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FootyScout · Football scouting and analytics

Based on available StatsBomb 2023/24 Bundesliga event data.

Player profile

Jonas Hofmann

Bayer Leverkusen · Right Attacking Midfield · MID

Matches observed32
Pass attempts1,528
Reliable sample

Actual completion

81.1%

1,239 completed passes

Pass difficulty

83.6%

How difficult a pass was to complete.

Actual vs. expected passing

-2.5 pp

-37.8 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

83.6%

17th percentile among MID players

n = 13 eligible peers · sample 1528

Under-pressure pass rate

12.4%

17th percentile among MID players

n = 13 eligible peers · sample 1528

Progressive pass rate

18.9%

100th percentile among MID players

n = 13 eligible peers · sample 1528

Long-pass rate

15.0%

83rd percentile among MID players

n = 13 eligible peers · sample 1528

Average forward distance

-1.5 units

0th percentile among MID players

n = 13 eligible peers · sample 1528

Positive forward distance / 100 passes

415.9 units

8th percentile among MID players

n = 13 eligible peers · sample 1528

Final-third entries / 100 passes

7.134

33rd percentile among MID players

n = 13 eligible peers · sample 1528

Carry share of actions

43.9%

32nd percentile among MID players

n = 61 eligible peers · sample 2675

Progressive carry rate

4.7%

63rd percentile among MID players

n = 66 eligible peers · sample 1173

Progressive action rate

12.5%

73rd percentile among MID players

n = 61 eligible peers · sample 2675

Under-pressure action rate

18.4%

23rd percentile among MID players

n = 61 eligible peers · sample 2675

Shots / observed match

1.94 / match

Unavailable among MID players

n = 5 eligible peers · sample 62

requires 10 eligible position peers

xG / shot

9.2%

Unavailable among MID players

n = 5 eligible peers · sample 62

requires 10 eligible position peers

Performance

Observed execution or model-derived output relative to opportunities.

Actual vs. expected passing

-2.5 pp

8th percentile among MID players

n = 13 eligible peers · sample 1528

Under-pressure completion above expected

-5.9 pp

11th percentile among MID players

n = 10 eligible peers · sample 190

Progressive completion above expected

-5.5 pp

Unavailable among MID players

n = 9 eligible peers · sample 289

requires 10 eligible position peers

Long-pass completion above expected

-2.7 pp

Unavailable among MID players

n = 9 eligible peers · sample 229

requires 10 eligible position peers

Goals above expected

-1.707

Unavailable among MID players

n = 5 eligible peers · sample 62

requires 10 eligible position peers

Overall impact / 100 actions

-0.058

22nd percentile among MID players

n = 61 eligible peers · sample 2675

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

Passing impact / 100 passes

-0.200

18th percentile among MID players

n = 58 eligible peers · sample 1502

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

Carrying impact / 100 carries

0.123

62nd percentile among MID players

n = 66 eligible peers · sample 1173

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

Progressive-action impact / 100 actions

0.043

65th percentile among MID players

n = 61 eligible peers · sample 2675

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

Under-pressure impact / 100 actions

0.014

23rd percentile among MID players

n = 61 eligible peers · sample 2675

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

Playing style

Direct Progressor

Position-relative style among eligible MID players.

Style separation0.180

↑Progressive-pass rate (higher)

↓Pass difficulty (lower)

↑Positive forward distance / 100 passes (higher)

↑Long-pass rate (higher)

Pass difficulty-0.56 z
Under-pressure pass rate-0.73 z
Progressive-pass rate+0.98 z
Long-pass rate+0.48 z
Positive forward distance / 100 passes-1.40 z
Carry share of actions-0.48 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 closer1.045
CloserFarther

Strongest alignment

  • Pressure Pass Rate
  • Carry Share Of Actions
  • Long Pass Rate

Largest difference

Positive Forward Distance Per 100 Passes

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

62

26 matches observed

Goals

4

Total xG

5.7

Goals above expected

-1.7

xG / shot

0.1

6.5% goals / shot

Campos visualization

Shot map

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

Shots62
Goals4
xG5.71
xG0.00 – 1.00
Foot
Header
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

-0.058

Passing impact / 100 passes

-0.200

Carrying impact / 100 carries

+0.123

Progressive-action impact / 100 actions

+0.043

Under-pressure impact / 100 actions

+0.014

2,675 actions · 1,502 passes · 1,173 carries · 43.3% 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

190 attempts

Reliable sample
Actual
75.8%
Pass difficulty
81.7%
Actual vs. expected passing
-5.9 pp

Progressive passing

289 attempts

Reliable sample
Actual
47.1%
Pass difficulty
52.5%
Actual vs. expected passing
-5.5 pp

Long passing

229 attempts

Reliable sample
Actual
59.4%
Pass difficulty
62.1%
Actual vs. expected passing
-2.7 pp

Progression profile

Progressive-pass rate

18.9%

Pressure-pass rate

12.4%

Average forward distance

-1.5 m

Positive forward distance / 100

415.9 m

Final-third entries / 100

7.1

Campos visualization

Pass map

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

Showing 1–200 of 1,528 passes

Pass subset

CompletedIncompleteStronger line = greater pass difficultyThicker line = progressive or under pressure
Pass difficulty
97.9%
Outcome
Completed
Attacking impact
-0.0026
Value before
0.0155
Value after
0.0129
Length
8.4 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

Mario Götze

Eintracht Frankfurt · Right Defensive Midfield

Style similarity

68.8 / 100

Carry Share Of ActionsExpected Completion RateProgressive Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 32 vs 2 matches

#2 · Same position group

Yannick Gerhardt

Wolfsburg · Right Center Midfield

Style similarity

67.8 / 100

Expected Completion RatePressure Pass Rate
Long Pass Rate

Sample support: Limited · 2 limiting matches

Observed: 32 vs 2 matches

#3 · Same position group

Angelo Stiller

VfB Stuttgart · Left Defensive Midfield

Style similarity

63.4 / 100

Long Pass RateCarry Share Of ActionsExpected Completion Rate

Sample support: Limited · 1 limiting matches

Observed: 32 vs 1 matches

#4 · Same position group

Florian Neuhaus

Borussia Mönchengladbach · Left Defensive Midfield

Style similarity

61.5 / 100

Expected Completion RatePressure Pass RateCarry Share Of Actions

Sample support: Limited · 2 limiting matches

Observed: 32 vs 2 matches

#5 · Same position group

Joshua Kimmich

Bayern Munich · Right Defensive Midfield

Style similarity

60.2 / 100

Progressive Pass RatePressure Pass RateExpected Completion Rate

Sample support: Limited · 2 limiting matches

Observed: 32 vs 2 matches

#6 · Same position group

Julian Brandt

Borussia Dortmund · Center Attacking Midfield

Style similarity

59.4 / 100

Positive Forward Distance Per 100 PassesExpected Completion RateCarry Share Of Actions

Sample support: Limited · 2 limiting matches

Observed: 32 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.