Rudes vs Novigrad: result 1-1 and analysis
First NLRegular Season - 17Kick-off on November 27, 2016 at 12:30 PM (UTC)Igralište NK Rudeš, Zagreb
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What was the result of Rudes vs Novigrad?
Rudes and Novigrad drew 1-1 on November 27, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Rudes have 8 wins, 5 draws and 2 defeats; Novigrad have 6, 3 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 19, 2016 | Dinamo Zagreb II(home) | 1-1 | First NL |
| Nov 13, 2016 | Sibenik(away) | 3-1 | First NL |
| Nov 6, 2016 | Hrvatski Dragovoljac(home) | 2-1 | First NL |
| Oct 29, 2016 | Solin(away) | 0-2 | First NL |
| Oct 22, 2016 | NK Zagreb(home) | 0-0 | First NL |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 23, 2016 | HNK Gorica(home) | 1-0 | First NL |
| Nov 5, 2016 | Sesvete(home) | 0-2 | First NL |
| Oct 29, 2016 | Sibenik(away) | 1-3 | First NL |
| Oct 22, 2016 | Imotski(home) | 3-1 | First NL |
| Oct 14, 2016 | Hrvatski Dragovoljac(away) | 0-2 | First NL |
What does the head-to-head say?
In the last meeting: 1 Rudes win, 0 draws, 0 Novigrad wins.
| Date | Score | Competition |
|---|---|---|
| Sep 17, 2016 | Novigrad 1-2 Rudes | First NL |
How many goals should we expect?
Rudes score 1.7 and concede 0.8 goals per match over their last 15; Novigrad score 0.9 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Rudes | 1.7 | 0.8 | 6 | 8/15 | 6/15 |
| Novigrad | 0.9 | 1.1 | 7 | 5/15 | 5/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Rudes | 33 | 19 | 8 | 6 | 49 | 29 | 65 |
A question about Rudes vs Novigrad?
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