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OBOS-ligaen
Referee: E Bodding
KFUM Oslo
U U T S S
2–1
Full-time
Jerv
T T T T T

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.

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Team trends

KFUM Oslo Jerv
Last 6 — all competitions · 6/6 matches
Win Ø 17%
33%
0%
Points per game
1,3
0,2
Over 2.5 Ø 25%
17%
33%
Both score Ø 25%
17%
33%
Average goals
1,3
3,0
Scored
0,8
0,3
Conceded
0,5
2,7
Goal diff per game
+0,3
-2,3
🔒 Goal markets Pro

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

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🔒 Most likely result Pro

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

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Recent head-to-head meetings

21. Aug -19 Jerv – KFUM Oslo 2–2 5. May -19 KFUM Oslo – Jerv 5–0 16. Oct -16 KFUM Oslo – Jerv 0–1 17. Apr -16 Jerv – KFUM Oslo 1–1

Match report

KFUM Oslo Jerv
33′
⚽ D. Campos 0–1
Half-time 0–1
M. Gueye 🟨
51′
1–1 D. Tavakoli ⚽
57′
F. Kastrati 🔁
↦ A. Sanyang
58′
O. Øby 🔁
↦ H. Hoseth
58′
H. Stavrum 🟨
70′
73′
🔁 J. Solli
↦ A. Latifu
M. Mahnin 🔁
↦ D. Holm
77′
85′
🔁 A. Dang
↦ Pibe
89′
🔁 J. Myhre
↦ D. Campos
2–1 O. Øby ⚽
89′
C. Lindquist 🔁
↦ D. Tavakoli
90′
J. Moula 🔁
↦ H. Stavrum
94′
Full-time 2–1

Line-ups

KFUM Oslo

1 S. Thomas
28 E. Troudart
3 D. Gaye
15 M. Gueye
17 F. Dahl
6 D. Holm
8 S. Sortevik
37 H. Stavrum
14 H. Hoseth
11 D. Tavakoli
10 A. Sanyang
Bench (7)
16 F. Kastrati
22 O. Øby
27 M. Mahnin
20 J. Moula
24 C. Lindquist
18 A. Pedersen
19 Y. Moula

Coach: J. Isnes

Jerv

20 Ø. Øvretveit
15 A. Latifu
3 B. Hove
19 I. Mafi
6 M. Wichmann
8 T. Zernichow
11 D. Aase
9 D. Campos
13 H. Suggelia
39 Pibe
23 O. Håbestad
Bench (7)
18 J. Solli
10 A. Dang
28 J. Myhre
1 B. Boujar
80 M. Baidoo
17 A. Hagen
32 M. Abdalhalim

Coach: A. Sandstø

Odds comparison

Green columns are the outcomes that came in.

Over/under goals
O1,5 ✓
–
🔒
U1,5
–
🔒
O2,5 ✓
–
🔒
U2,5
–
🔒
O3,5
–
🔒
U3,5 ✓
–
🔒
Both teams to score
BLS ja ✓
–
🔒
BLS nei
–
🔒

Recent matches

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