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FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Robert Andrich

Bayer Leverkusen · Right Defensive Midfield · MID

Matches observed28
Pass attempts1,501
Reliable sample

Actual completion

90.5%

1,359 completed passes

Pass difficulty

89.6%

How difficult a pass was to complete.

Actual vs. expected passing

+0.9 pp

+13.4 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

89.6%

75th percentile among MID players

n = 13 eligible peers · sample 1501

Under-pressure pass rate

12.7%

25th percentile among MID players

n = 13 eligible peers · sample 1501

Progressive pass rate

9.8%

42nd percentile among MID players

n = 13 eligible peers · sample 1501

Long-pass rate

11.0%

58th percentile among MID players

n = 13 eligible peers · sample 1501

Average forward distance

3.9 units

100th percentile among MID players

n = 13 eligible peers · sample 1501

Positive forward distance / 100 passes

666.4 units

83rd percentile among MID players

n = 13 eligible peers · sample 1501

Final-third entries / 100 passes

9.727

75th percentile among MID players

n = 13 eligible peers · sample 1501

Carry share of actions

43.7%

30th percentile among MID players

n = 61 eligible peers · sample 2571

Progressive carry rate

1.5%

29th percentile among MID players

n = 66 eligible peers · sample 1124

Progressive action rate

5.9%

35th percentile among MID players

n = 61 eligible peers · sample 2571

Under-pressure action rate

15.4%

10th percentile among MID players

n = 61 eligible peers · sample 2571

Shots / observed match

0.82 / match

Unavailable among MID players

n = 5 eligible peers · sample 23

requires 10 eligible position peers

xG / shot

8.2%

Unavailable among MID players

n = 5 eligible peers · sample 23

requires 10 eligible position peers

Performance

Observed execution or model-derived output relative to opportunities.

Actual vs. expected passing

+0.9 pp

75th percentile among MID players

n = 13 eligible peers · sample 1501

Under-pressure completion above expected

+0.0 pp

44th percentile among MID players

n = 10 eligible peers · sample 190

Progressive completion above expected

-0.8 pp

Unavailable among MID players

n = 9 eligible peers · sample 147

requires 10 eligible position peers

Long-pass completion above expected

-2.3 pp

Unavailable among MID players

n = 9 eligible peers · sample 165

requires 10 eligible position peers

Goals above expected

2.124

Unavailable among MID players

n = 5 eligible peers · sample 23

requires 10 eligible position peers

Overall impact / 100 actions

0.029

65th percentile among MID players

n = 61 eligible peers · sample 2571

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

Passing impact / 100 passes

-0.003

74th percentile among MID players

n = 58 eligible peers · sample 1447

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

Carrying impact / 100 carries

0.069

34th percentile among MID players

n = 66 eligible peers · sample 1124

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

Progressive-action impact / 100 actions

0.007

42nd percentile among MID players

n = 61 eligible peers · sample 2571

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

Under-pressure impact / 100 actions

0.024

40th percentile among MID players

n = 61 eligible peers · sample 2571

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

Playing style

Safe Circulator

Position-relative style among eligible MID players.

Style separation0.206

↓Progressive-pass rate (lower)

↑Pass difficulty (higher)

↓Positive forward distance / 100 passes (lower)

↓Long-pass rate (lower)

Pass difficulty+0.77 z
Under-pressure pass rate-0.69 z
Progressive-pass rate-0.42 z
Long-pass rate-0.27 z
Positive forward distance / 100 passes+0.59 z
Carry share of actions-0.52 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 closer0.610
CloserFarther

Strongest alignment

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

Largest difference

Positive Forward Distance Per 100 Passes

higher sampleObserved across 28 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

23

11 matches observed

Goals

4

Total xG

1.9

Goals above expected

+2.1

xG / shot

0.1

17.4% goals / shot

Campos visualization

Shot map

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

Shots23
Goals4
xG1.88
xG0.00 – 1.00
Foot
Header
Set piece
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

+0.029

Passing impact / 100 passes

-0.003

Carrying impact / 100 carries

+0.069

Progressive-action impact / 100 actions

+0.007

Under-pressure impact / 100 actions

+0.024

2,571 actions · 1,447 passes · 1,124 carries · 53.5% 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

190 attempts

Reliable sample
Actual
85.8%
Pass difficulty
85.8%
Actual vs. expected passing
+0.0 pp

Progressive passing

147 attempts

Reliable sample
Actual
54.4%
Pass difficulty
55.3%
Actual vs. expected passing
-0.8 pp

Long passing

165 attempts

Reliable sample
Actual
75.2%
Pass difficulty
77.5%
Actual vs. expected passing
-2.3 pp

Progression profile

Progressive-pass rate

9.8%

Pressure-pass rate

12.7%

Average forward distance

3.9 m

Positive forward distance / 100

666.4 m

Final-third entries / 100

9.7

Campos visualization

Pass map

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

Showing 1–200 of 1,501 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
84.8%
Outcome
Completed
Attacking impact
0.0005
Value before
0.0105
Value after
0.0109
Length
5.1 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

Granit Xhaka

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: 28 vs 33 matches

#2 · Same position group

Leon Goretzka

Bayern Munich · Left Defensive Midfield

Style similarity

74.3 / 100

Carry Share Of ActionsLong Pass Rate
Expected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 28 vs 2 matches

#3 · Same position group

Exequiel Alejandro Palacios

Bayer Leverkusen · Left Defensive Midfield

Style similarity

73.7 / 100

Pressure Pass RateExpected Completion RateProgressive Pass Rate

Sample support: Higher · 24 limiting matches

Observed: 28 vs 24 matches

#4 · Same position group

Julian Weigl

Borussia Mönchengladbach · Right Defensive Midfield

Style similarity

73.6 / 100

Progressive Pass RatePositive Forward Distance Per 100 PassesExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 28 vs 2 matches

#5 · Same position group

Aïssa Bilal Laïdouni

Union Berlin · Left Defensive Midfield

Style similarity

70.2 / 100

Progressive Pass RatePositive Forward Distance Per 100 PassesLong Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 28 vs 2 matches

#6 · Same position group

Florian Neuhaus

Borussia Mönchengladbach · Left Defensive Midfield

Style similarity

69.9 / 100

Long Pass RatePressure Pass RateProgressive Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 28 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.