Pass difficulty
86.5%
41st percentile among DEF players
n = 23 eligible peers · sample 119
Player profile
Bayern Munich · Center Back · DEF
Actual completion
84.0%
100 completed passes
Pass difficulty
86.5%
How difficult a pass was to complete.
Actual vs. expected passing
-2.5 pp
-3.0 completions vs model expectation
Actual pass completion compared with the model's expected completion.
Player intelligence
DEF context · Each percentile is an empirical rank among eligible players in the same broad position group. Percentiles are not ratings.
Tendencies describe what a player attempts; higher is not automatically better.
Pass difficulty
86.5%
41st percentile among DEF players
n = 23 eligible peers · sample 119
Under-pressure pass rate
10.1%
32nd percentile among DEF players
n = 23 eligible peers · sample 119
Progressive pass rate
11.8%
45th percentile among DEF players
n = 23 eligible peers · sample 119
Long-pass rate
19.3%
73rd percentile among DEF players
n = 23 eligible peers · sample 119
Average forward distance
11.6 units
100th percentile among DEF players
n = 23 eligible peers · sample 119
Positive forward distance / 100 passes
1286.1 units
100th percentile among DEF players
n = 23 eligible peers · sample 119
Final-third entries / 100 passes
12.605
95th percentile among DEF players
n = 23 eligible peers · sample 119
Carry share of actions
45.9%
75th percentile among DEF players
n = 94 eligible peers · sample 205
Progressive carry rate
3.2%
62nd percentile among DEF players
n = 87 eligible peers · sample 94
Progressive action rate
8.3%
43rd percentile among DEF players
n = 94 eligible peers · sample 205
Under-pressure action rate
7.3%
13th percentile among DEF players
n = 94 eligible peers · sample 205
Shots / observed match
0.00 / match
Unavailable among DEF players
n = 4 eligible peers · sample 0
requires 20 shots
xG / shot
—
Unavailable among DEF players
n = 4 eligible peers · sample 0
metric unavailable
Observed execution or model-derived output relative to opportunities.
Actual vs. expected passing
-2.5 pp
9th percentile among DEF players
n = 23 eligible peers · sample 119
Under-pressure completion above expected
-10.6 pp
Unavailable among DEF players
n = 13 eligible peers · sample 12
requires 20 pressure passes
Progressive completion above expected
-7.7 pp
Unavailable among DEF players
n = 17 eligible peers · sample 14
requires 20 progressive passes
Long-pass completion above expected
-5.4 pp
15th percentile among DEF players
n = 21 eligible peers · sample 23
Goals above expected
0.000
Unavailable among DEF players
n = 4 eligible peers · sample 0
requires 20 shots
Overall impact / 100 actions
0.020
55th percentile among DEF players
n = 94 eligible peers · sample 205
Weak split-half stability in the current 34-match product cohort.
Passing impact / 100 passes
-0.017
59th percentile among DEF players
n = 94 eligible peers · sample 111
Weak split-half stability in the current 34-match product cohort.
Carrying impact / 100 carries
0.064
50th percentile among DEF players
n = 87 eligible peers · sample 94
Moderate split-half stability; descriptive rather than latent ability.
Progressive-action impact / 100 actions
-0.038
19th percentile among DEF players
n = 94 eligible peers · sample 205
Weak split-half stability in the current 34-match product cohort.
Under-pressure impact / 100 actions
0.017
49th percentile among DEF players
n = 94 eligible peers · sample 205
Weak split-half stability in the current 34-match product cohort.
Playing style
Position-relative style among eligible DEF players.
Progressive-pass rate (higher)
Pass difficulty (lower)
Positive forward distance / 100 passes (higher)
Long-pass rate (higher)
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.
Role Fit
How closely a player's playing style matches this role. Compared with Bayer Leverkusen's observed DEF role.
Lower distance means closer stylistic resemblance.
Forward distance per 100 passes
Role Fit compares observed playing style. It does not predict player quality, transfer success, or future performance.
Attacking impact
Measures how much each pass or carry changed the expected attacking value of a possession. Positive values improved the attack; negative values reduced it.
Overall impact / 100 actions
+0.020
Passing impact / 100 passes
-0.017
Carrying impact / 100 carries
+0.064
Progressive-action impact / 100 actions
-0.038
Under-pressure impact / 100 actions
+0.017
205 actions · 111 passes · 94 carries · 67.8% increased attacking value
Campos visualization
Exact StatsBomb carry start/end locations. Green increases modeled possession value; coral decreases it.
12 attempts
Limited sample — interpret this split cautiously.
14 attempts
Limited sample — interpret this split cautiously.
23 attempts
Progressive-pass rate
11.8%
Pressure-pass rate
10.1%
Average forward distance
11.6 m
Positive forward distance / 100
1286.1 m
Final-third entries / 100
12.6
Campos visualization
Attacking left to right. Switch between xPass execution difficulty and possession attacking impact.
Showing 1–119 of 119 passes
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.
Style similarity
78.6 / 100
Sample support: Limited · 1 limiting matches
Observed: 1 vs 2 matches
Style similarity
75.9 / 100
Sample support: Limited · 1 limiting matches
Observed: 1 vs 1 matches
Style similarity
74.9 / 100
Sample support: Limited · 1 limiting matches
Observed: 1 vs 2 matches
Style similarity
74.5 / 100
Sample support: Limited · 1 limiting matches
Observed: 1 vs 2 matches
Style similarity
73.9 / 100
Sample support: Limited · 1 limiting matches
Observed: 1 vs 2 matches
Style similarity
71.1 / 100
Sample support: Limited · 1 limiting matches
Observed: 1 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.