xgEdge

Sunday, 13/09/2026 at 17:00

Full time
Match report · Eliteserien

KFUM Oslo 2:1 Aalesunds FK

KFUM Oslo Home 1.48 xG · 9 shots
Aalesunds FK Away 1.57 xG · 18 shots
21 The chances were evenly matched

KFUM Oslo were the model's likeliest winner before kick-off at 37%. They won 2–1. Both teams produced xG close to their pre-match projections.

Goals

  1. 10' Bilal Njie KFUM Oslo · 0.16 xG chance 1–0
  2. 39' Marcus Haagensen Reed Aalesunds FK · 0.07 xG chance 1–1
  3. 45' Hakon Helland Hoseth KFUM Oslo · 0.12 xG chance 2–1

The model against the result

priced before kick-off
KFUM Oslo
37% What happened
Draw
29%
Aalesunds FK
34%

Data coverage Both teams have the full 20-match model window available.

Projected vs produced

Expected goals
KFUM Oslo The model projected 1.45 Produced 1.48 Difference +0.03
Aalesunds FK The model projected 1.39 Produced 1.57 Difference +0.18

Projected before kick-off Produced on the night

The shots behind it

KFUM Oslo Aalesunds FK
Shots
9
18
On target
5
3
Inside the box
7
10
xG per shot
0.17
0.08
Open play xG
0.60
1.12
Set-piece xG
0.10
0.32
Penalties
1
0
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: 0.69 for KFUM Oslo and 1.43 for Aalesunds FK.

Shot map

Both teams shown attacking the same goal for comparison.

KFUM Oslo · Eirik Franke Saunes · 6' · No goal · 12 m · 0.82 xG Aalesunds FK · Marius Andresen · 29' · No goal · 4 m · 0.26 xG Aalesunds FK · Marcus Haagensen Reed · 23' · No goal · 6 m · 0.23 xG KFUM Oslo · Bjorn Martin Kristensen · 33' · No goal · 15 m · 0.18 xG Aalesunds FK · Uba Charles · 28' · No goal · 10 m · 0.17 xG KFUM Oslo · Bilal Njie · 10' · Goal · 14 m · 0.16 xG Aalesunds FK · Ólafur Guðmundsson · 73' · No goal · 4 m · 0.14 xG KFUM Oslo · Hakon Helland Hoseth · 45' · Goal · 12 m · 0.12 xG Aalesunds FK · Elias Kristoffersen Hagen · 23' · No goal · 11 m · 0.11 xG Aalesunds FK · Elias Kristoffersen Hagen · 19' · No goal · 20 m · 0.09 xG Aalesunds FK · Sander Erik Kartum · 53' · No goal · 18 m · 0.08 xG KFUM Oslo · Rasmus Eggen Vinge · 90' · No goal · 12 m · 0.08 xG Aalesunds FK · Marcus Haagensen Reed · 39' · Goal · 9 m · 0.07 xG KFUM Oslo · Ola Visted · 87' · No goal · 19 m · 0.06 xG Aalesunds FK · Mathias Christensen · 67' · No goal · 27 m · 0.05 xG KFUM Oslo · Martin Tangen Vinjor · 4' · No goal · 19 m · 0.04 xG Aalesunds FK · Elias Kristoffersen Hagen · 56' · No goal · 19 m · 0.04 xG KFUM Oslo · Bjorn Martin Kristensen · 69' · No goal · 14 m · 0.04 xG Aalesunds FK · Jakob Nyland Örsahl · 74' · No goal · 20 m · 0.04 xG Aalesunds FK · Sander Erik Kartum · 20' · No goal · 25 m · 0.03 xG Aalesunds FK · Marius Andresen · 50' · No goal · 14 m · 0.03 xG Aalesunds FK · Marcus Haagensen Reed · 51' · No goal · 25 m · 0.02 xG KFUM Oslo · Fredrik Tobias Berglie · 64' · No goal · 13 m · 0.02 xG Aalesunds FK · Uba Charles · 73' · No goal · 3 m · 0.02 xG Aalesunds FK · Elias Kristoffersen Hagen · 76' · No goal · 26 m · 0.02 xG Aalesunds FK · Marcus Haagensen Reed · 81' · No goal · 28 m · 0.02 xG Aalesunds FK · Luca Podlech · 90' · No goal · 15 m · 0.02 xG

All shots

27 shots · 2.96 xG

Hover, focus or tap a shot to read it.

  • KFUM Oslo
  • Aalesunds FK
  • Filled = goal
  • Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match
KFUM Oslo

1.15 xG created 2.36 xGA

  • L 0.69 created, 3.54 conceded against Molde FK
  • W 1.23 created, 1.22 conceded against Kristiansund BK
  • W 2.25 created, 1.33 conceded against Sandefjord Fotball
  • D 0.92 created, 2.80 conceded against Lillestrøm SK
  • L 1.65 created, 3.43 conceded against IK Start
  • L 0.18 created, 1.81 conceded against Molde FK
Aalesunds FK

1.78 xG created 2.06 xGA

  • D 1.98 created, 1.70 conceded against Viking FK
  • L 2.69 created, 1.86 conceded against Tromsø IL
  • D 0.63 created, 1.59 conceded against HamKam
  • D 2.08 created, 3.13 conceded against Vålerenga IF
  • L 0.87 created, 2.42 conceded against Viking FK
  • W 2.42 created, 1.67 conceded against IK Start

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

Head to head

KFUM Oslo: 0 won · 1 drawn · 0 lost

Pre-match model & market record

5 opportunities flagged1 won4 lost

  • Lost
  • Lost
  • Won
  • Lost
  • Lost
View pre-match record
The outcomes the model flagged on KFUM Oslo against Aalesunds FK before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection Price Edge Result
Draw 3.70 +9.0% Lost
Under 2.5 goals 2.40 +6.2% Lost
Aalesunds FK at most 1 goal 1.80 +4.9% Won
KFUM Oslo at most 1 goal 1.80 +1.3% Lost
Under 1.5 goals 5.50 +0.5% Lost

Pre-match model vs market

Outcome Model Market Difference Fair odds
KFUM Oslo 36.6% 39.5% −3.0 pp 2.73
Draw 29.5% 25.1% +4.4 pp 3.39
Aalesunds FK 34.0% 35.4% −1.4 pp 2.94

Other markets

Outcome Model Market Difference Fair odds
KFUM Oslo to score 79.1% 79.2% −0.1 pp 1.26
KFUM Oslo not to score 20.9% 20.8% +0.1 pp 4.79
Aalesunds FK to score 78.0% 79.2% −1.2 pp 1.28
Aalesunds FK not to score 22.0% 20.8% +1.2 pp 4.55
Both teams to score 63.4% 62.5% +0.9 pp 1.58
Both teams not to score 36.6% 37.5% −0.9 pp 2.73
KFUM Oslo 2+ goals 43.7% 48.5% −4.8 pp 2.29
KFUM Oslo at most 1 goal 56.3% 51.5% +4.8 pp 1.78
Aalesunds FK 2+ goals 41.7% 48.5% −6.8 pp 2.40
Aalesunds FK at most 1 goal 58.3% 51.5% +6.8 pp 1.72
Over 1.5 goals 81.7% 82.8% −1.1 pp 1.22
Under 1.5 goals 18.3% 17.2% +1.1 pp 5.47
Over 2.5 goals 55.7% 61.0% −5.3 pp 1.79
Under 2.5 goals 44.3% 39.0% +5.3 pp 2.26

Prices and probabilities are the ones stored before kick-off; nothing here is recalculated. Edge is the model's probability times the price, minus one, so a flagged outcome that lost is the ordinary case rather than a contradiction.

Model details

Show
Fit window
the last 20 matches, recency weighted (a match 107 days old counts half)
KFUM Oslo sample
20 matches
Aalesunds FK sample
20 matches
Computed
7 hours before kick-off
Prices taken
7 hours before kick-off

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.