Cesena
33%
Fair odds 3.02
Ascoli
Model pick
39%
Fair odds 2.58
Share of the pitch
Who wins
| Cesena | Draw | Ascoli | |
|---|---|---|---|
| Goals model | 33% | 28% | 39% |
| Elo model | 36% | 28% | 36% |
Why this prediction
-
Overall strength Favours Ascoli
Ascoli are rated 64 points above Cesena (1382 to 1318), built from every result, weighted towards recent ones.
-
Home advantage Favours Cesena
Playing at home is worth about 65 rating points, which adds 9 points to Cesena's chance of winning and takes the same from Ascoli's.
-
Attack against defence Neutral
Expected goals 1.2 to 1.3. Cesena score 0.8 a match against an average side (18th in Serie B); Ascoli concede 1.4 (5th best defence).
-
Last 5 matches Favours Ascoli
Cesena DWLDL, lost 10 rating points; Ascoli DWWDD, gained 28 rating points. Already counted in the ratings above.
Rating, last 12 months
CesenaAscoliCesena
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
Ascoli
3/10 over 2.5
16 scored
6 conceded
08/23
08/29
09/05
09/12
09/19
10/10
10/17
10/24
10/27
11/01
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
- 0-1
- 1-0
- 0-0
- 1-2
- 2-1
- 0-2
- 2-0
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 9 | 10 | 7 | 3 | 1 | |
| 1 | 9 | 13 | 8 | 4 | 1 | |
| 2 | 6 | 8 | 5 | 2 | 1 | |
| 3 | 2 | 3 | 2 | 1 | ||
| 4 | 1 | 1 | 1 | |||
| 5 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Cesena | Draw | Ascoli |
|---|---|---|---|
| Cesena | 21%4.76 | 6%17.01 | 3%38.31 |
| Level | 11%8.89 | 17%5.85 | 16%6.37 |
| Ascoli | 1%73.53 | 4%24.39 | 21%4.77 |
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.