Superliga · Denmark · Regular Season - 2

Odense–Sonderjyske

1–0

HT 0–0

Kick-off: Monday, 3 August 2026 at 17:00
Status: Match Finished
Venue: Odense Stadium, Odense

What the model said, and what happened

Prediction correct

This verdict goes into the public record unchanged; we do not filter out the ones we get wrong. The model's track record

Goals and red cards

81'OdenseN. Ganaus

Match statistics

Match statistics
Odense		Sonderjyske
17	Shots	8
4	Shots on target	3
12	Shots inside the box	6
2	Goalkeeper saves	3
7	Corners	9
0	Offsides	0
56%	Possession	44%
499	Passes	392
442	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Odense 1.74 · Sonderjyske 1.38. On the pitch: 1-0.
Shots Odense 17 · Sonderjyske 8; on target 4 and 3.
Odense kept the ball more (56%).

Referee

Sandi Putros, Denmark→

3.63

yellows per match

0.11

reds per match

matches of data

Model prediction

Why this prediction?

The model puts the most likely outcome at 45.5%: “Odense to win”. Second comes “Sonderjyske to win” at 29.3%.
Behind that distribution are the expected goals: 1.74 for Odense, 1.38 for Sonderjyske.
The highest double chance value is 74.8% (12 — any result other than a draw).
These values were computed from 659 past matches.

This is a prediction, not a guarantee; a probability is not a certainty.

These sentences are built by a fixed template; every number in them comes straight from the model's computation, none invented while the text was written.

Odense to win45.5%

Draw25.2%

Sonderjyske to win29.3%

When the model has said 45–50% in the past, 2,196 of 4,685 predictions were correct (46.9%). Accuracy record →

10	Fouls	12

1	Yellow cards	1

0	Red cards	0

First half

Actual: 0–0

Odense lead at half-time34.1%

Level at half-time38.6%

Sonderjyske lead at half-time27.3%

First-half double chance

1X — Odense ahead or level72.7%

12 — not level at half-time61.4%

X2 — level or Sonderjyske ahead65.9%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 659 matches. Its edge over the base rate is markedly smaller than the full-match model's — the measured figure is on the accuracy record. Read them more cautiously. First-half goal markets are not published because they failed to beat the base rate.

Expected fouls and corners

Fouls

Odense: at least 10Actual: 10
Sonderjyske: at least 10Actual: 12

Corners

Odense: at least 6Actual: 7
Sonderjyske: at least 3Actual: 9

These figures are set to hold in at least 60% of matches; in the rest the count comes in below them. No upper bound is stated — we make no "at most" claim. Yellow cards were measured and are not published: there our model did not beat the historical average.

What these probabilities rest on

Expected goals comes out of a team's attack weighed against its opponent's defence. A strong attack is damped when it meets a strong defence — which is why comparing the ratings on their own is misleading.

How many goals Odense score1.74

Attack: Odense score close to the league average.

Opponent's defence: Sonderjyske's defence is close to the league average (1.09×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.74 goals (including home advantage).

How many goals Sonderjyske score1.38

Attack: Sonderjyske score close to the league average.

Opponent's defence: Odense's defence is close to the league average (1.11×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.38 goals (including the away penalty).

Most likely scorelines

1–112.0%2–110.1%1–27.9%

A single scoreline is always less likely than an outcome: “home win” is the sum of 1-0, 2-0, 2-1 and dozens more. So the most likely single score can be a draw while the most likely outcome is a home win; the two do not contradict each other.

Week 2 of the season. This prediction was computed from previous seasons. Summer transfers, budget changes and squad rebuilds aren't in the ratings yet — the model can only see that a team has been rebuilt once new results come in.

We measured this: the bias is only pronounced in the opening week. In this week the model's overall accuracy does not separate from the rest of the season — that is, we found no measurable flaw. The one tendency across all opening weeks is that home wins are called slightly too often (said 43.0%, got 41.9%; n=583).

This sample is small and not statistically established, which is why we do not correct the model for it. The correction we tried (pulling probabilities toward the league average) didn't win on holdout, so it wasn't added. Read opening-week predictions with a little more caution.