Gent
Model pick
57%
Fair odds 1.74
Red Star
19%
Fair odds 5.39
Share of the pitch
Who wins
| Gent | Draw | Red Star | |
|---|---|---|---|
| Goals model | 57% | 24% | 19% |
| Elo model | 68% | 22% | 10% |
Why this prediction
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Overall strength Favours Gent
Gent are rated 162 points above Red Star (1550 to 1388), built from every result, weighted towards recent ones.
-
Home advantage Favours Gent
Playing at home is worth about 65 rating points, which adds 7 points to Gent's chance of winning and takes the same from Red Star's.
-
Attack against defence Favours Gent
Expected goals 1.8 to 0.9. Gent score 1.2 a match against an average side (10th in Belgian Pro League); Red Star concede 1.4 (8th best defence in Ligue 2).
-
Last 5 matches Favours Gent
Gent DLWLW, lost 6 rating points; Red Star WLLDL, lost 28 rating points. Already counted in the ratings above.
Rating, last 12 months
GentRed StarGent
3/10 over 2.5
14 scored
6 conceded
09/03
09/06
09/13
09/18
10/10
10/15
10/22
10/25
11/01
11/05
Red Star
8/10 over 2.5
17 scored
17 conceded
09/04
09/14
09/19
10/10
10/15
10/17
10/22
10/26
11/02
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
- 1-0
- 2-0
- 2-1
- 0-0
- 3-0
- 3-1
- 0-1
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 7 | 6 | 3 | 1 | ||
| 1 | 11 | 11 | 5 | 2 | ||
| 2 | 11 | 10 | 5 | 1 | ||
| 3 | 6 | 6 | 3 | 1 | ||
| 4 | 3 | 3 | 1 | |||
| 5 | 1 | 1 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Gent | Draw | Red Star |
|---|---|---|---|
| Gent | 40%2.48 | 5%19.88 | 1%74.63 |
| Level | 16%6.37 | 14%6.97 | 8%13.16 |
| Red Star | 2%51.28 | 4%26.81 | 10%9.96 |
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.