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OBOS-ligaen
Referee: O Ekeli Valen
Aalesund
S U U S U
2–2
Full-time
Sandnes ULF
S T S U 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

Aalesund Sandnes ULF
Last 6 — all competitions · 6/6 matches
Win Ø 50%
50%
50%
Points per game
2,0
1,7
Over 2.5 Ø 75%
83%
67%
Both score Ø 75%
83%
67%
Average goals
4,5
3,2
Scored
3,0
1,7
Conceded
1,5
1,5
Goal diff per game
+1,5
+0,2
This season — OBOS-ligaen · 24/24 matches
Win Ø 44%
54%
33%
Points per game
2,0
1,3
Over 2.5 Ø 61%
58%
63%
Both score Ø 67%
67%
67%
Average goals
3,5
3,1
Scored
2,2
1,4
Conceded
1,3
1,7
Goal diff per game
+0,9
-0,3
🔒 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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The table before the match Aalesund 3. · Sandnes ULF 10.
# Team K V U T +/− P
1 Ham-Kam 24 16 5 3 +34 53
2 Jerv 24 14 6 4 +6 48
3 Aalesund 24 13 8 3 +21 47
4 Fredrikstad 23 12 6 5 +17 42
5 Sogndal 24 9 7 8 +4 34
6 KFUM Oslo 22 9 6 7 +0 33
7 Raufoss 24 9 4 11 +4 31
8 Ranheim 24 8 7 9 +1 31
9 Start 25 8 6 11 -2 30
10 Sandnes ULF 24 8 6 10 -6 30
11 Asane 24 8 5 11 -13 29
12 Bryne 24 8 4 12 -5 28
13 Ull/Kisa 24 6 6 12 -13 24
14 Grorud 24 7 3 14 -17 24
15 Stjørdals-Blink 24 7 3 14 -18 24
16 Strommen 24 2 12 10 -13 18

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.