Liga I · Romania · Regular Season - 26
HT 2–0
| FC Botosani | Metaloglobus | |
|---|---|---|
| 16 | Shots | 12 |
| 5 | Shots on target | 5 |
| 12 | Shots inside the box | 8 |
| 4 | Goalkeeper saves | 3 |
| 6 | Corners | 3 |
| 1 | Offsides | 1 |
| 63% | Possession | 37% |
| 531 | Passes | 309 |
| 422 | Accurate passes |
3.33
yellows per match
0.17
reds per match
6
matches of data
6 matches is a small sample — these averages are noisy and should not be read as a tendency.
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.
When the model has said 60–65% in the past, 847 of 1,354 predictions were correct (62.6%). Accuracy record →
| 225 |
| 11 | Fouls | 10 |
|---|
| 0 | Yellow cards | 0 |
|---|
| 0 | Red cards | 0 |
|---|
The measurements our data provider sent for this match. A row that was not measured shows “—”; writing 0 into an empty field would claim we measured it and found none.
When the model has said 45–50% in the past, 1,425 of 3,100 predictions were correct (46.0%). Accuracy record →
These three values add up to 200%, not 100% — and that is not a mistake. The options are not mutually exclusive; every outcome is counted in two of them. For the same reason 1X plus X2 exceeds 100% by exactly the probability of a draw (23.7%).
First-half double chance
These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 1015 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.
Fouls
Corners
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.
When the model has said 45–50% in the past, 1,604 of 3,461 predictions were correct (46.3%). Accuracy record →
The league's historical "3+ goals" rate is 44.3%. For this match the model gives a value above that baseline — and in backtesting the model's edge was confirmed only in this direction.
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.
Attack: FC Botosani score close to the league average.
Opponent's defence: Metaloglobus concede 40% more than the league average — the defence is the weakest link in this match.
Result: These two effects give an expectation of 1.78 goals (including home advantage).
Attack: Metaloglobus score below the league average (19% fewer).
Opponent's defence: FC Botosani concede 16% fewer than the league average, which pulls the expectation down.
Result: These two effects give an expectation of 0.72 goals (including the away penalty).
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.
Ratings were computed from 1015 matches played in this league before kick-off; the team with fewer has 25 matches. No data from after the match was used. The model's track record is published unfiltered.