Norwich City 1:1 Oxford United: xG & match report · Championship

Tuesday, 25/11/2025 at 20:45

Full time

Match report · Championship

Norwich City Home 1.42 xG · 14 shots

Oxford United Away 0.82 xG · 12 shots

11 Norwich City had the better chances, but it finished level

Goals

29' Jovon Makama Norwich City · 0.14 xG chance 1–0
90' Filip Krastev Oxford United · 0.22 xG chance 1–1

The shots behind it

Norwich City Oxford United

Shots: 14; 12
On target: 5; 4
Inside the box: 10; 6
xG per shot: 0.10; 0.07
Open play xG: 1.01; 0.69
Set-piece xG: 0.40; 0.11
Penalties: —; —

Shot-level xG may differ from the published match total

The provider publishes the match total separately from its shot-by-shot values. Those values are rounded to two decimals and, leaving out penalties and own goals, add up to its non-penalty xG: 1.43 for Norwich City and 0.82 for Oxford United.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

26 shots · 2.21 xG

Hover or tap a shot, or step through them with the arrows.

Norwich City
Oxford United
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

Norwich City

1.34 xG created 1.65 xGA

L 1.11 created, 0.95 conceded against Derby County
L 1.17 created, 0.43 conceded against Swansea City
L 2.52 created, 1.26 conceded against Hull City
D 1.68 created, 2.08 conceded against Sheffield Wednesday
L 0.30 created, 1.59 conceded against Leicester City
L 1.28 created, 3.56 conceded against Birmingham City

Oxford United

0.84 xG created 1.54 xGA

L 0.15 created, 0.77 conceded against Wrexham
W 0.99 created, 1.16 conceded against Sheffield Wednesday
D 0.63 created, 2.42 conceded against Millwall
L 1.78 created, 2.19 conceded against Stoke City
L 0.95 created, 1.61 conceded against West Bromwich Albion
D 0.53 created, 1.06 conceded against Middlesbrough

xG created xG conceded (xGA) W / D / L: the match result

Model details

Show

The model never priced this match before kick-off, so there is no projection to read the result against.

Limitations

The model reads expected goals and nothing else. It does not know the lineups, who is injured or suspended, what either side has to play for, the weather, or how congested the schedule around this match is.