Gullegem vs Harelbeke: result 1-2 and analysis
Second Amateur Division - VFV ARegular Season - 5Kick-off on September 30, 2018 at 01:00 PM (UTC)Stadion FC Gullegem, Gullegem
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What was the result of Gullegem vs Harelbeke?
Harelbeke won 1-2 on September 30, 2018.
What is the recent form of both teams?
Over their last 4 matches in all competitions, Gullegem have 1 wins, 1 draws and 2 defeats; Harelbeke have 1, 0 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 22, 2018 | KRC Gent(away) | 0-0 | Second Amateur Division - VFV A |
| Sep 16, 2018 | Olsa Brakel(home) | 0-2 | Second Amateur Division - VFV A |
| Sep 9, 2018 | Diegem Sport(away) | 2-1 | Second Amateur Division - VFV A |
| Sep 2, 2018 | Toekomst Menen(home) | 1-2 | Second Amateur Division - VFV A |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 22, 2018 | Westhoek(home) | 4-1 | Second Amateur Division - VFV A |
| Sep 16, 2018 | Olympia Wijgmaal(away) | 1-2 | Second Amateur Division - VFV A |
| Sep 9, 2018 | Mandel United(home) | 2-4 | Second Amateur Division - VFV A |
| Sep 2, 2018 | Ronse(away) | 0-1 | Second Amateur Division - VFV A |
How many goals should we expect?
Gullegem score 0.8 and concede 1.3 goals per match over their last 4; Harelbeke score 1.8 and concede 2.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Gullegem | 0.8 | 1.3 | 1 | 2/4 | 2/4 |
| Harelbeke | 1.8 | 2.0 | 0 | 3/4 | 3/4 |
Over the last 4 matches in all competitions.
Where do both teams sit in the table?
Gullegem sit 16th in Second Amateur Division - VFV A (32 points from 30 matches) and Harelbeke sit 6th (41 points from 30 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 6 | Harelbeke | 30 | 10 | 11 | 9 | 57 | 47 | 41 |
| 16 | Gullegem | 30 | 8 | 8 | 14 | 47 | 53 | 32 |
How does Footlab compute this prediction?
The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy