Retrospective analysis — the model is trained only on matches played before this one.
The model's probabilities for a home win, draw and away win — with reasoning and recommended markets.
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Sonderjyske
Odense
Expected goals, over/under and both teams to score — priced by the model before kick-off.
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The model's top final scores with the best bookmaker odds.
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| # | Team | K | V | U | T | +/− | P |
|---|---|---|---|---|---|---|---|
| 1 |
FC Copenhagen
|
20 | 12 | 6 | 2 | +28 | 42 |
| 2 |
Midtjylland
|
20 | 12 | 3 | 5 | +15 | 39 |
| 3 |
Brondby
|
19 | 10 | 6 | 3 | +8 | 36 |
| 4 |
Silkeborg
|
19 | 7 | 10 | 2 | +16 | 31 |
| 5 |
Aalborg
|
19 | 9 | 4 | 6 | +6 | 31 |
| 6 |
Randers FC
|
20 | 8 | 5 | 7 | +0 | 29 |
| 7 |
Aarhus
|
19 | 6 | 6 | 7 | -4 | 24 |
| 8 |
Viborg
|
20 | 5 | 8 | 7 | -4 | 23 |
| 9 |
Odense
|
19 | 4 | 8 | 7 | -1 | 20 |
| 10 |
Nordsjaelland
|
19 | 4 | 5 | 10 | -13 | 17 |
| 11 |
Vejle
|
19 | 3 | 3 | 13 | -27 | 12 |
| 12 |
Sonderjyske
|
19 | 2 | 4 | 13 | -24 | 10 |
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.
Green columns are the outcomes that came in.
Brondby
Sonderjyske
Sonderjyske
Aarhus
Viborg
Sonderjyske
Sonderjyske
Aalborg
Vejle
Sonderjyske
The analysis is a statistical estimate based on the teams' results and underlying performances (xG) — not a guarantee. See the model's results.