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OBOS-ligaen
Referee: C Moen
Jerv
T T T T T
2–2
Full-time
Sandnes ULF
T T S S S

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

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

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Team trends

Jerv Sandnes ULF
Last 6 — all competitions · 6/6 matches
Win Ø 25%
0%
50%
Points per game
0,0
1,5
Over 2.5 Ø 67%
50%
83%
Both score Ø 50%
33%
67%
Average goals
3,2
4,0
Scored
0,3
1,8
Conceded
2,8
2,2
Goal diff per game
-2,5
-0,3
This season — OBOS-ligaen · 1/1 matches
Win Ø 50%
0%
100%
Points per game
0,0
3,0
Over 2.5 Ø 100%
100%
100%
Both score Ø 100%
100%
100%
Average goals
3,0
7,0
Scored
1,0
4,0
Conceded
2,0
3,0
Goal diff per game
-1,0
+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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The table before the match Jerv 12. · Sandnes ULF 3.
# Team K V U T +/− P
1 Ull/Kisa 1 1 0 0 +4 3
2 Sogndal 1 1 0 0 +3 3
3 Sandnes ULF 1 1 0 0 +1 3
4 Kongsvinger 1 1 0 0 +1 3
5 Ranheim 1 1 0 0 +1 3
6 KFUM Oslo 1 1 0 0 +1 3
7 Tromso 1 1 0 0 +1 3
8 Lillestrom 1 1 0 0 +1 3
9 Øygarden 1 0 0 1 -1 0
10 Ham-Kam 1 0 0 1 -1 0
11 Stjørdals-Blink 1 0 0 1 -1 0
12 Jerv 1 0 0 1 -1 0
13 Raufoss 1 0 0 1 -1 0
14 Grorud 1 0 0 1 -1 0
15 Asane 1 0 0 1 -3 0
16 Strommen 1 0 0 1 -4 0

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.