Verona
Model pick
64%
Fair odds 1.55
Cesena
15%
Fair odds 6.88
Share of the pitch
Who wins
| Verona | Draw | Cesena | |
|---|---|---|---|
| Goals model | 64% | 21% | 15% |
| Elo model | 56% | 25% | 18% |
Why this prediction
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Overall strength Favours Verona
Verona are rated 74 points above Cesena (1392 to 1318), built from every result, weighted towards recent ones.
-
Home advantage Favours Verona
Playing at home is worth about 65 rating points, which adds 9 points to Verona's chance of winning and takes the same from Cesena's.
-
Attack against defence Favours Verona
Expected goals 2.1 to 0.9. Verona score 1.1 a match against an average side (3rd in Serie B); Cesena concede 1.8 (17th best defence).
-
Last 5 matches Favours Verona
Verona WWDDL, gained 8 rating points; Cesena DWLDL, lost 10 rating points. Already counted in the ratings above.
Rating, last 12 months
VeronaCesenaVerona
7/10 over 2.5
19 scored
13 conceded
08/23
08/29
09/06
09/11
09/20
10/11
10/16
10/25
10/28
11/01
Cesena
4/10 over 2.5
11 scored
14 conceded
08/23
08/29
09/06
09/12
09/18
10/10
10/18
10/24
10/27
10/31
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
- 2-0
- 1-0
- 1-1
- 2-1
- 3-0
- 3-1
- 0-0
- 2-2
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 6 | 4 | 2 | 1 | ||
| 1 | 10 | 10 | 4 | 1 | ||
| 2 | 11 | 10 | 4 | 1 | ||
| 3 | 8 | 7 | 3 | 1 | ||
| 4 | 4 | 4 | 2 | |||
| 5 | 2 | 1 | 1 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Verona | Draw | Cesena |
|---|---|---|---|
| Verona | 41%2.46 | 4%26.88 | 1%— |
| Level | 21%4.78 | 12%8.10 | 6%17.18 |
| Cesena | 3%30.49 | 4%23.87 | 8%12.20 |
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.