Eliteserien · Norway · Regular Season - 1

Molde–Rosenborg

2–0

HT 1–0

Kick-off: Saturday, 14 March 2026 at 17:00
Status: Match Finished
Venue: Aker Stadion, Molde

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

31'MoldeE. Breivik (assist: C. Zady Sery)
57'MoldeE. Hestad (assist: H. Stenevik)

Match statistics

Match statistics
Molde		Rosenborg
13	Shots	8
4	Shots on target	2
10	Shots inside the box	3
1	Goalkeeper saves	2
5	Corners	4
0	Offsides	3
62%	Possession	38%
563	Passes	349
464	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Molde 1.95 · Rosenborg 1.19. On the pitch: 2-0.
Shots Molde 13 · Rosenborg 8; on target 4 and 2.
Molde kept the ball more (62%).

Unavailable players

Molde

D. Dagaout · injury
F. Dahlout · Knee Injury
M. Linnesout · injury
M. Møller Dæhliout · Muscle Injury
O. Spiten-Nysæterout · injury

Rosenborg

E. Slordalout · Leg Injury
I. Holmenout · Lacking Match Fitness
J. Mortensenout · Ankle Injury
J. Reitan-Sundeout · Broken collarbone
S. Nordliout · injury
S. Vaananenout · injury
T. Nemcikout · Knee Injury

Provider data — may change until the line-ups are announced. Last updated: Saturday, 19 September 2026 at 15:10.

Referee

Tore Hansen, Norway→

3.67

yellows per match

0.06

reds per match

matches of data

Model prediction

Why this prediction?

The model puts the most likely outcome at 55.0%: “Molde to win”. Second comes “a draw” at 23.6%.
Behind that distribution are the expected goals: 1.95 for Molde, 1.19 for Rosenborg.
The highest double chance value is 78.5% (1X — Molde win or draw).
These values were computed from 960 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.

Molde to win55.0%

Draw23.6%

Rosenborg to win21.5%

When the model has said 50–55% in the past, 1,798 of 3,471 predictions were correct (51.8%). Accuracy record →

14	Fouls	13

1	Yellow cards	4

0	Red cards	0

The measurements our data provider sent for this match. A row that was not measured shows “—”; writing 0 into an empty field would claim we measured it and found none.

When the model has said 60–65% in the past, 2,215 of 3,677 predictions were correct (60.2%). Accuracy record →

Double chance

1X — Molde win or draw78.5%

12 — any result other than a draw76.4%

X2 — draw or Rosenborg win45.0%

These three values add up to 200%, not 100% — and that is not a mistake. The options are not mutually exclusive; every outcome is counted in two of them. For the same reason 1X plus X2 exceeds 100% by exactly the probability of a draw (23.6%).

First half

Actual: 1–0

Molde lead at half-time44.3%

Level at half-time36.8%

Rosenborg lead at half-time18.9%

First-half double chance

1X — Molde ahead or level81.1%

12 — not level at half-time63.2%

X2 — level or Rosenborg ahead55.7%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 960 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

Molde: at least 11Actual: 14
Rosenborg: at least 9Actual: 13

Corners

Molde: at least 5Actual: 5
Rosenborg: at least 4Actual: 4

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.

Goals market

3+ goals61.6%

When the model has said 60–65% in the past, 1,726 of 2,749 predictions were correct (62.8%). Accuracy record →

The league's historical "3+ goals" rate is 60.8%. For this match the model gives a value above that baseline — and in backtesting the model's edge was confirmed only in this direction.

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 Molde score1.95

Attack: Molde score close to the league average.

Opponent's defence: Rosenborg's defence is close to the league average (0.95×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.95 goals (including home advantage).

How many goals Rosenborg score1.19

Attack: Rosenborg score close to the league average.

Opponent's defence: Molde's defence is close to the league average (0.86×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.19 goals (including the away penalty).

Most likely scorelines

1–111.3%2–110.8%2–08.3%

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.

Ratings were computed from 960 matches played in this league before kick-off; the team with fewer has 120 matches. No data from after the match was used. The model's track record is published unfiltered.

Week 1 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 and we're not hiding it: in the opening week of past seasons the model came in 3.3 points below the accuracy it claimed (n=220) — for the rest of the season it beats its own claim. The tendency points this way, though it is not proof on its own: in the opening week it slightly over-calls home wins (said 42.7%, got 39.5%) and slightly under-calls draws (said 26.1%, got 28.2%).

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.