Onhaye vs RUS Binche: result 2-1 and analysis
Second Amateur Division - ACFFACFF - 6Kick-off on September 27, 2025 at 06:00 PM (UTC)Terrain de Onhaye, Onhaye
Full time
What was the result of Onhaye vs RUS Binche?
Onhaye won 2-1 on September 27, 2025.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Onhaye have 6 wins, 4 draws and 5 defeats; RUS Binche have 5, 5 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 20, 2025 | Stade Verviers(away) | 0-1 | Second Amateur Division - ACFF |
| Sep 14, 2025 | Entité Manageoise(away) | 3-1 | Second Amateur Division - ACFF |
| Sep 6, 2025 | Huy(home) | 1-2 | Second Amateur Division - ACFF |
| Aug 31, 2025 | Ganshoren(away) | 2-0 | Second Amateur Division - ACFF |
| Aug 23, 2025 | Richelle United(home) | 0-4 | Second Amateur Division - ACFF |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 21, 2025 | Huy(home) | 0-0 | Second Amateur Division - ACFF |
| Sep 13, 2025 | Tournai(away) | 4-1 | Second Amateur Division - ACFF |
| Sep 7, 2025 | Aywaille(home) | 1-2 | Second Amateur Division - ACFF |
| Aug 30, 2025 | Acren-Lessines(away) | 1-3 | Second Amateur Division - ACFF |
| Aug 27, 2025 | Sporting Bruxelles(home) | 1-0 | Second Amateur Division - ACFF |
How many goals should we expect?
Onhaye score 1.8 and concede 1.5 goals per match over their last 15; RUS Binche score 1.4 and concede 1.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Onhaye | 1.8 | 1.5 | 3 | 10/15 | 10/15 |
| RUS Binche | 1.4 | 1.2 | 4 | 10/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 10 | RUS Binche | 9 | 3 | 3 | 3 | 16 | 19 | 12 |
A question about Onhaye vs RUS Binche?
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How does Footlab AI 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. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy