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OBOS-ligaen
Referee: E Bodding
KFUM Oslo
U T T U T
0–1
Full-time

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 Stjørdals-Blink
Last 6 — all competitions · 6/6 matches
Win Ø 9%
0%
17%
Points per game
0,5
1,0
Over 2.5 Ø 75%
67%
83%
Both score Ø 75%
67%
83%
Average goals
2,7
3,7
Scored
0,8
1,7
Conceded
1,8
2,0
Goal diff per game
-1,0
-0,3
This season — OBOS-ligaen · 11/11 matches
Win Ø 32%
27%
36%
Points per game
1,2
1,4
Over 2.5 Ø 78%
73%
82%
Both score Ø 82%
82%
82%
Average goals
2,9
3,8
Scored
1,4
1,9
Conceded
1,5
1,9
Goal diff per game
-0,2
+0,0
🔒 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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The table before the match KFUM Oslo 10. · Stjørdals-Blink 9.
# Team K V U T +/− P
1 Tromso 11 8 1 2 +11 25
2 Ranheim 10 8 0 2 +18 24
3 Asane 11 5 3 3 +6 18
4 Sogndal 10 5 2 3 +6 17
5 Grorud 11 5 2 4 +3 17
6 Sandnes ULF 11 5 2 4 -6 17
7 Lillestrom 11 4 4 3 +2 16
8 Jerv 11 3 6 2 +3 15
9 Stjørdals-Blink 11 4 3 4 +0 15
10 KFUM Oslo 11 3 4 4 -2 13
11 Raufoss 11 2 5 4 -2 11
12 Ull/Kisa 11 2 5 4 -6 11
13 Strommen 11 3 2 6 -8 11
14 Øygarden 11 2 4 5 -8 10
15 Kongsvinger 11 2 3 6 -10 9
16 Ham-Kam 11 1 4 6 -7 7

Calculated from our results data. “xG +/−” is expected goal difference — a positive number with a low league position suggests an undervalued team. Ties on points are sorted by goal difference; some leagues use other rules.

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