Jēkabpils vs Preiļu BJSS: result 0-2 and analysis
1. LigaRegular Season - 10Kick-off on May 29, 2016 at 11:00 AM (UTC)Jēkabpils SC stadions, Jēkabpils
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What was the result of Jēkabpils vs Preiļu BJSS?
Preiļu BJSS won 0-2 on May 29, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Jēkabpils have 3 wins, 1 draw and 11 defeats; Preiļu BJSS have 2, 1 and 12.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 21, 2016 | Auda(away) | 1-0 | 1. Liga |
| May 14, 2016 | Babīte(home) | 1-6 | 1. Liga |
| May 7, 2016 | RTU(away) | 2-1 | 1. Liga |
| Apr 30, 2016 | Skonto(away) | 1-4 | 1. Liga |
| Apr 23, 2016 | Rēzekne FA(home) | 1-6 | 1. Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2016 | Staiceles Bebri(home) | 2-3 | 1. Liga |
| May 14, 2016 | Tukums(away) | 1-5 | 1. Liga |
| May 8, 2016 | Smiltene(home) | 0-1 | 1. Liga |
| May 4, 2016 | Ogre(away) | 0-1 | 1. Liga |
| May 1, 2016 | Olaine / Super Nova(away) | 0-5 | 1. Liga |
What does the head-to-head say?
Across the last 4 meetings: 4 Jēkabpils wins, 0 draws, 0 Preiļu BJSS wins.
| Date | Score | Competition |
|---|---|---|
| Aug 29, 2015 | Preiļu BJSS 0-2 Jēkabpils | 1. Liga |
| May 1, 2015 | Jēkabpils 5-0 Preiļu BJSS | 1. Liga |
| Oct 11, 2014 | Jēkabpils 3-2 Preiļu BJSS | 1. Liga |
| Jun 15, 2014 | Preiļu BJSS 0-1 Jēkabpils | 1. Liga |
Last archived meeting: Preiļu BJSS vs Jēkabpils on Aug 29, 2015
How many goals should we expect?
Jēkabpils score 1.3 and concede 3.6 goals per match over their last 15; Preiļu BJSS score 0.9 and concede 2.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Jēkabpils | 1.3 | 3.6 | 2 | 11/15 | 14/15 |
| Preiļu BJSS | 0.9 | 2.5 | 2 | 7/15 | 9/15 |
Over the last 15 matches in all competitions.
A question about Jēkabpils vs Preiļu BJSS?
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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