Super League 1 · Greece · Relegation Round - 3

Panetolikos–Ionikos

0–1

HT 0–1

Kick-off: Saturday, 8 April 2023 at 16:30
Status: Match Finished
Venue: Panetolikos Stadium, Agrinon

Goals and red cards

37'IonikosSebá (penalty)

Match statistics

Match statistics
Panetolikos		Ionikos
6	Shots	11
1	Shots on target	1
4	Shots inside the box	6
0	Goalkeeper saves	1
4	Corners	2
1	Offsides	1
55%	Possession	45%
401	Passes	330
308	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Panetolikos 1.17 · Ionikos 0.89. On the pitch: 0-1.
Shots Panetolikos 6 · Ionikos 11; on target 1 and 1.
Panetolikos kept the ball more (55%).

Referee

C. Vergetis→

6.25

yellows per match

0.25

reds per match

matches of data

8 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 41.6%: “Panetolikos to win”. Second comes “a draw” at 31.7%.
Behind that distribution are the expected goals: 1.17 for Panetolikos, 0.89 for Ionikos.
The highest double chance value is 73.3% (1X — Panetolikos win or draw).
These values were computed from 191 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.

Panetolikos to win41.6%

Draw31.7%

Ionikos to win26.7%

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

18	Fouls	15

4	Yellow cards	3

0	Red cards	0

First half

Actual: 0–1

Panetolikos lead at half-time35.9%

Level at half-time46.9%

Ionikos lead at half-time17.2%

First-half double chance

1X — Panetolikos ahead or level82.8%

12 — not level at half-time53.1%

X2 — level or Ionikos ahead64.1%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 191 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

Panetolikos: at least 14Actual: 18
Ionikos: at least 15Actual: 15

Corners

Panetolikos: at least 3Actual: 4
Ionikos: 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 Panetolikos score1.17

Attack: Panetolikos score below the league average (30% fewer).

Opponent's defence: Ionikos concede 30% more than the league average — the defence is the weakest link in this match.

Result: These two effects give an expectation of 1.17 goals (including home advantage).

How many goals Ionikos score0.89

Attack: Ionikos score below the league average (37% fewer).

Opponent's defence: Panetolikos concede 30% more than the league average — the defence is the weakest link in this match.

Result: These two effects give an expectation of 0.89 goals (including the away penalty).

Most likely scorelines

1–115.4%1–014.2%0–012.3%

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.

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.