Atlante
29%
Fair odds 3.43
Santos
Model pick
46%
Fair odds 2.19
Share of the pitch
Who wins
| Atlante | Draw | Santos | |
|---|---|---|---|
| Goals model | 29% | 25% | 46% |
| Elo model | 38% | 28% | 34% |
Why this prediction
-
Overall strength Favours Santos
Santos are rated 52 points above Atlante (1380 to 1327), built from every result, weighted towards recent ones.
-
Home advantage Favours Atlante
Playing at home is worth about 65 rating points, which adds 9 points to Atlante's chance of winning and takes the same from Santos's.
-
Attack against defence Favours Santos
Expected goals 1.3 to 1.7. Atlante score 0.8 a match against an average side (13th in Liga MX); Santos concede 1.6 (7th best defence in Brasileirão).
-
Last 5 matches Favours Santos
Atlante LLWLL, lost 21 rating points; Santos LDDWL, barely moved. Already counted in the ratings above.
Rating, last 12 months
AtlanteSantos
Atlante
4/10 over 2.5
11 scored
17 conceded
Santos
8/10 over 2.5
16 scored
13 conceded
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
- 0-2
- 2-1
- 1-0
- 2-2
- 0-0
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 6 | 8 | 7 | 4 | 2 | 1 |
| 1 | 6 | 12 | 9 | 5 | 2 | 1 |
| 2 | 4 | 7 | 6 | 3 | 1 | |
| 3 | 2 | 3 | 3 | 1 | 1 | |
| 4 | 1 | 1 | 1 | |||
| 5 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Atlante | Draw | Santos |
|---|---|---|---|
| Atlante | 22%4.54 | 8%12.24 | 5%18.87 |
| Level | 7%14.71 | 13%7.50 | 19%5.27 |
| Santos | 1%— | 3%36.76 | 22%4.56 |
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.