← Match Finder
OBOS-ligaen
Referee: M Støfringshaug
KFUM Oslo
T U T S T
0–2
Full-time
Ham-Kam
U U U S S

Retrospective analysis — the model is trained only on matches played before this one.

🔒 Who wins? Pro

The model's probabilities for a home win, draw and away win — with reasoning and recommended markets.

Unlock with Pro

Already have an account? Log in

Team trends

KFUM Oslo Ham-Kam
Last 6 — all competitions · 6/6 matches
Win Ø 34%
17%
50%
Points per game
0,8
2,0
Over 2.5 Ø 50%
50%
50%
Both score Ø 67%
50%
83%
Average goals
4,0
2,8
Scored
2,0
2,0
Conceded
2,0
0,8
Goal diff per game
+0,0
+1,2
🔒 Goal markets Pro

Expected goals, over/under and both teams to score — priced by the model before kick-off.

Unlock with Pro

Already have an account? Log in

🔒 Most likely result Pro

The model's top final scores with the best bookmaker odds.

Unlock with Pro

Already have an account? Log in

Match report

KFUM Oslo Ham-Kam
22′
K. Eriksen 0–1
36′
🟨 A. Melgalvis
Half-time 0–1
P. Romsaas 🔁
↦ H. Hoseth
46′
A. Olsen 🟨
64′
65′
🔁 E. Sildnes
↦ A. Berisha
R. Svindland 🔁
↦ K. Ghaedamini
67′
D. Tavakoli 🔁
↦ A. Sanyang
75′
88′
🔁 D. Arzani
↦ M. Bjørlo
91′
🟨 J. Faye Lund
92′
🔁 H. Rødølen
↦ K. Onsrud
93′
Rubén Alegre 0–2
Full-time 0–2

Line-ups

KFUM Oslo

12 K. Skjærstein
2 K. Ghaedamini
3 D. Gaye
25 J. Taaje
17 F. Dahl
5 A. Olsen
8 S. Sortevik
27 M. Mahnin
21 T. Sørås
14 H. Hoseth
10 A. Sanyang
Bench (7)
19 P. Romsaas
26 R. Svindland
9 D. Tavakoli
18 A. Pedersen
20 J. Moula
23 K. Aarstad
24 C. Lindquist

Coach: J. Isnes

Ham-Kam

31 J. Lund
5 S. Strømnes
13 Rubén Alegre
58 H. Kuruçay
33 A. Melgalvis
7 K. Onsrud
6 K. Eriksen
11 M. Bjørlo
53 A. Berisha
8 V. Skjærvik
9 J. Enkerud
Bench (7)
10 E. Sildnes
25 D. Arzani
14 H. Rødølen
12 Ł. Jarosiński
18 N. Rekdal
20 J. Matland
24 E. Munkelien

Coach: K. Rekdal

Odds comparison

Green columns are the outcomes that came in.

Over/under goals
O1,5 ✓
U2,5 ✓
U3,5 ✓
Both teams to score
BLS ja
BLS nei ✓

Referee

M Støfringshaug · 64 kamper i vår database

🟥 Red cards: 0,10 per match

The analysis is a statistical estimate based on the teams' results and underlying performances (xG) — not a guarantee. See the model's results.