Bundesliga · Germany · Regular Season - 31
HT 0–1
Ended level — we gave the draw 21%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
| VfB Stuttgart | Werder Bremen | |
|---|---|---|
| 20 | Shots | 9 |
| 4 | Shots on target | 3 |
| 9 | Shots inside the box | 9 |
| 2 | Goalkeeper saves | 3 |
| 14 | Corners | 2 |
| 0 | Offsides | 1 |
| 69% | Possession | 31% |
| 663 | Passes | 313 |
| 588 | Accurate passes |
4.09
yellows per match
0.36
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 60–65% in the past, 847 of 1,354 predictions were correct (62.6%). Accuracy record →
| 237 |
| 8 | Fouls | 10 |
|---|
| 0 | 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 60–65% in the past, 1,567 of 2,553 predictions were correct (61.4%). 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 (20.6%).
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 1195 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 65–70% in the past, 699 of 988 predictions were correct (70.7%). Accuracy record →
The league's historical "3+ goals" rate is 61.3%. 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: VfB Stuttgart score above the league average (23% more).
Opponent's defence: Werder Bremen's defence is close to the league average (0.98×), so it doesn't move the expectation much.
Result: These two effects give an expectation of 2.09 goals (including home advantage).
Attack: Werder Bremen score close to the league average.
Opponent's defence: VfB Stuttgart's defence is close to the league average (0.93×), so it doesn't move the expectation much.
Result: These two effects give an expectation of 1.14 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 1195 matches played in this league before kick-off; the team with fewer has 132 matches. No data from after the match was used. The model's track record is published unfiltered.