Super League 1 · Greece · Relegation Round - 2

PAS Giannina–Panetolikos

1–1

HT 1–0

Kick-off: Saturday, 30 March 2024 at 17:30
Status: Match Finished
Venue: Stadio Zosimades, Ioannina

Goals and red cards

25'PAS GianninaPedro Conde (assist: C. Soria)
70'PanetolikosS. Díaz (assist: C. Mavrias)

Match statistics

Match statistics
PAS Giannina		Panetolikos
12	Shots	13
3	Shots on target	4
8	Shots inside the box	4
3	Goalkeeper saves	2
3	Corners	2
1	Offsides	2
41%	Possession	59%
304	Passes	454
220	Accurate passes

What we expected, and what happened

Expected goals before kick-off: PAS Giannina 1.44 · Panetolikos 1.24. On the pitch: 1-1.
Shots PAS Giannina 12 · Panetolikos 13; on target 3 and 4.
Panetolikos kept the ball more (59%).

Referee

S. Koumbarakis→

5.33

yellows per match

0.00

reds per match

matches of data

6 matches is a small sample — these averages are noisy and should not be read as a tendency.

Model prediction

Why this prediction?

The model puts the most likely outcome at 41.0%: “PAS Giannina to win”. Second comes “Panetolikos to win” at 31.2%.
Behind that distribution are the expected goals: 1.44 for PAS Giannina, 1.24 for Panetolikos.
The highest double chance value is 72.2% (12 — any result other than a draw).
These values were computed from 397 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.

PAS Giannina to win41.0%

Draw27.8%

Panetolikos to win31.2%

When the model has said 40–45% in the past, 2,518 of 5,655 predictions were correct (44.5%). Accuracy record →

15	Fouls	20

1	Yellow cards	1

0	Red cards	0

First half

Actual: 1–0

PAS Giannina lead at half-time37.5%

Level at half-time40.4%

Panetolikos lead at half-time22.1%

First-half double chance

1X — PAS Giannina ahead or level77.9%

12 — not level at half-time59.6%

X2 — level or Panetolikos ahead62.5%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 396 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

PAS Giannina: at least 13Actual: 15
Panetolikos: at least 14Actual: 20

Corners

PAS Giannina: at least 4Actual: 3
Panetolikos: at least 3Actual: 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.

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 PAS Giannina score1.44

Attack: PAS Giannina score below the league average (25% fewer).

Opponent's defence: Panetolikos concede 15% more than the league average, which pushes the expectation up.

Result: These two effects give an expectation of 1.44 goals (including home advantage).

How many goals Panetolikos score1.24

Attack: Panetolikos score below the league average (26% fewer).

Opponent's defence: PAS Giannina concede 25% more than the league average, which pushes the expectation up.

Result: These two effects give an expectation of 1.24 goals (including the away penalty).

Most likely scorelines

1–114.1%2–19.7%1–09.0%

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.