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Manchester United

Aaron Wan-Bissaka

Defender28 yrs
75% chance
Non-penalty xG per 90
0.010 non-penalty goals from 3 shots
Expected assists per 90
0.072 assists, 12 key passes
Finishing
-0.14goals above what the league converts the same chances into
Build-up per 90
0.327% of Manchester United’s build-up value

Aaron Wan-Bissaka ranks 313th of 402 qualified players for attacking involvement, shooting from 19.7m on average.

75% chance. Hamstring injury - 75% chance of playing. Weigh the rates below against the chance he features at all. Club status as of 18 Oct 2026.

Against their position

135 defenders

Shooting

per 90
Goals
0.00
Non-penalty goals
0.00
xG
0.01
Non-penalty xG
0.01
Shots
0.15
npxG per shot
–not ranked
Shot distance
–not ranked
Set-piece share
–not ranked
Goals against xG
-0.1

2 figures here come from match-event data, which is not recorded for 2023/24.

Creating

per 90
Assists
0.10
Expected assists
0.07
Key passes
0.61
npxG + xA
0.08
xG chain
0.39
xG build-up
0.32
Assists against xA
+0.6

On the ball

per 90

6 figures here come from match-event data, which is not recorded for 2023/24.

Defending

per 90

7 figures here come from match-event data, which is not recorded for 2023/24.

Discipline

per 90
Yellow cards
4season count
Red cards
0season count

3 figures here come from match-event data, which is not recorded for 2023/24.

Ranked against 135 defenders with half a match a round or more, the same comparison the compare page makes. Where less is better, such as being dispossessed, the order is turned round, so a high percentile is always the good end.

This week

Gameweek 8

Next fixture

Gameweek 8

vs Manchester City

Sat 24 Oct, 11:30 UTC

Manchester City concede 7.8 shots a match and are 0.74× the league norm against defenders. A difficult one.

Projected shots
0.10

0.15 per 90 × 0.65

Projected on target
0.03

0.05 per 90 × 0.60

Season rate times what this opponent concedes, over a full ninety minutes. Check availability.

Shots

22 appearances
  • Over 0.53 of 2214%± 7
  • Over 1.50 of 220%± 0
  • Over 2.50 of 220%± 0
  • Over 3.50 of 220%± 0

The band is one standard error, the tick the estimate. Blanks count as misses, 19 of 22.

Shooting profile

3 shots

Where they shoot

3 shots
Every shotBy zone
33% of shots, 1 shot67% of shots, 2 shots33%67%Opponent goalLeftRight
Share of shots<1%1–2%2–4%4–6%6%+

Aaron Wan-Bissaka, 2023/24, final 35m.

left
0%
Centre
37%
right
63%

share of their shooting xG

Chance profile

quality, volume and route
xG per shot
0.049
Shots per 90
0.15
Key passes per 90
0.61
Average shot distance
19.7m
From set pieces
0%

How the chances arrive

Crosses
0%
Through balls
0%
Own dribble
0%
Headed
0%

Club role

Manchester United

What they are for

  • On the pitch52% of available minutes.

What would actually have to be replaced. Losing the penalty taker is not the same as losing a proportional slice of Aaron Wan-Bissaka’soutput.

Chances received

who supplies them
  1. Christian Eriksen0.1 xG1 shot, 0g
  2. Alejandro Garnacho0.0 xG1 shot, 0g

Chances created

who they supply
  1. Raphael Varane0.8 xG1 shot, 1g
  2. Alejandro Garnacho0.2 xG2 shots, 0g
  3. Antony0.1 xG2 shots, 0g
  4. Kobbie Mainoo0.1 xG2 shots, 1g
  5. Rasmus Højlund0.1 xG1 shot, 0g

Season record

2023/24

Involvement in build-up

excludes their own shots and final passes

Aaron Wan-Bissaka carries 6.6% of Manchester United’s build-up value.

  • Build-up per 900.324
    63% of defenders
  • Possession value per 900.390
    64% of defenders

Ranked against 135 defenders with a comparable sample. Build-up is the value of possessions a player was involved in, with their own shots and final passes removed, so it credits the work before the chance rather than the chance.

Match by match

Match log

22 appearances, oldest first

at Newcastle1 shot
0 on target

at Forest1 shot
1 on target

v Newcastle1 shot
0 on target

19 blanksno shot
not placed

Height is shots, solid is on target, and the dashed rule is the 1.5 line. The feed cannot date an appearance with no shot in it, so 19 sits at the end, counted but unplaced.

How to read the ties. Each rate ties back to the league average: solid where the sample is settled, broken where it is still being shrunk toward the league, an open circle where there is no cohort to rank against.