Nishan ’42 vs Botopasie: result 1-3 and analysis
Eerste DivisieRegular Season - 21Kick-off on June 4, 2017 at 07:30 PM (UTC)
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What was the result of Nishan ’42 vs Botopasie?
Botopasie won 1-3 on June 4, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Nishan ’42 have 5 wins, 6 draws and 4 defeats; Botopasie have 4, 2 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 26, 2017 | Robin Hood(away) | 1-1 | Eerste Divisie |
| May 20, 2017 | WBC(home) | 1-3 | Eerste Divisie |
| May 14, 2017 | SNL(away) | 1-1 | Eerste Divisie |
| May 6, 2017 | PVV(home) | 1-1 | Eerste Divisie |
| Apr 29, 2017 | Jong Rambaan(away) | 2-1 | Eerste Divisie |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 28, 2017 | PVV(away) | 4-2 | Eerste Divisie |
| May 20, 2017 | Jong Rambaan(home) | 5-0 | Eerste Divisie |
| May 13, 2017 | Inter Moengotapoe(away) | 0-0 | Eerste Divisie |
| May 7, 2017 | Leo Victor(home) | 2-3 | Eerste Divisie |
| Apr 28, 2017 | Transvaal(away) | 1-2 | Eerste Divisie |
What does the head-to-head say?
Across the last 3 meetings: 0 Nishan ’42 wins, 2 draws, 1 Botopasie win.
| Date | Score | Competition |
|---|---|---|
| Feb 9, 2017 | Botopasie 3-3 Nishan ’42 | Eerste Divisie |
| Mar 5, 2016 | Botopasie 2-1 Nishan ’42 | Eerste Divisie |
| Nov 28, 2015 | Nishan ’42 2-2 Botopasie | Eerste Divisie |
Last archived meeting: Botopasie vs Nishan ’42 on Feb 9, 2017
How many goals should we expect?
Nishan ’42 score 1.6 and concede 1.5 goals per match over their last 15; Botopasie score 1.7 and concede 2.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Nishan ’42 | 1.6 | 1.5 | 1 | 14/15 | 9/15 |
| Botopasie | 1.7 | 2.0 | 4 | 9/15 | 12/15 |
Over the last 15 matches in all competitions.
A question about Nishan ’42 vs Botopasie?
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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