FSFootyScout
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FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Angelo Stiller

VfB Stuttgart · Left Defensive Midfield · MID

Matches observed1
Pass attempts79
Limited sample

Actual completion

88.6%

70 completed passes

Pass difficulty

85.6%

How difficult a pass was to complete.

Actual vs. expected passing

+3.0 pp

+2.4 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.

Insufficient eligible position metrics for a meaningful radar.

Style

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

Pass difficulty

85.6%

Unavailable among MID players

n = 13 eligible peers · sample 79

requires 100 passes

Under-pressure pass rate

7.6%

Unavailable among MID players

n = 13 eligible peers · sample 79

requires 100 passes

Progressive pass rate

13.9%

Unavailable among MID players

n = 13 eligible peers · sample 79

requires 100 passes

Long-pass rate

15.2%

Unavailable among MID players

n = 13 eligible peers · sample 79

requires 100 passes

Average forward distance

2.1 units

Unavailable among MID players

n = 13 eligible peers · sample 79

requires 100 passes

Positive forward distance / 100 passes

625.3 units

Unavailable among MID players

n = 13 eligible peers · sample 79

requires 100 passes

Final-third entries / 100 passes

11.392

Unavailable among MID players

n = 13 eligible peers · sample 79

requires 100 passes

Carry share of actions

43.6%

27th percentile among MID players

n = 61 eligible peers · sample 133

Progressive carry rate

3.4%

52nd percentile among MID players

n = 66 eligible peers · sample 58

Progressive action rate

9.8%

62nd percentile among MID players

n = 61 eligible peers · sample 133

Under-pressure action rate

14.3%

7th percentile among MID players

n = 61 eligible peers · sample 133

Shots / observed match

1.00 / match

Unavailable among MID players

n = 5 eligible peers · sample 1

requires 20 shots

xG / shot

3.9%

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

+3.0 pp

Unavailable among MID players

n = 13 eligible peers · sample 79

requires 100 passes

Under-pressure completion above expected

-1.6 pp

Unavailable among MID players

n = 10 eligible peers · sample 6

requires 20 pressure passes

Progressive completion above expected

+4.2 pp

Unavailable among MID players

n = 9 eligible peers · sample 11

requires 20 progressive passes

Long-pass completion above expected

+9.5 pp

Unavailable among MID players

n = 9 eligible peers · sample 12

requires 20 long passes

Goals above expected

-0.039

Unavailable among MID players

n = 5 eligible peers · sample 1

requires 20 shots

Overall impact / 100 actions

0.035

70th percentile among MID players

n = 61 eligible peers · sample 133

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

Passing impact / 100 passes

-0.054

61st percentile among MID players

n = 58 eligible peers · sample 75

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

Carrying impact / 100 carries

0.149

72nd percentile among MID players

n = 66 eligible peers · sample 58

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

Progressive-action impact / 100 actions

-0.024

23rd percentile among MID players

n = 61 eligible peers · sample 133

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

Under-pressure impact / 100 actions

0.042

65th percentile among MID players

n = 61 eligible peers · sample 133

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

Playing style

Direct Progressor

Position-relative style among eligible MID players.

Style separation0.357

↑Progressive-pass rate (higher)

↓Pass difficulty (lower)

↑Positive forward distance / 100 passes (higher)

↑Long-pass rate (higher)

Pass difficulty-0.11 z
Under-pressure pass rate-1.57 z
Progressive-pass rate+0.21 z
Long-pass rate+0.52 z
Positive forward distance / 100 passes+0.27 z
Carry share of actions-0.55 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 closer0.797
CloserFarther

Strongest alignment

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

Largest difference

Pressure Pass Rate

limited sampleObserved across 1 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

0.0

Goals above expected

-0.0

xG / shot

0.0

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
xG0.04
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

+0.035

Passing impact / 100 passes

-0.054

Carrying impact / 100 carries

+0.149

Progressive-action impact / 100 actions

-0.024

Under-pressure impact / 100 actions

+0.042

133 actions · 75 passes · 58 carries · 54.9% 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

6 attempts

Limited sample
Actual
83.3%
Pass difficulty
84.9%
Actual vs. expected passing
-1.6 pp

Limited sample — interpret this split cautiously.

Progressive passing

11 attempts

Limited sample
Actual
36.4%
Pass difficulty
32.2%
Actual vs. expected passing
+4.2 pp

Limited sample — interpret this split cautiously.

Long passing

12 attempts

Limited sample
Actual
58.3%
Pass difficulty
48.8%

Progression profile

Progressive-pass rate

13.9%

Pressure-pass rate

7.6%

Average forward distance

2.1 m

Positive forward distance / 100

625.3 m

Final-third entries / 100

11.4

Campos visualization

Pass map

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

Showing 1–79 of 79 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
99.4%
Outcome
Completed
Attacking impact
-0.0000
Value before
0.0068
Value after
0.0068
Length
16.1 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.

Limited sample: this player's style profile is based on 1 observed match, so nearest-neighbor rankings may be less stable.

#1 · Same position group

Joshua Kimmich

Bayern Munich · Right Defensive Midfield

Style similarity

75.1 / 100

Positive Forward Distance Per 100 PassesExpected Completion RatePressure Pass Rate

Sample support: Limited · 1 limiting matches

Observed: 1 vs 2 matches

#2 · Same position group

Florian Neuhaus

Borussia Mönchengladbach · Left Defensive Midfield

Style similarity

72.6 / 100

Actual vs. expected passing
+9.5 pp

Limited sample — interpret this split cautiously.

Expected Completion RateProgressive Pass RatePositive Forward Distance Per 100 Passes

Sample support: Limited · 1 limiting matches

Observed: 1 vs 2 matches

#3 · Same position group

Robert Andrich

Bayer Leverkusen · Right Defensive Midfield

Style similarity

69.8 / 100

Carry Share Of ActionsPositive Forward Distance Per 100 PassesProgressive Pass Rate

Sample support: Limited · 1 limiting matches

Observed: 1 vs 28 matches

#4 · Same position group

Xaver Schlager

RB Leipzig · Left Defensive Midfield

Style similarity

67.4 / 100

Pressure Pass RatePositive Forward Distance Per 100 PassesExpected Completion Rate

Sample support: Limited · 1 limiting matches

Observed: 1 vs 2 matches

#5 · Same position group

Yannick Gerhardt

Wolfsburg · Right Center Midfield

Style similarity

67.2 / 100

Progressive Pass RateLong Pass RatePositive Forward Distance Per 100 Passes

Sample support: Limited · 1 limiting matches

Observed: 1 vs 2 matches

#6 · Same position group

Julian Weigl

Borussia Mönchengladbach · Right Defensive Midfield

Style similarity

66.6 / 100

Positive Forward Distance Per 100 PassesLong Pass RatePressure Pass Rate

Sample support: Limited · 1 limiting matches

Observed: 1 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.