1. Division · Cyprus · Regular Season - 2

Omonia 29is Maiou–Karmiotissa

2–2

HT 0–2

Kick-off: Friday, 4 September 2026 at 16:00
Status: Match Finished

What the model said, and what happened

Ended level — we gave the draw 19%double chance: 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

2'KarmiotissaPatrick Luan
31'KarmiotissaM. Kokkinoftas
45'KarmiotissaD. A. Reynolds · red card
54'Omonia 29is MaiouS. Fiakas
67'Omonia 29is MaiouR. Fernandes
90+2'KarmiotissaJulio César · red card

What we expected, and what happened

Expected goals before kick-off: Omonia 29is Maiou 2.16 · Karmiotissa 0.66. On the pitch: 2-2.

Referee

Konstantinos Photiou, Cyprus→

6.80

yellows per match

0.20

reds per match

matches of data

5 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 72.8%: “Omonia 29is Maiou to win”. Second comes “a draw” at 18.5%.
Behind that distribution are the expected goals: 2.16 for Omonia 29is Maiou, 0.66 for Karmiotissa.
The highest double chance value is 91.4% (1X — Omonia 29is Maiou win or draw).
These values were computed from 852 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.

Omonia 29is Maiou to win72.8%

Draw18.5%

Karmiotissa to win8.6%

When the model has said 70–75% in the past, 912 of 1,222 predictions were correct (74.6%). Accuracy record →

First half

Actual: 0–2

Omonia 29is Maiou lead at half-time41.9%

Level at half-time42.6%

Karmiotissa lead at half-time15.5%

First-half double chance

1X — Omonia 29is Maiou ahead or level84.5%

12 — not level at half-time57.4%

X2 — level or Karmiotissa ahead58.1%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 851 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

Omonia 29is Maiou: at least 12
Karmiotissa: at least 12

Corners

Omonia 29is Maiou: at least 5
Karmiotissa: at least 3

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 Omonia 29is Maiou score2.16

Attack: Omonia 29is Maiou score close to the league average.

Opponent's defence: Karmiotissa concede 46% more than the league average — the defence is the weakest link in this match.

Result: These two effects give an expectation of 2.16 goals (including home advantage).

How many goals Karmiotissa score0.66

Attack: Karmiotissa score below the league average (38% fewer).

Opponent's defence: Omonia 29is Maiou's defence is close to the league average (0.96×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 0.66 goals (including the away penalty).

Most likely scorelines

2–014.5%1–012.2%3–010.3%

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 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.