Woking
Model pick
44%
Fair odds 2.29
Barrow
30%
Fair odds 3.35
Share of the pitch
Who wins
| Woking | Draw | Barrow | |
|---|---|---|---|
| Goals model | 44% | 26% | 30% |
| Elo model | 39% | 28% | 33% |
Why this prediction
-
Overall strength Favours Barrow
Barrow are rated 44 points above Woking (1130 to 1086), built from every result, weighted towards recent ones.
-
Home advantage Favours Woking
Playing at home is worth about 65 rating points, which adds 9 points to Woking's chance of winning and takes the same from Barrow's.
-
Attack against defence Favours Woking
Expected goals 1.5 to 1.2. Woking score 0.6 a match against an average side (8th in National League); Barrow concede 2.6 (7th best defence).
-
Last 5 matches Neutral
Woking WLWLW, gained 14 rating points; Barrow DWWWW, gained 22 rating points. Already counted in the ratings above.
Rating, last 12 months
WokingBarrowWoking
6/10 over 2.5
21 scored
14 conceded
09/12
09/26
09/29
10/03
10/10
10/24
10/27
Barrow
7/10 over 2.5
21 scored
10 conceded
09/05
09/15
09/19
09/26
09/29
10/03
10/27
10/31
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
- 1-2
- 0-1
- 0-0
- 2-2
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 7 | 7 | 5 | 2 | 1 | |
| 1 | 9 | 13 | 7 | 3 | 1 | |
| 2 | 7 | 9 | 6 | 2 | 1 | |
| 3 | 4 | 5 | 3 | 1 | ||
| 4 | 1 | 2 | 1 | |||
| 5 | 1 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Woking | Draw | Barrow |
|---|---|---|---|
| Woking | 24%4.16 | 4%22.78 | 2%62.50 |
| Level | 17%5.84 | 15%6.52 | 11%9.17 |
| Barrow | 3%32.68 | 6%17.76 | 18%5.59 |
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.