Hearts
34%
Fair odds 2.92
Monaco
Model pick
39%
Fair odds 2.56
Share of the pitch
Who wins
| Hearts | Draw | Monaco | |
|---|---|---|---|
| Goals model | 34% | 27% | 39% |
| Elo model | 42% | 28% | 30% |
Why this prediction
-
Overall strength Favours Monaco
Monaco are rated 23 points above Hearts (1578 to 1555), built from every result, weighted towards recent ones.
-
Home advantage Favours Hearts
Playing at home is worth about 65 rating points, which adds 9 points to Hearts's chance of winning and takes the same from Monaco's.
-
Attack against defence Neutral
Expected goals 1.3 to 1.4. Hearts score 1.2 a match against an average side (4th in Scottish Premiership); Monaco concede 1.1 (4th best defence in Ligue 1).
-
Last 5 matches Favours Monaco
Hearts LDWLL, lost 28 rating points; Monaco WLDWL, lost 6 rating points. Already counted in the ratings above.
Rating, last 12 months
HeartsMonacoHearts
6/10 over 2.5
16 scored
19 conceded
09/06
09/15
09/19
10/10
10/15
10/18
10/22
10/25
10/28
11/05
Monaco
6/10 over 2.5
16 scored
11 conceded
09/04
09/12
09/18
10/10
10/15
10/18
10/22
10/25
11/01
11/05
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
- 2-1
- 1-0
- 0-0
- 0-2
- 2-2
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 7 | 8 | 7 | 3 | 1 | |
| 1 | 8 | 13 | 9 | 4 | 1 | |
| 2 | 6 | 8 | 6 | 3 | 1 | |
| 3 | 2 | 4 | 3 | 1 | ||
| 4 | 1 | 1 | 1 | |||
| 5 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Hearts | Draw | Monaco |
|---|---|---|---|
| Hearts | 26%3.83 | 8%11.83 | 5%21.28 |
| Level | 8%12.76 | 15%6.86 | 18%5.69 |
| Monaco | 1%— | 3%38.46 | 17%5.74 |
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.