Baykonur vs Kyran: result 0-2 and analysis
1. DivisionRelegation Round - 1Kick-off on August 27, 2016 at 11:00 AM (UTC)Stadion im. Gany Muratbaeva, Kyzylorda
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What was the result of Baykonur vs Kyran?
Kyran won 0-2 on August 27, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Baykonur have 2 wins, 1 draw and 12 defeats; Kyran have 6, 1 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 7, 2016 | Kyzyl-Zhar(away) | 0-5 | 1. Division |
| Jul 31, 2016 | Altay(home) | 0-2 | 1. Division |
| Jul 23, 2016 | Kaisar(away) | 0-3 | 1. Division |
| Jul 17, 2016 | Bulat(home) | 1-0 | 1. Division |
| Jul 9, 2016 | Maqtaaral(away) | 0-3 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 7, 2016 | Ekibastuz(away) | 0-1 | 1. Division |
| Jul 31, 2016 | Kyzyl-Zhar(home) | 0-0 | 1. Division |
| Jul 23, 2016 | Altay(away) | 0-2 | 1. Division |
| Jul 16, 2016 | Kaisar(home) | 0-1 | 1. Division |
| Jul 9, 2016 | Bulat(away) | 2-1 | 1. Division |
What does the head-to-head say?
Across the last 4 meetings: 0 Baykonur wins, 1 draw, 3 Kyran wins.
| Date | Score | Competition |
|---|---|---|
| Jun 17, 2016 | Kyran 7-1 Baykonur | 1. Division |
| Apr 23, 2016 | Baykonur 1-3 Kyran | 1. Division |
| Nov 1, 2015 | Baykonur 0-0 Kyran | 1. Division |
| Apr 4, 2015 | Kyran 2-1 Baykonur | 1. Division |
How many goals should we expect?
Baykonur score 0.7 and concede 2.6 goals per match over their last 15; Kyran score 1.1 and concede 1.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Baykonur | 0.7 | 2.6 | 2 | 5/15 | 10/15 |
| Kyran | 1.1 | 1.2 | 4 | 4/15 | 5/15 |
Over the last 15 matches in all competitions.
A question about Baykonur vs Kyran?
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