

15 attempts

Limited sample
Actual
60.0%
Pass difficulty
57.7%
Actual vs. expected passing
+2.3 pp

Limited sample — interpret this split cautiously.

Long passing

13 attempts

Limited sample
Actual
69.2%
Pass difficulty
75.0%
Actual vs. expected passing

Progression profile

Progressive-pass rate

9.7%

Pressure-pass rate

31.6%

Average forward distance

-0.7 m

Positive forward distance / 100

438.8 m

Final-third entries / 100

4.5

Campos visualization

Pass map

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

Showing 1–155 of 155 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
76.8%
Outcome
Incomplete
Attacking impact
—
Value before
—
Value after
—
Length
16.9 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

Jamal Musiala

Bayern Munich · Left Attacking Midfield

Style similarity

70.6 / 100

Expected Completion RateCarry Share Of ActionsPositive Forward Distance Per 100 Passes

Sample support: Limited · 2 limiting matches

Observed: 19 vs 2 matches

#2 · Same position group

Florian Wirtz

Bayer Leverkusen · Left Attacking Midfield

Style similarity

53.0 / 100

Expected Completion Rate
-5.8 pp

Limited sample — interpret this split cautiously.

Long Pass Rate
Positive Forward Distance Per 100 Passes

Sample support: Higher · 19 limiting matches

Observed: 19 vs 32 matches

#3 · Same position group

Julian Brandt

Borussia Dortmund · Center Attacking Midfield

Style similarity

52.8 / 100

Expected Completion RatePositive Forward Distance Per 100 PassesLong Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 19 vs 2 matches

#4 · Same position group

Nadiem Amiri

Bayer Leverkusen · Left Defensive Midfield

Style similarity

52.3 / 100

Expected Completion RateLong Pass RateProgressive Pass Rate

Sample support: Higher · 8 limiting matches

Observed: 19 vs 8 matches

#5 · Same position group

Dejan Ljubicic

FC Köln · Center Attacking Midfield

Style similarity

51.4 / 100

Expected Completion RatePressure Pass RateProgressive Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 19 vs 2 matches

#6 · Same position group

Amine Adli

Bayer Leverkusen · Left Attacking Midfield

Style similarity

50.2 / 100

Expected Completion RateLong Pass RatePositive Forward Distance Per 100 Passes

Sample support: Higher · 19 limiting matches

Observed: 19 vs 23 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.