Ružomberok vs Nitra: result 3-1 and analysis
Super LigaRegular Season - 11Kick-off on October 6, 2018 at 02:00 PM (UTC)Futbalový štadión MFK Ružomberok, Ružomberok
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What was the result of Ružomberok vs Nitra?
Ružomberok won 3-1 on October 6, 2018.
Goalscorers
- 7′T. VestenickýNitra
- 10′Ismar TandirRužomberok
- 41′P. Gál-AndrezlyRužomberok
- 90′Z. MustedanagićRužomberok
What is the recent form of both teams?
Over their last 15 matches in all competitions, Ružomberok have 6 wins, 5 draws and 4 defeats; Nitra have 3, 3 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 29, 2018 | Zemplín Michalovce(away) | 2-2 | Super Liga |
| Sep 22, 2018 | Podbrezová(home) | 3-0 | Super Liga |
| Sep 15, 2018 | Zlaté Moravce(away) | 1-1 | Super Liga |
| Sep 1, 2018 | Senica(home) | 4-0 | Super Liga |
| Aug 26, 2018 | Spartak Trnava(away) | 0-0 | Super Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 29, 2018 | Sereď(away) | 1-2 | Super Liga |
| Sep 25, 2018 | AS Trencin(home) | 2-1 | Super Liga |
| Sep 22, 2018 | Zemplín Michalovce(home) | 2-1 | Super Liga |
| Sep 15, 2018 | Podbrezová(away) | 2-3 | Super Liga |
| Sep 1, 2018 | Zlaté Moravce(home) | 4-1 | Super Liga |
How many goals should we expect?
Ružomberok score 1.5 and concede 0.8 goals per match over their last 15; Nitra score 1.6 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Ružomberok | 1.5 | 0.8 | 6 | 5/15 | 6/15 |
| Nitra | 1.6 | 1.5 | 1 | 9/10 | 7/10 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 11 | Ružomberok | 10 | 1 | 3 | 6 | 10 | 20 | 6 |
A question about Ružomberok vs Nitra?
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