FSFootyScout
PlayersTeam IntelligenceScoutingLeaderboardCompareArchetypesModel

FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Yannick Gerhardt

Wolfsburg · Right Center Midfield · MID

Matches observed2
Pass attempts56
Limited sample

Actual completion

76.8%

43 completed passes

Pass difficulty

82.2%

How difficult a pass was to complete.

Actual vs. expected passing

-5.4 pp

-3.0 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.

Insufficient eligible position metrics for a meaningful radar.

Style

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

Pass difficulty

82.2%

Unavailable among MID players

n = 13 eligible peers · sample 56

requires 100 passes

Under-pressure pass rate

14.3%

Unavailable among MID players

n = 13 eligible peers · sample 56

requires 100 passes

Progressive pass rate

12.5%

Unavailable among MID players

n = 13 eligible peers · sample 56

requires 100 passes

Long-pass rate

12.5%

Unavailable among MID players

n = 13 eligible peers · sample 56

requires 100 passes

Average forward distance

-0.0 units

Unavailable among MID players

n = 13 eligible peers · sample 56

requires 100 passes

Positive forward distance / 100 passes

550.9 units

Unavailable among MID players

n = 13 eligible peers · sample 56

requires 100 passes

Final-third entries / 100 passes

12.500

Unavailable among MID players

n = 13 eligible peers · sample 56

requires 100 passes

Carry share of actions

46.5%

52nd percentile among MID players

n = 61 eligible peers · sample 101

Progressive carry rate

4.3%

57th percentile among MID players

n = 66 eligible peers · sample 47

Progressive action rate

7.9%

48th percentile among MID players

n = 61 eligible peers · sample 101

Under-pressure action rate

18.8%

28th percentile among MID players

n = 61 eligible peers · sample 101

Shots / observed match

1.00 / match

Unavailable among MID players

n = 5 eligible peers · sample 2

requires 20 shots

xG / shot

6.4%

Unavailable among MID players

n = 5 eligible peers · sample 2

requires 20 shots

Performance

Observed execution or model-derived output relative to opportunities.

Actual vs. expected passing

-5.4 pp

Unavailable among MID players

n = 13 eligible peers · sample 56

requires 100 passes

Under-pressure completion above expected

-6.0 pp

Unavailable among MID players

n = 10 eligible peers · sample 8

requires 20 pressure passes

Progressive completion above expected

-12.2 pp

Unavailable among MID players

n = 9 eligible peers · sample 7

requires 20 progressive passes

Long-pass completion above expected

-13.1 pp

Unavailable among MID players

n = 9 eligible peers · sample 7

requires 20 long passes

Goals above expected

-0.127

Unavailable among MID players

n = 5 eligible peers · sample 2

requires 20 shots

Overall impact / 100 actions

-0.237

2nd percentile among MID players

n = 61 eligible peers · sample 101

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

Passing impact / 100 passes

-0.508

2nd percentile among MID players

n = 58 eligible peers · sample 54

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

Carrying impact / 100 carries

0.075

40th percentile among MID players

n = 66 eligible peers · sample 47

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

Progressive-action impact / 100 actions

-0.042

15th percentile among MID players

n = 61 eligible peers · sample 101

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

Under-pressure impact / 100 actions

-0.029

7th percentile among MID players

n = 61 eligible peers · sample 101

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

Playing style

Direct Progressor

Position-relative style among eligible MID players.

Style separation0.088

↑Progressive-pass rate (higher)

↓Pass difficulty (lower)

↑Positive forward distance / 100 passes (higher)

↑Long-pass rate (higher)

Pass difficulty-0.86 z
Under-pressure pass rate-0.41 z
Progressive-pass rate-0.01 z
Long-pass rate+0.02 z
Positive forward distance / 100 passes-0.33 z
Carry share of actions+0.27 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 Bayer Leverkusen's observed MID role.

Role distance · lower is closer0.565
CloserFarther

Strongest alignment

  • Progressive Pass Rate
  • Positive Forward Distance Per 100 Passes
  • Carry Share Of Actions

Largest difference

Expected Completion Rate

limited sampleObserved across 2 matchesRole: 34 matches · 10 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

2

1 matches observed

Goals

0

Total xG

0.1

Goals above expected

-0.1

xG / shot

0.1

0.0% 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.

Shots2
Goals0
xG0.13
xG0.00 – 1.00
Foot
Header
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

-0.237

Passing impact / 100 passes

-0.508

Carrying impact / 100 carries

+0.075

Progressive-action impact / 100 actions

-0.042

Under-pressure impact / 100 actions

-0.029

101 actions · 54 passes · 47 carries · 39.6% 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

8 attempts

Limited sample
Actual
50.0%
Pass difficulty
56.0%
Actual vs. expected passing
-6.0 pp

Limited sample — interpret this split cautiously.

Progressive passing

7 attempts

Limited sample
Actual
28.6%
Pass difficulty
40.8%
Actual vs. expected passing
-12.2 pp

Limited sample — interpret this split cautiously.

Long passing

7 attempts

Limited sample
Actual
42.9%
Pass difficulty
55.9%

Progression profile

Progressive-pass rate

12.5%

Pressure-pass rate

14.3%

Average forward distance

-0.0 m

Positive forward distance / 100

550.9 m

Final-third entries / 100

12.5

Campos visualization

Pass map

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

Showing 1–56 of 56 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
12.8%
Outcome
Incomplete
Attacking impact
-0.0058
Value before
0.0058
Value after
0.0000
Length
16.9 m
Context
Under pressure
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.

Limited sample: this player's style profile is based on 2 observed matches, so nearest-neighbor rankings may be less stable.

#1 · Same position group

Florian Neuhaus

Borussia Mönchengladbach · Left Defensive Midfield

Style similarity

76.9 / 100

Progressive Pass RateCarry Share Of ActionsPositive Forward Distance Per 100 Passes

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#2 · Same position group

Mario Götze

Eintracht Frankfurt · Right Defensive Midfield

Style similarity

74.2 / 100

Actual vs. expected passing
-13.1 pp

Limited sample — interpret this split cautiously.

Positive Forward Distance Per 100 PassesPressure Pass RateExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#3 · Same position group

Nicolas Seiwald

RB Leipzig · Right Defensive Midfield

Style similarity

73.7 / 100

Positive Forward Distance Per 100 PassesCarry Share Of ActionsPressure Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#4 · Same position group

Aïssa Bilal Laïdouni

Union Berlin · Left Defensive Midfield

Style similarity

73.6 / 100

Carry Share Of ActionsPressure Pass RateProgressive Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#5 · Same position group

Julian Brandt

Borussia Dortmund · Center Attacking Midfield

Style similarity

68.7 / 100

Carry Share Of ActionsLong Pass RateExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#6 · Same position group

Jonas Hofmann

Bayer Leverkusen · Right Attacking Midfield

Style similarity

67.8 / 100

Expected Completion RatePressure Pass RateLong Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 32 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.