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OBOS-ligaen
Sandefjord
S T S U T
1–0
Full-time
KFUM Oslo
T S T T T

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

⚠️ One of the teams has played few league matches recently (e.g. newly promoted). The analysis is therefore more uncertain than usual, and we give no recommendations for this match.
🔒 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

Sandefjord KFUM Oslo
Last 6 — all competitions · 6/6 matches
Win Ø 25%
33%
17%
Points per game
1,3
0,5
Over 2.5 Ø 59%
67%
50%
Both score Ø 59%
100%
17%
Average goals
3,5
2,3
Scored
1,8
0,7
Conceded
1,7
1,7
Goal diff per game
+0,2
-1,0
🔒 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

14. Aug -16 Sandefjord – KFUM Oslo 3–0 29. Jun -16 KFUM Oslo – Sandefjord 1–2

Match report

Sandefjord KFUM Oslo
Half-time 0–0
53′
🔁 O. Øby
↦ A. Agouda
T. Svendsen 🔁
↦ H. Storbæk
61′
65′
🔁 F. Kastrati
↦ D. Holm
S. Mladenovic 🔁
↦ V. Jonsson
67′
83′
🔁 J. Moula
↦ M. Mawa
W. Kurtović 🔁
↦ E. Mjelde
87′
1–0 Tito ⚽
90′
Full-time 1–0

Line-ups

Sandefjord

12 W. Viitala
2 L. Grorud
13 M. Høibråten
23 V. Jonsson
19 B. Wembangomo
8 E. Mjelde
5 Enric Vallès
9 H. Storbæk
24 Tito
15 P. Engblom
6 M. Ofkir
Bench (7)
11 T. Svendsen
14 S. Mladenovic
18 W. Kurtović
3 S. Foss
4 C. Reppesgård
20 G. Gibson
99 J. Granlund

Coach: Martí Cifuentes

KFUM Oslo

12 K. Skjærstein
33 J. Hammer
28 E. Troudart
6 D. Holm
8 S. Sortevik
7 R. Rasch
21 T. Sørås
26 L. Larsen
31 K. Brix
9 A. Agouda
11 M. Mawa
Bench (7)
18 O. Øby
16 F. Kastrati
20 J. Moula
1 S. Thomas
4 K. Hagen
5 H. Aalmen
19 Y. Moula

Coach: J. Isnes

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.