Mantova
Model pick
61%
Fair odds 1.63
Arezzo
17%
Fair odds 5.86
Share of the pitch
Who wins
| Mantova | Draw | Arezzo | |
|---|---|---|---|
| Goals model | 61% | 22% | 17% |
| Elo model | 53% | 26% | 21% |
Why this prediction
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Overall strength Favours Mantova
Mantova are rated 50 points above Arezzo (1366 to 1315), built from every result, weighted towards recent ones.
-
Home advantage Favours Mantova
Playing at home is worth about 65 rating points, which adds 9 points to Mantova's chance of winning and takes the same from Arezzo's.
-
Attack against defence Favours Mantova
Expected goals 2.0 to 1.0. Mantova score 1.1 a match against an average side (4th in Serie B); Arezzo concede 1.8 (19th best defence).
-
Last 5 matches Favours Mantova
Mantova DLWLW, barely moved; Arezzo DLLWD, lost 15 rating points. Already counted in the ratings above.
Rating, last 12 months
MantovaArezzoMantova
4/10 over 2.5
15 scored
11 conceded
08/22
08/30
09/06
09/13
09/20
10/11
10/17
10/24
10/27
10/31
Arezzo
7/10 over 2.5
9 scored
19 conceded
08/22
08/30
09/06
09/11
09/20
10/10
10/18
10/24
10/28
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
- 2-0
- 2-1
- 1-0
- 3-0
- 3-1
- 0-0
- 2-2
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 5 | 4 | 2 | 1 | ||
| 1 | 9 | 10 | 5 | 2 | ||
| 2 | 10 | 10 | 5 | 2 | ||
| 3 | 7 | 7 | 3 | 1 | ||
| 4 | 4 | 4 | 2 | 1 | ||
| 5 | 1 | 1 | 1 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Mantova | Draw | Arezzo |
|---|---|---|---|
| Mantova | 35%2.83 | 4%28.25 | 1%— |
| Level | 22%4.51 | 12%8.19 | 6%15.65 |
| Arezzo | 4%23.70 | 5%19.92 | 10%9.90 |
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.