Harrogate
Model pick
45%
Fair odds 2.22
Share of the pitch
Who wins
| Worthing | Draw | Harrogate | |
|---|---|---|---|
| Goals model | 30% | 25% | 45% |
| Elo model | 34% | 28% | 38% |
Why this prediction
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Overall strength Favours Harrogate
Harrogate are rated 77 points above Worthing (1153 to 1076), built from every result, weighted towards recent ones.
-
Home advantage Favours Worthing
Playing at home is worth about 65 rating points, which adds 9 points to Worthing's chance of winning and takes the same from Harrogate's.
-
Attack against defence Favours Harrogate
Expected goals 1.4 to 1.7. Worthing score 0.6 a match against an average side (7th in National League); Harrogate concede 2.3 (2nd best defence).
-
Last 5 matches Neutral
Worthing LDWWW, barely moved; Harrogate DLWWW, gained 7 rating points. Already counted in the ratings above.
Rating, last 12 months
WorthingHarrogate
09/12
09/19
09/26
09/29
10/03
10/10
10/27
10/31
Harrogate
8/10 over 2.5
19 scored
14 conceded
09/15
09/19
09/26
09/29
10/10
10/24
10/28
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
- 1-2
- 2-1
- 0-1
- 0-2
- 2-2
- 1-0
- 1-3
Every score
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| 0 | 5 | 7 | 7 | 4 | 2 | 1 |
| 1 | 6 | 11 | 9 | 5 | 2 | 1 |
| 2 | 4 | 7 | 6 | 4 | 2 | 1 |
| 3 | 2 | 3 | 3 | 2 | 1 | |
| 4 | 1 | 1 | 1 | 1 | ||
| 5 |
Half-time result
First-half goals
Half-time / full-time
| Half-time ↓ Full-time → | Worthing | Draw | Harrogate |
|---|---|---|---|
| Worthing | 17%5.84 | 5%20.41 | 3%37.45 |
| Level | 11%8.84 | 13%7.45 | 15%6.78 |
| Harrogate | 2%43.10 | 5%18.45 | 28%3.56 |
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.