FSFootyScout
PlayersTeam IntelligenceScoutingLeaderboardCompareArchetypesModel

FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Thomas Müller

Bayern Munich · Center Attacking Midfield · MID

Matches observed2
Pass attempts50
Limited sample

Actual completion

86.0%

43 completed passes

Pass difficulty

83.8%

How difficult a pass was to complete.

Actual vs. expected passing

+2.2 pp

+1.1 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.

Insufficient eligible position metrics for a meaningful radar.

Style

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

Pass difficulty

83.8%

Unavailable among MID players

n = 13 eligible peers · sample 50

requires 100 passes

Under-pressure pass rate

22.0%

Unavailable among MID players

n = 13 eligible peers · sample 50

requires 100 passes

Progressive pass rate

22.0%

Unavailable among MID players

n = 13 eligible peers · sample 50

requires 100 passes

Long-pass rate

6.0%

Unavailable among MID players

n = 13 eligible peers · sample 50

requires 100 passes

Average forward distance

0.2 units

Unavailable among MID players

n = 13 eligible peers · sample 50

requires 100 passes

Positive forward distance / 100 passes

500.8 units

Unavailable among MID players

n = 13 eligible peers · sample 50

requires 100 passes

Final-third entries / 100 passes

10.000

Unavailable among MID players

n = 13 eligible peers · sample 50

requires 100 passes

Carry share of actions

41.0%

7th percentile among MID players

n = 61 eligible peers · sample 83

Progressive carry rate

2.9%

43rd percentile among MID players

n = 66 eligible peers · sample 34

Progressive action rate

14.5%

82nd percentile among MID players

n = 61 eligible peers · sample 83

Under-pressure action rate

31.3%

83rd percentile among MID players

n = 61 eligible peers · sample 83

Shots / observed match

0.50 / match

Unavailable among MID players

n = 5 eligible peers · sample 1

requires 20 shots

xG / shot

11.0%

Unavailable among MID players

n = 5 eligible peers · sample 1

requires 20 shots

Performance

Observed execution or model-derived output relative to opportunities.

Actual vs. expected passing

+2.2 pp

Unavailable among MID players

n = 13 eligible peers · sample 50

requires 100 passes

Under-pressure completion above expected

+3.6 pp

Unavailable among MID players

n = 10 eligible peers · sample 11

requires 20 pressure passes

Progressive completion above expected

-7.4 pp

Unavailable among MID players

n = 9 eligible peers · sample 11

requires 20 progressive passes

Long-pass completion above expected

+26.0 pp

Unavailable among MID players

n = 9 eligible peers · sample 3

requires 20 long passes

Goals above expected

-0.110

Unavailable among MID players

n = 5 eligible peers · sample 1

requires 20 shots

Overall impact / 100 actions

0.093

87th percentile among MID players

n = 61 eligible peers · sample 83

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

Passing impact / 100 passes

0.100

96th percentile among MID players

n = 58 eligible peers · sample 49

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

Carrying impact / 100 carries

0.084

49th percentile among MID players

n = 66 eligible peers · sample 34

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

Progressive-action impact / 100 actions

0.072

75th percentile among MID players

n = 61 eligible peers · sample 83

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

Under-pressure impact / 100 actions

0.056

78th percentile among MID players

n = 61 eligible peers · sample 83

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

Playing style

Direct Progressor

Position-relative style among eligible MID players.

Style separation0.078

↑Progressive-pass rate (higher)

↓Pass difficulty (lower)

↑Positive forward distance / 100 passes (higher)

↑Long-pass rate (higher)

Pass difficulty-0.51 z
Under-pressure pass rate+0.93 z
Progressive-pass rate+1.45 z
Long-pass rate-1.20 z
Positive forward distance / 100 passes-0.73 z
Carry share of actions-1.30 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 closer1.113
CloserFarther

Strongest alignment

  • Positive Forward Distance Per 100 Passes
  • Long Pass Rate
  • Expected Completion Rate

Largest difference

Progressive Pass 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

1

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.

Shots1
Goals0
xG0.11
xG0.00 – 1.00
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

+0.093

Passing impact / 100 passes

+0.100

Carrying impact / 100 carries

+0.084

Progressive-action impact / 100 actions

+0.072

Under-pressure impact / 100 actions

+0.056

83 actions · 49 passes · 34 carries · 55.4% 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

11 attempts

Limited sample
Actual
90.9%
Pass difficulty
87.3%
Actual vs. expected passing
+3.6 pp

Limited sample — interpret this split cautiously.

Progressive passing

11 attempts

Limited sample
Actual
45.5%
Pass difficulty
52.9%
Actual vs. expected passing
-7.4 pp

Limited sample — interpret this split cautiously.

Long passing

3 attempts

Limited sample
Actual
100.0%
Pass difficulty
74.0%

Progression profile

Progressive-pass rate

22.0%

Pressure-pass rate

22.0%

Average forward distance

0.2 m

Positive forward distance / 100

500.8 m

Final-third entries / 100

10.0

Campos visualization

Pass map

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

Showing 1–50 of 50 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
92.8%
Outcome
Completed
Attacking impact
0.0001
Value before
0.0091
Value after
0.0092
Length
14.9 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.

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

Mario Götze

Eintracht Frankfurt · Right Defensive Midfield

Style similarity

67.8 / 100

Expected Completion RatePositive Forward Distance Per 100 PassesLong Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#2 · Same position group

Florian Wirtz

Bayer Leverkusen · Left Attacking Midfield

Style similarity

60.2 / 100

Actual vs. expected passing
+26.0 pp

Limited sample — interpret this split cautiously.

Expected Completion RatePositive Forward Distance Per 100 PassesLong Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 32 matches

#3 · Same position group

Grischa Prömel

Hoffenheim · Left Center Midfield

Style similarity

56.9 / 100

Pressure Pass RateCarry Share Of ActionsExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#4 · Same position group

Leandro Barreiro Martins

FSV Mainz 05 · Right Defensive Midfield

Style similarity

56.9 / 100

Pressure Pass RateLong Pass RateExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#5 · Same position group

Patrick Osterhage

Bochum · Center Defensive Midfield

Style similarity

56.5 / 100

Long Pass RatePositive Forward Distance Per 100 PassesPressure Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#6 · Same position group

Amine Adli

Bayer Leverkusen · Left Attacking Midfield

Style similarity

56.4 / 100

Long Pass RateExpected Completion RatePressure Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 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.