Tukums vs Babīte: result 0-3 and analysis
1. LigaRegular Season - 21Kick-off on September 3, 2016 at 01:00 PM (UTC)Tukuma mākslīgā laukumā stadions, Tukums
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What was the result of Tukums vs Babīte?
Babīte won 0-3 on September 3, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Tukums have 10 wins, 1 draw and 4 defeats; Babīte have 14, 0 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 27, 2016 | RTU(home) | 1-1 | 1. Liga |
| Aug 13, 2016 | Skonto(away) | 2-1 | 1. Liga |
| Aug 6, 2016 | Rēzekne FA(away) | 5-3 | 1. Liga |
| Jul 30, 2016 | Saldus / Brocēnu(away) | 7-3 | 1. Liga |
| Jul 23, 2016 | Valmiera / BSS(home) | 2-0 | 1. Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 27, 2016 | Smiltene(away) | 3-1 | 1. Liga |
| Aug 21, 2016 | Ogre(away) | 4-0 | 1. Liga |
| Aug 14, 2016 | Olaine / Super Nova(away) | 0-3 | 1. Liga |
| Aug 7, 2016 | Preiļu BJSS(away) | 7-1 | 1. Liga |
| Jul 30, 2016 | Auda(away) | 4-0 | 1. Liga |
What does the head-to-head say?
In the last meeting: 0 Tukums wins, 0 draws, 1 Babīte win.
| Date | Score | Competition |
|---|---|---|
| May 4, 2016 | Babīte 2-1 Tukums | 1. Liga |
How many goals should we expect?
Tukums score 3.5 and concede 1.9 goals per match over their last 15; Babīte score 3.1 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tukums | 3.5 | 1.9 | 2 | 12/15 | 12/15 |
| Babīte | 3.1 | 0.9 | 7 | 7/15 | 12/15 |
Over the last 15 matches in all competitions.
A question about Tukums vs Babīte?
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