KFUM Oslo 1:2 Sandefjord Fotball: xG & match report · Eliteserien

Tuesday, 07/04/2026 at 19:00

Full time

Match report · Eliteserien

KFUM Oslo Home 0.55 xG · 9 shots

Sandefjord Fotball Away 1.89 xG · 13 shots

12 The scoreline reflected the chances

Goals

5' Jakob Vester Sandefjord Fotball · 0.32 xG chance 0–1
16' Teodor Haltvik KFUM Oslo · 0.10 xG chance 1–1
30' Evangelos Patoulidis (pen.) Sandefjord Fotball · 0.82 xG chance 1–2

The shots behind it

KFUM Oslo Sandefjord Fotball

Shots: 9; 13
On target: 1; 5
Inside the box: 8; 9
xG per shot: 0.07; 0.13
Open play xG: 0.21; 0.50
Set-piece xG: 0.40; 0.40
Penalties: 0; 1

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: 0.59 for KFUM Oslo and 0.91 for Sandefjord Fotball.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

22 shots · 2.33 xG

Hover, focus or tap a shot to read it.

KFUM Oslo
Sandefjord Fotball
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

KFUM Oslo

1.55 xG created 1.41 xGA

L 4.73 created, 2.57 conceded against Haugesund
D 0.81 created, 1.22 conceded against SK Brann
L 0.97 created, 1.53 conceded against Bodø/Glimt
L 0.50 created, 1.23 conceded against Sandefjord Fotball
W 1.15 created, 0.40 conceded against IK Start
L 1.14 created, 1.53 conceded against Fredrikstad FK

Sandefjord Fotball

1.74 xG created 1.58 xGA

L 2.08 created, 2.47 conceded against HamKam
W 0.49 created, 1.78 conceded against Tromsø IL
W 3.76 created, 1.73 conceded against Strømsgodset
W 1.23 created, 0.50 conceded against KFUM Oslo
L 1.78 created, 1.17 conceded against Vålerenga IF
L 1.13 created, 1.83 conceded against Sarpsborg 08

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

Head to head

KFUM Oslo: 1 won · 0 drawn · 1 lost

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.