Bundesliga · Germany · Regular Season - 34
HT 2–0
Too close to call — we gave this result 37%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
| Union Berlin | FC Augsburg | |
|---|---|---|
| 17 | Shots | 11 |
| 9 | Shots on target | 1 |
| 10 | Shots inside the box | 6 |
| 1 | Goalkeeper saves | 5 |
| 4 | Corners | 9 |
| 2 | Offsides | 3 |
| 49% | Possession | 51% |
| 450 | Passes | 448 |
| 376 | Accurate passes |
2.64
yellows per match
0.00
reds per match
11
matches of data
11 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 35–40% in the past, 1,562 of 4,187 predictions were correct (37.3%). Accuracy record →
| 369 |
| 6 | Fouls | 7 |
|---|
| 3 | Yellow cards | 1 |
|---|
| 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 70–75% in the past, 113 of 165 predictions were correct (68.5%). 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 (23.6%).
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 1215 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 70–75% in the past, 405 of 553 predictions were correct (73.2%). Accuracy record →
The league's historical "3+ goals" rate is 61.6%. 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: Union Berlin score below the league average (20% fewer).
Opponent's defence: FC Augsburg's defence is close to the league average (1.06×), so it doesn't move the expectation much.
Result: These two effects give an expectation of 1.57 goals (including home advantage).
Attack: FC Augsburg score close to the league average.
Opponent's defence: Union Berlin's defence is close to the league average (1.01×), so it doesn't move the expectation much.
Result: These two effects give an expectation of 1.39 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 1215 matches played in this league before kick-off; the team with fewer has 135 matches. No data from after the match was used. The model's track record is published unfiltered.