Nishan ’42 vs PVV: result 1-2 and analysis
Eerste DivisieRegular Season - 3Kick-off on November 4, 2017 at 07:30 PM (UTC)
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What was the result of Nishan ’42 vs PVV?
PVV won 1-2 on November 4, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Nishan ’42 have 4 wins, 7 draws and 4 defeats; PVV have 3, 4 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 28, 2017 | Leo Victor(home) | 1-2 | Eerste Divisie |
| Jun 12, 2017 | Voorwaarts(away) | 1-1 | Eerste Divisie |
| Jun 4, 2017 | Botopasie(home) | 1-3 | Eerste Divisie |
| May 26, 2017 | Robin Hood(away) | 1-1 | Eerste Divisie |
| May 20, 2017 | WBC(home) | 1-3 | Eerste Divisie |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 25, 2017 | Robin Hood(home) | 1-5 | Eerste Divisie |
| Oct 20, 2017 | Leo Victor(away) | 1-1 | Eerste Divisie |
| Jun 7, 2017 | Transvaal(away) | 0-1 | Eerste Divisie |
| Jun 3, 2017 | Inter Moengotapoe(home) | 1-3 | Eerste Divisie |
| May 28, 2017 | Botopasie(home) | 2-4 | Eerste Divisie |
What does the head-to-head say?
Across the last 2 meetings: 0 Nishan ’42 wins, 1 draw, 1 PVV win.
| Date | Score | Competition |
|---|---|---|
| May 6, 2017 | Nishan ’42 1-1 PVV | Eerste Divisie |
| Dec 17, 2016 | PVV 3-2 Nishan ’42 | Eerste Divisie |
How many goals should we expect?
Nishan ’42 score 1.5 and concede 1.5 goals per match over their last 15; PVV score 1.3 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Nishan ’42 | 1.5 | 1.5 | 1 | 14/15 | 8/15 |
| PVV | 1.3 | 2.1 | 1 | 11/15 | 11/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 5 | PVV | 18 | 9 | 4 | 5 | 36 | 19 | 31 |
A question about Nishan ’42 vs PVV?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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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