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FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Granit Xhaka

Bayer Leverkusen · Right Defensive Midfield · MID

Matches observed33
Pass attempts3,299
Reliable sample

Actual completion

92.3%

3,045 completed passes

Pass difficulty

91.0%

How difficult a pass was to complete.

Actual vs. expected passing

+1.3 pp

+44.2 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

91.0%

92nd percentile among MID players

n = 13 eligible peers · sample 3299

Under-pressure pass rate

16.0%

58th percentile among MID players

n = 13 eligible peers · sample 3299

Progressive pass rate

9.1%

25th percentile among MID players

n = 13 eligible peers · sample 3299

Long-pass rate

11.9%

67th percentile among MID players

n = 13 eligible peers · sample 3299

Average forward distance

3.3 units

75th percentile among MID players

n = 13 eligible peers · sample 3299

Positive forward distance / 100 passes

654.3 units

75th percentile among MID players

n = 13 eligible peers · sample 3299

Final-third entries / 100 passes

12.761

92nd percentile among MID players

n = 13 eligible peers · sample 3299

Carry share of actions

45.9%

43rd percentile among MID players

n = 61 eligible peers · sample 5969

Progressive carry rate

2.2%

34th percentile among MID players

n = 66 eligible peers · sample 2738

Progressive action rate

5.7%

33rd percentile among MID players

n = 61 eligible peers · sample 5969

Under-pressure action rate

20.9%

40th percentile among MID players

n = 61 eligible peers · sample 5969

Shots / observed match

1.33 / match

Unavailable among MID players

n = 5 eligible peers · sample 44

requires 10 eligible position peers

xG / shot

4.3%

Unavailable among MID players

n = 5 eligible peers · sample 44

requires 10 eligible position peers

Performance

Observed execution or model-derived output relative to opportunities.

Actual vs. expected passing

+1.3 pp

83rd percentile among MID players

n = 13 eligible peers · sample 3299

Under-pressure completion above expected

+2.1 pp

78th percentile among MID players

n = 10 eligible peers · sample 528

Progressive completion above expected

+5.1 pp

Unavailable among MID players

n = 9 eligible peers · sample 299

requires 10 eligible position peers

Long-pass completion above expected

+4.6 pp

Unavailable among MID players

n = 9 eligible peers · sample 391

requires 10 eligible position peers

Goals above expected

1.107

Unavailable among MID players

n = 5 eligible peers · sample 44

requires 10 eligible position peers

Overall impact / 100 actions

0.028

63rd percentile among MID players

n = 61 eligible peers · sample 5969

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

Passing impact / 100 passes

-0.015

68th percentile among MID players

n = 58 eligible peers · sample 3231

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

Carrying impact / 100 carries

0.078

43rd percentile among MID players

n = 66 eligible peers · sample 2738

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

Progressive-action impact / 100 actions

0.023

57th percentile among MID players

n = 61 eligible peers · sample 5969

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

Under-pressure impact / 100 actions

0.033

55th percentile among MID players

n = 61 eligible peers · sample 5969

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

Playing style

Safe Circulator

Position-relative style among eligible MID players.

Style separation0.453

↓Progressive-pass rate (lower)

↑Pass difficulty (higher)

↓Positive forward distance / 100 passes (lower)

↓Long-pass rate (lower)

Pass difficulty+1.06 z
Under-pressure pass rate-0.11 z
Progressive-pass rate-0.54 z
Long-pass rate-0.11 z
Positive forward distance / 100 passes+0.50 z
Carry share of actions+0.09 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 closer0.666
CloserFarther

Strongest alignment

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

Largest difference

Positive Forward Distance Per 100 Passes

higher sampleObserved across 33 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

44

25 matches observed

Goals

3

Total xG

1.9

Goals above expected

+1.1

xG / shot

0.0

6.8% goals / shot

Campos visualization

Shot map

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

Shots44
Goals3
xG1.89
xG0.00 – 1.00
Foot
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

+0.028

Passing impact / 100 passes

-0.015

Carrying impact / 100 carries

+0.078

Progressive-action impact / 100 actions

+0.023

Under-pressure impact / 100 actions

+0.033

5,969 actions · 3,231 passes · 2,738 carries · 51.4% 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

528 attempts

Reliable sample
Actual
89.6%
Pass difficulty
87.5%
Actual vs. expected passing
+2.1 pp

Progressive passing

299 attempts

Reliable sample
Actual
63.5%
Pass difficulty
58.4%
Actual vs. expected passing
+5.1 pp

Long passing

391 attempts

Reliable sample
Actual
84.9%
Pass difficulty
80.3%
Actual vs. expected passing
+4.6 pp

Progression profile

Progressive-pass rate

9.1%

Pressure-pass rate

16.0%

Average forward distance

3.3 m

Positive forward distance / 100

654.3 m

Final-third entries / 100

12.8

Campos visualization

Pass map

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

Showing 1–200 of 3,299 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
68.7%
Outcome
Completed
Attacking impact
0.0033
Value before
0.0348
Value after
0.0382
Length
6.4 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

Robert Andrich

Bayer Leverkusen · Right Defensive Midfield

Style similarity

81.8 / 100

Positive Forward Distance Per 100 PassesProgressive Pass RateLong Pass Rate

Sample support: Higher · 28 limiting matches

Observed: 33 vs 28 matches

#2 · Same position group

Leon Goretzka

Bayern Munich · Left Defensive Midfield

Style similarity

77.6 / 100

Expected Completion Rate
Pressure Pass Rate
Long Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 33 vs 2 matches

#3 · Same position group

Niklas Dorsch

Augsburg · Center Defensive Midfield

Style similarity

77.1 / 100

Expected Completion RateProgressive Pass RatePositive Forward Distance Per 100 Passes

Sample support: Limited · 2 limiting matches

Observed: 33 vs 2 matches

#4 · Same position group

Exequiel Alejandro Palacios

Bayer Leverkusen · Left Defensive Midfield

Style similarity

75.9 / 100

Expected Completion RateProgressive Pass RateCarry Share Of Actions

Sample support: Higher · 24 limiting matches

Observed: 33 vs 24 matches

#5 · Same position group

Aleksandar Pavlović

Bayern Munich · Right Defensive Midfield

Style similarity

72.5 / 100

Expected Completion RateCarry Share Of ActionsProgressive Pass Rate

Sample support: Limited · 1 limiting matches

Observed: 33 vs 1 matches

#6 · Same position group

Aïssa Bilal Laïdouni

Union Berlin · Left Defensive Midfield

Style similarity

71.7 / 100

Pressure Pass RateProgressive Pass RatePositive Forward Distance Per 100 Passes

Sample support: Limited · 2 limiting matches

Observed: 33 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.