Taraz vs Baykonur: result 2-1 and analysis
1. DivisionRegular Season - 22Kick-off on August 4, 2018 at 12:00 PM (UTC)Ortalyq stadıon, Taraz
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What was the result of Taraz vs Baykonur?
Taraz won 2-1 on August 4, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Taraz have 10 wins, 4 draws and 1 defeat; Baykonur have 5, 4 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 28, 2018 | Maqtaaral(home) | 2-1 | 1. Division |
| Jul 23, 2018 | Aktobe Jas(away) | 2-0 | 1. Division |
| Jul 22, 2018 | Zhetysu II(away) | 1-0 | 1. Division |
| Jul 15, 2018 | Kyran(home) | 7-0 | 1. Division |
| Jul 6, 2018 | Altay(home) | 1-1 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 28, 2018 | Kaspiy(away) | 1-1 | 1. Division |
| Jul 21, 2018 | Sport Academy Kairat(home) | 2-2 | 1. Division |
| Jul 16, 2018 | Maqtaaral(home) | 2-0 | 1. Division |
| Jul 11, 2018 | Zhetysu II(away) | 0-4 | 1. Division |
| Jul 6, 2018 | Kyran(home) | 1-3 | 1. Division |
What does the head-to-head say?
In the last meeting: 0 Taraz wins, 1 draw, 0 Baykonur wins.
| Date | Score | Competition |
|---|---|---|
| Apr 1, 2018 | Baykonur 0-0 Taraz | 1. Division |
How many goals should we expect?
Taraz score 2.4 and concede 0.9 goals per match over their last 15; Baykonur score 1.1 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Taraz | 2.4 | 0.9 | 7 | 8/15 | 9/15 |
| Baykonur | 1.1 | 1.5 | 4 | 6/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 7 | Taraz | 24 | 8 | 7 | 9 | 31 | 33 | 31 |
A question about Taraz vs Baykonur?
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