Braunschweig
28%
Fair odds 3.63
Wolfsburg
Model pick
48%
Fair odds 2.07
The prediction
- 1–111%
- 1–29%
- 0–17%
Share of the pitch
Who wins
| Braunschweig | Draw | Wolfsburg | |
|---|---|---|---|
| Goals model | 28% | 24% | 48% |
| Elo model | 22% | 26% | 52% |
Why this prediction
-
Overall strength Favours Wolfsburg
Wolfsburg are rated 172 points above Braunschweig (1470 to 1298), built from every result, weighted towards recent ones.
-
Home advantage Favours Braunschweig
Playing at home is worth about 65 rating points, which adds 8 points to Braunschweig's chance of winning and takes the same from Wolfsburg's.
-
Attack against defence Favours Wolfsburg
Expected goals 1.3 to 1.8. Braunschweig score 0.9 a match against an average side (13th in 2. Bundesliga); Wolfsburg concede 1.4 (2nd best defence).
-
Last 5 matches Favours Wolfsburg
Braunschweig LWLWL, barely moved; Wolfsburg WDWDW, gained 18 rating points. Already counted in the ratings above.
Rating, last 12 months
BraunschweigWolfsburg
Braunschweig
5/10 over 2.5
16 scored
18 conceded
Wolfsburg
5/10 over 2.5
25 scored
14 conceded
Bars show total goals in each of the last 10 matches, oldest on the left: the team's goals in its colour, conceded in grey. The dashed line is 2.5 goals.
Total goals
Both teams to score & clean sheets
Most likely scores
- 1-1
- 1-2
- 0-1
- 0-2
- 2-1
- 2-2
- 1-3
- 1-0
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 5 | 7 | 7 | 4 | 2 | 1 |
| 1 | 5 | 11 | 9 | 6 | 3 | 1 |
| 2 | 4 | 7 | 6 | 4 | 2 | 1 |
| 3 | 2 | 3 | 3 | 2 | 1 | |
| 4 | 1 | 1 | 1 | 1 | ||
| 5 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Braunschweig | Draw | Wolfsburg |
|---|---|---|---|
| Braunschweig | 16%6.41 | 5%20.24 | 3%33.67 |
| Level | 10%9.74 | 13%7.70 | 16%6.33 |
| Wolfsburg | 2%47.39 | 5%19.27 | 30%3.32 |
Corners
Most corners
Corner totals are hard to call: over 9.5 the model's log loss is 0.685 against 0.693 for a naive guess, across 30,937 past matches. Which side wins more corners is called much better.
Cards
Over 4.5 cards, the model's log loss is 0.653 against 0.682 for a naive guess, across 33,146 past matches. The referee matters a lot and isn't in the model.
They haven't met in the data.