Allsvenskan · Sweden · Regular Season - 2

Sirius–Hammarby FF

2–0

HT 1–0

Kick-off: Monday, 13 April 2026 at 17:00
Status: Match Finished
Venue: Studenternas IP, Uppsala

Goals and red cards

9'SiriusI. Bjerkebo (assist: Oscar Krusnell)
70'SiriusR. Ure

Match statistics

Match statistics
Sirius		Hammarby FF
11	Shots	16
4	Shots on target	4
6	Shots inside the box	8
4	Goalkeeper saves	2
3	Corners	2
1	Offsides	1
30%	Possession	70%
297	Passes	686
214	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Sirius 1.35 · Hammarby FF 1.56. On the pitch: 2-0.
Shots Sirius 11 · Hammarby FF 16; on target 4 and 4.
Hammarby FF kept the ball more (70%).

Referee

G. Nyberg→

3.43

yellows per match

0.12

reds per match

matches of data

Model prediction

Why this prediction?

The model puts the most likely outcome at 41.6%: “Hammarby FF to win”. Second comes “Sirius to win” at 31.8%.
Behind that distribution are the expected goals: 1.35 for Sirius, 1.56 for Hammarby FF.
The highest double chance value is 73.4% (12 — any result other than a draw).
These values were computed from 974 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.

Sirius to win31.8%

Draw26.6%

Hammarby FF to win41.6%

When the model has said 40–45% in the past, 2,356 of 5,298 predictions were correct (44.5%). Accuracy record →

14	Fouls	13

0	Yellow cards	2

0	Red cards	0

First half

Actual: 1–0

Sirius lead at half-time20.5%

Level at half-time42.5%

Hammarby FF lead at half-time36.9%

First-half double chance

1X — Sirius ahead or level63.1%

12 — not level at half-time57.5%

X2 — level or Hammarby FF ahead79.5%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 974 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

Sirius: at least 12Actual: 14
Hammarby FF: at least 11Actual: 13

Corners

Sirius: at least 4Actual: 3
Hammarby FF: at least 5Actual: 2

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+ goals56.5%

When the model has said 55–60% in the past, 2,356 of 4,137 predictions were correct (56.9%). Accuracy record →

The league's historical "3+ goals" rate is 53.5%. 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 Sirius score1.35

Attack: Sirius score above the league average (23% more).

Opponent's defence: Hammarby FF concede 25% fewer than the league average, which pulls the expectation down.

Result: These two effects give an expectation of 1.35 goals (including home advantage).

How many goals Hammarby FF score1.56

Attack: Hammarby FF score above the league average (20% more).

Opponent's defence: Sirius's defence is close to the league average (0.98×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.56 goals (including the away penalty).

Most likely scorelines

1–113.1%1–29.8%2–18.4%

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.

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.