Serie A · Italy · Regular Season - 3

Cagliari–Parma

2–0

HT 1–0

Kick-off: Saturday, 13 September 2025 at 13:00
Status: Match Finished
Venue: Unipol Domus, Cagliari

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

33'CagliariY. Mina
77'CagliariM. Felici

Match statistics

Match statistics
Cagliari		Parma
12	Shots	17
5	Shots on target	5
8	Shots inside the box	11
6	Goalkeeper saves	3
4	Corners	5
3	Offsides	0
51%	Possession	49%
396	Passes	375
319	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Cagliari 1.31 · Parma 1.22. On the pitch: 2-0.
Shots Cagliari 12 · Parma 17; on target 5 and 5.

Referee

Francesco Fourneau, Italy→

There's no card data for this referee from before this match yet. We don't invent an average; it will appear here once the data exists.

Model prediction

Why this prediction?

The model puts the most likely outcome at 42.7%: “Cagliari to win”. Second comes “a draw” at 29.1%.
Behind that distribution are the expected goals: 1.36 for Cagliari, 1.07 for Parma.
The highest double chance value is 71.8% (1X — Cagliari win or draw).
These values were computed from 1,160 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.

Cagliari to win42.7%

Draw29.1%

Parma to win28.2%

When the model has said 40–45% in the past, 1,778 of 3,998 predictions were correct (44.5%). Accuracy record →

15	Fouls	18

3	Yellow cards	1

0	Red cards	0

First half

Actual: 1–0

Cagliari lead at half-time26.6%

Level at half-time49.3%

Parma lead at half-time24.1%

First-half double chance

1X — Cagliari ahead or level75.9%

12 — not level at half-time50.7%

X2 — level or Parma ahead73.4%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 1160 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

Cagliari: at least 12Actual: 15
Parma: at least 10Actual: 18

Corners

Cagliari: at least 5Actual: 4
Parma: 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.

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 Cagliari score1.31

Attack: Cagliari score close to the league average.

Opponent's defence: Parma's defence is close to the league average (1.10×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.31 goals (including home advantage).

How many goals Parma score1.22

Attack: Parma score close to the league average.

Opponent's defence: Cagliari's defence is close to the league average (1.13×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.22 goals (including the away penalty).

Most likely scorelines

1–114.8%1–011.1%2–19.5%

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 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.