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FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Florian Wirtz

Bayer Leverkusen · Left Attacking Midfield · MID

Matches observed32
Pass attempts1,841
Reliable sample

Actual completion

83.8%

1,543 completed passes

Pass difficulty

84.2%

How difficult a pass was to complete.

Actual vs. expected passing

-0.3 pp

-6.4 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

84.2%

33rd percentile among MID players

n = 13 eligible peers · sample 1841

Under-pressure pass rate

19.1%

75th percentile among MID players

n = 13 eligible peers · sample 1841

Progressive pass rate

18.6%

92nd percentile among MID players

n = 13 eligible peers · sample 1841

Long-pass rate

7.3%

17th percentile among MID players

n = 13 eligible peers · sample 1841

Average forward distance

1.5 units

33rd percentile among MID players

n = 13 eligible peers · sample 1841

Positive forward distance / 100 passes

516.4 units

33rd percentile among MID players

n = 13 eligible peers · sample 1841

Final-third entries / 100 passes

8.474

50th percentile among MID players

n = 13 eligible peers · sample 1841

Carry share of actions

48.6%

78th percentile among MID players

n = 61 eligible peers · sample 3509

Progressive carry rate

8.8%

83rd percentile among MID players

n = 66 eligible peers · sample 1707

Progressive action rate

13.8%

80th percentile among MID players

n = 61 eligible peers · sample 3509

Under-pressure action rate

30.0%

77th percentile among MID players

n = 61 eligible peers · sample 3509

Shots / observed match

2.19 / match

Unavailable among MID players

n = 5 eligible peers · sample 70

requires 10 eligible position peers

xG / shot

9.5%

Unavailable among MID players

n = 5 eligible peers · sample 70

requires 10 eligible position peers

Performance

Observed execution or model-derived output relative to opportunities.

Actual vs. expected passing

-0.3 pp

50th percentile among MID players

n = 13 eligible peers · sample 1841

Under-pressure completion above expected

+0.9 pp

56th percentile among MID players

n = 10 eligible peers · sample 352

Progressive completion above expected

+3.2 pp

Unavailable among MID players

n = 9 eligible peers · sample 342

requires 10 eligible position peers

Long-pass completion above expected

+1.6 pp

Unavailable among MID players

n = 9 eligible peers · sample 135

requires 10 eligible position peers

Goals above expected

3.320

Unavailable among MID players

n = 5 eligible peers · sample 70

requires 10 eligible position peers

Overall impact / 100 actions

0.044

72nd percentile among MID players

n = 61 eligible peers · sample 3509

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

Passing impact / 100 passes

-0.122

40th percentile among MID players

n = 58 eligible peers · sample 1802

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

Carrying impact / 100 carries

0.219

83rd percentile among MID players

n = 66 eligible peers · sample 1707

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

Progressive-action impact / 100 actions

0.106

87th percentile among MID players

n = 61 eligible peers · sample 3509

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

Under-pressure impact / 100 actions

0.084

87th percentile among MID players

n = 61 eligible peers · sample 3509

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

Playing style

Safe Circulator

Position-relative style among eligible MID players.

Style separation0.215

↓Progressive-pass rate (lower)

↑Pass difficulty (higher)

↓Positive forward distance / 100 passes (lower)

↓Long-pass rate (lower)

Pass difficulty-0.43 z
Under-pressure pass rate+0.43 z
Progressive-pass rate+0.93 z
Long-pass rate-0.95 z
Positive forward distance / 100 passes-0.60 z
Carry share of actions+0.87 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 closer0.850
CloserFarther

Strongest alignment

  • Positive Forward Distance Per 100 Passes
  • Long Pass Rate
  • Pressure Pass Rate

Largest difference

Progressive Pass Rate

higher sampleObserved across 32 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

70

28 matches observed

Goals

10

Total xG

6.7

Goals above expected

+3.3

xG / shot

0.1

14.3% goals / shot

Campos visualization

Shot map

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

Shots71
Goals11
xG6.68
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

+0.044

Passing impact / 100 passes

-0.122

Carrying impact / 100 carries

+0.219

Progressive-action impact / 100 actions

+0.106

Under-pressure impact / 100 actions

+0.084

3,509 actions · 1,802 passes · 1,707 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

352 attempts

Reliable sample
Actual
80.7%
Pass difficulty
79.7%
Actual vs. expected passing
+0.9 pp

Progressive passing

342 attempts

Reliable sample
Actual
62.3%
Pass difficulty
59.1%
Actual vs. expected passing
+3.2 pp

Long passing

135 attempts

Reliable sample
Actual
65.2%
Pass difficulty
63.6%
Actual vs. expected passing
+1.6 pp

Progression profile

Progressive-pass rate

18.6%

Pressure-pass rate

19.1%

Average forward distance

1.5 m

Positive forward distance / 100

516.4 m

Final-third entries / 100

8.5

Campos visualization

Pass map

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

Showing 1–200 of 1,841 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
81.7%
Outcome
Completed
Attacking impact
-0.0061
Value before
0.0388
Value after
0.0327
Length
6.8 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

Amine Adli

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: 32 vs 23 matches

#2 · Same position group

Mario Götze

Eintracht Frankfurt · Right Defensive Midfield

Style similarity

69.1 / 100

Expected Completion RatePositive Forward Distance Per 100 Passes
Long Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 32 vs 2 matches

#3 · Same position group

Patrick Osterhage

Bochum · Center Defensive Midfield

Style similarity

69.0 / 100

Positive Forward Distance Per 100 PassesLong Pass RatePressure Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 32 vs 2 matches

#4 · Same position group

Yannick Gerhardt

Wolfsburg · Right Center Midfield

Style similarity

67.7 / 100

Positive Forward Distance Per 100 PassesExpected Completion RateCarry Share Of Actions

Sample support: Limited · 2 limiting matches

Observed: 32 vs 2 matches

#5 · Same position group

Jamal Musiala

Bayern Munich · Left Attacking Midfield

Style similarity

67.7 / 100

Expected Completion RatePositive Forward Distance Per 100 PassesLong Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 32 vs 2 matches

#6 · Same position group

Nadiem Amiri

Bayer Leverkusen · Left Defensive Midfield

Style similarity

67.6 / 100

Carry Share Of ActionsExpected Completion RateProgressive Pass Rate

Sample support: Higher · 8 limiting matches

Observed: 32 vs 8 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.