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Eliteserien · Norway · Regular Season - 3

KFUM Oslo–Sandefjord

1–2

HT 1–2

Kick-off
Tuesday, 7 April 2026 at 17:00
Status
Match Finished
Venue
KFUM Arena, Oslo
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What the model said, and what happened

✗ Incorrect — we gave this result 23%

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

  • 5'⚽SandefjordJ. Vester (assist: Z. Smajlovic)
  • 16'⚽KFUM OsloT. Haltvik (assist: J. Hjorth)
  • 30'⚽SandefjordE. Patoulidis (penalty)

Match statistics

Match statistics
KFUM OsloSandefjord
9Shots14
1Shots on target6
8Shots inside the box9
4Goalkeeper saves0
9Corners5
3Offsides2
54%Possession46%
497Passes433
399Accurate passes

What we expected, and what happened

  • Expected goals before kick-off: KFUM Oslo 1.61 · Sandefjord 1.06. On the pitch: 1-2.
  • Shots KFUM Oslo 9 · Sandefjord 14; on target 1 and 6.

Unavailable players

KFUM Oslo

  • A. Aleesamiout · Groin Injury
  • B. Njieout · not in squad
  • B. Skaretout · injury
  • D. Hicksonout · injury
  • E. Odegaardout · Elbow Injury
  • M. Grodemout · illness
  • M. Njieout · not in squad
  • M. Sinyanout · injury
  • T. Sorasout · injury

Sandefjord

  • J. Swiftout · injury

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

Referee

Marius Grotta, Norway→

3.57

yellows per match

0.05

reds per match

21

matches of data

Model prediction

Why this prediction?

  • ·The model puts the most likely outcome at 49.9%: “KFUM Oslo to win”. Second comes “a draw” at 26.7%.
  • ·Behind that distribution are the expected goals: 1.61 for KFUM Oslo, 1.06 for Sandefjord.
  • ·The highest double chance value is 76.5% (1X — KFUM Oslo win or draw).
  • ·These values were computed from 978 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.

KFUM Oslo to win49.9%
Draw26.7%
Sandefjord to win23.5%

When the model has said 45–50% in the past, 2,070 of 4,393 predictions were correct (47.1%). Accuracy record →

326
7Fouls14
1Yellow cards3
0Red cards0

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.

Both teams to score
55.3%

When the model has said 55–60% in the past, 3,524 of 6,225 predictions were correct (56.6%). Accuracy record →

Double chance

1X — KFUM Oslo win or draw76.5%
12 — any result other than a draw73.3%
X2 — draw or Sandefjord win50.1%

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 (26.7%).

First half

Actual: 1–2
KFUM Oslo lead at half-time27.6%
Level at half-time40.9%
Sandefjord lead at half-time31.5%

First-half double chance

1X — KFUM Oslo ahead or level68.5%
12 — not level at half-time59.1%
X2 — level or Sandefjord ahead72.4%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 978 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

KFUM Oslo
at least 11Actual: 7
Sandefjord
at least 10Actual: 14

Corners

KFUM Oslo
at least 5Actual: 9
Sandefjord
at least 3Actual: 5

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

The 3+ goals prediction is not published for this match.

The model gives a probability below the baseline (60.5%). In backtesting the model's edge in the "fewer goals" direction could not be confirmed; we don't publish an unconfirmed prediction.

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 KFUM Oslo score1.61

Attack: KFUM Oslo score close to the league average.

Opponent's defence: Sandefjord's defence is close to the league average (0.97×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.61 goals (including home advantage).

How many goals Sandefjord score1.06

Attack: Sandefjord score close to the league average.

Opponent's defence: KFUM Oslo concede 28% fewer than the league average, which pulls the expectation down.

Result: These two effects give an expectation of 1.06 goals (including the away penalty).

Most likely scorelines

1–113.5%2–110.5%1–010.4%

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 978 matches played in this league before kick-off; the team with fewer has 62 matches. No data from after the match was used. The model's track record is published unfiltered.

Week 3 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.