FSFootyScout
PlayersTeam IntelligenceScoutingLeaderboardCompareArchetypesModel

FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Maximilian Arnold

Wolfsburg · Center Defensive Midfield · MID

Matches observed2
Pass attempts96
Limited sample

Actual completion

87.5%

84 completed passes

Pass difficulty

87.7%

How difficult a pass was to complete.

Actual vs. expected passing

-0.2 pp

-0.2 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

87.7%

Unavailable among MID players

n = 13 eligible peers · sample 96

requires 100 passes

Under-pressure pass rate

15.6%

Unavailable among MID players

n = 13 eligible peers · sample 96

requires 100 passes

Progressive pass rate

14.6%

Unavailable among MID players

n = 13 eligible peers · sample 96

requires 100 passes

Long-pass rate

27.1%

Unavailable among MID players

n = 13 eligible peers · sample 96

requires 100 passes

Average forward distance

0.5 units

Unavailable among MID players

n = 13 eligible peers · sample 96

requires 100 passes

Positive forward distance / 100 passes

651.5 units

Unavailable among MID players

n = 13 eligible peers · sample 96

requires 100 passes

Final-third entries / 100 passes

10.417

Unavailable among MID players

n = 13 eligible peers · sample 96

requires 100 passes

Carry share of actions

39.1%

0th percentile among MID players

n = 61 eligible peers · sample 151

Progressive carry rate

0.0%

12th percentile among MID players

n = 66 eligible peers · sample 59

Progressive action rate

9.3%

57th percentile among MID players

n = 61 eligible peers · sample 151

Under-pressure action rate

19.2%

30th percentile among MID players

n = 61 eligible peers · sample 151

Shots / observed match

0.50 / match

Unavailable among MID players

n = 5 eligible peers · sample 1

requires 20 shots

xG / shot

3.6%

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

-0.2 pp

Unavailable among MID players

n = 13 eligible peers · sample 96

requires 100 passes

Under-pressure completion above expected

-1.7 pp

Unavailable among MID players

n = 10 eligible peers · sample 15

requires 20 pressure passes

Progressive completion above expected

-10.3 pp

Unavailable among MID players

n = 9 eligible peers · sample 14

requires 20 progressive passes

Long-pass completion above expected

-3.8 pp

Unavailable among MID players

n = 9 eligible peers · sample 26

requires 10 eligible position peers

Goals above expected

-0.036

Unavailable among MID players

n = 5 eligible peers · sample 1

requires 20 shots

Overall impact / 100 actions

-0.067

15th percentile among MID players

n = 61 eligible peers · sample 151

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

Passing impact / 100 passes

-0.159

30th percentile among MID players

n = 58 eligible peers · sample 92

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

Carrying impact / 100 carries

0.077

42nd percentile among MID players

n = 66 eligible peers · sample 59

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

Progressive-action impact / 100 actions

-0.072

5th percentile among MID players

n = 61 eligible peers · sample 151

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

Under-pressure impact / 100 actions

0.031

50th percentile among MID players

n = 61 eligible peers · sample 151

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

Playing style

Direct Progressor

Position-relative style among eligible MID players.

Style separation0.341

↑Progressive-pass rate (higher)

↓Pass difficulty (lower)

↑Positive forward distance / 100 passes (higher)

↑Long-pass rate (higher)

Pass difficulty+0.34 z
Under-pressure pass rate-0.17 z
Progressive-pass rate+0.31 z
Long-pass rate+2.74 z
Positive forward distance / 100 passes+0.47 z
Carry share of actions-1.83 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 closer1.559
CloserFarther

Strongest alignment

  • Pressure Pass Rate
  • Expected Completion Rate
  • Progressive Pass Rate

Largest difference

Long 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

0.0

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

-0.067

Passing impact / 100 passes

-0.159

Carrying impact / 100 carries

+0.077

Progressive-action impact / 100 actions

-0.072

Under-pressure impact / 100 actions

+0.031

151 actions · 92 passes · 59 carries · 52.3% 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

15 attempts

Limited sample
Actual
86.7%
Pass difficulty
88.4%
Actual vs. expected passing
-1.7 pp

Limited sample — interpret this split cautiously.

Progressive passing

14 attempts

Limited sample
Actual
35.7%
Pass difficulty
46.0%
Actual vs. expected passing
-10.3 pp

Limited sample — interpret this split cautiously.

Long passing

26 attempts

Reliable sample
Actual
69.2%
Pass difficulty
73.0%

Progression profile

Progressive-pass rate

14.6%

Pressure-pass rate

15.6%

Average forward distance

0.5 m

Positive forward distance / 100

651.5 m

Final-third entries / 100

10.4

Campos visualization

Pass map

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

Showing 1–96 of 96 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
99.0%
Outcome
Completed
Attacking impact
0.0001
Value before
0.0065
Value after
0.0066
Length
19.0 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

Joshua Kimmich

Bayern Munich · Right Defensive Midfield

Style similarity

64.7 / 100

Positive Forward Distance Per 100 PassesExpected Completion RateProgressive Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#2 · Same position group

Lennard Maloney

FC Heidenheim · Right Defensive Midfield

Style similarity

56.5 / 100

Actual vs. expected passing
-3.8 pp
Pressure Pass RatePositive Forward Distance Per 100 PassesLong Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#3 · Same position group

Grischa Prömel

Hoffenheim · Left Center Midfield

Style similarity

55.5 / 100

Expected Completion RateProgressive Pass RateCarry Share Of Actions

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#4 · Same position group

Ellyes Joris Skhiri

Eintracht Frankfurt · Left Defensive Midfield

Style similarity

55.3 / 100

Positive Forward Distance Per 100 PassesPressure Pass RateProgressive Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#5 · Same position group

Julian Weigl

Borussia Mönchengladbach · Right Defensive Midfield

Style similarity

52.2 / 100

Positive Forward Distance Per 100 PassesCarry Share Of ActionsExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 2 vs 2 matches

#6 · Same position group

Angelo Stiller

VfB Stuttgart · Left Defensive Midfield

Style similarity

52.1 / 100

Progressive Pass RatePositive Forward Distance Per 100 PassesExpected Completion Rate

Sample support: Limited · 1 limiting matches

Observed: 2 vs 1 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.