RTU vs JDFS Alberts: result 2-1 and analysis
1. LigaRegular Season - 28Kick-off on October 22, 2016 at 11:00 AM (UTC)Rīgas 49. vidusskolas sporta komplekss, Riga
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What was the result of RTU vs JDFS Alberts?
RTU won 2-1 on October 22, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, RTU have 6 wins, 1 draw and 8 defeats; JDFS Alberts have 5, 1 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 1, 2016 | Rēzekne FA(home) | 6-2 | 1. Liga |
| Sep 28, 2016 | Skonto(away) | 2-3 | 1. Liga |
| Sep 24, 2016 | Saldus / Brocēnu(away) | 3-0 | 1. Liga |
| Sep 18, 2016 | Valmiera / BSS(home) | 1-4 | 1. Liga |
| Sep 10, 2016 | Jēkabpils(away) | 8-0 | 1. Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 15, 2016 | Tukums(away) | 2-7 | 1. Liga |
| Oct 1, 2016 | Smiltene(away) | 1-4 | 1. Liga |
| Sep 24, 2016 | Skonto(home) | 2-0 | 1. Liga |
| Sep 18, 2016 | Ogre(away) | 0-3 | 1. Liga |
| Sep 10, 2016 | Rēzekne FA(home) | 1-0 | 1. Liga |
What does the head-to-head say?
In the last meeting: 0 RTU wins, 0 draws, 1 JDFS Alberts win.
| Date | Score | Competition |
|---|---|---|
| Jun 18, 2016 | JDFS Alberts 1-0 RTU | 1. Liga |
How many goals should we expect?
RTU score 2.4 and concede 1.7 goals per match over their last 15; JDFS Alberts score 1.1 and concede 2.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| RTU | 2.4 | 1.7 | 3 | 10/15 | 12/15 |
| JDFS Alberts | 1.1 | 2.6 | 5 | 7/15 | 9/15 |
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 | JDFS Alberts | 22 | 12 | 4 | 6 | 44 | 31 | 40 |
A question about RTU vs JDFS Alberts?
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