Cremonese
Model pick
49%
Fair odds 2.05
Avellino
25%
Fair odds 3.99
Share of the pitch
Who wins
| Cremonese | Draw | Avellino | |
|---|---|---|---|
| Goals model | 49% | 26% | 25% |
| Elo model | 52% | 26% | 22% |
Why this prediction
-
Overall strength Favours Cremonese
Cremonese are rated 42 points above Avellino (1399 to 1357), built from every result, weighted towards recent ones.
-
Home advantage Favours Cremonese
Playing at home is worth about 65 rating points, which adds 9 points to Cremonese's chance of winning and takes the same from Avellino's.
-
Attack against defence Favours Cremonese
Expected goals 1.6 to 1.1. Cremonese score 1.0 a match against an average side (7th in Serie B); Avellino concede 1.5 (10th best defence).
-
Last 5 matches Neutral
Cremonese WWLLD, barely moved; Avellino WDLDW, gained 13 rating points. Already counted in the ratings above.
Rating, last 12 months
CremoneseAvellinoCremonese
4/10 over 2.5
10 scored
11 conceded
08/22
08/28
09/06
09/12
09/19
10/10
10/17
10/24
10/27
10/31
Avellino
4/10 over 2.5
15 scored
10 conceded
08/22
08/29
09/06
09/13
09/19
10/09
10/18
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
- 1-0
- 2-1
- 2-0
- 0-0
- 0-1
- 1-2
- 2-2
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 7 | 7 | 4 | 1 | ||
| 1 | 10 | 12 | 6 | 2 | 1 | |
| 2 | 9 | 9 | 5 | 2 | 0 | |
| 3 | 5 | 5 | 3 | 1 | ||
| 4 | 2 | 2 | 1 | |||
| 5 | 1 | 1 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Cremonese | Draw | Avellino |
|---|---|---|---|
| Cremonese | 30%3.28 | 5%20.12 | 2%61.73 |
| Level | 16%6.07 | 15%6.47 | 10%10.06 |
| Avellino | 2%41.67 | 5%21.55 | 14%7.13 |
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.