Match

Benkovski Byala vs Kubrat: prediction and stats

Third League - NortheastNorth-East - 4Kick-off on August 30, 2020 at 03:00 PM (UTC)Stadion Georgi Benkovski, Byala

Benkovski ByalaKubrat

Match cancelled

What is the recent form of both teams?

Over their last 15 matches in all competitions, Benkovski Byala have 2 wins, 2 draws and 11 defeats; Kubrat have 4, 2 and 9.

The competition is shown for every match: in pre-season, several of these games are friendlies.

Benkovski Byala
DateOpponentScoreCompetition
Apr 26, 2020Hitrino(home)3-0Third League - Northeast
Feb 29, 2020Septemvri Tervel(away)0-3Third League - Northeast
Feb 23, 2020Svetkavitsa Targovishte(home)2-3Third League - Northeast
Nov 24, 2019Shumen 2007(home)2-2Third League - Northeast
Nov 17, 2019Botev Novi Pazar(home)3-1Third League - Northeast
Kubrat
DateOpponentScoreCompetition
Aug 22, 2020Botev Novi Pazar(home)2-0Third League - Northeast
Aug 16, 2020Ludogorets III(away)1-4Third League - Northeast
Aug 9, 2020Topoli(home)0-0Third League - Northeast
Mar 1, 2020Topoli(home)0-2Third League - Northeast
Feb 23, 2020Chernolomets 1919(away)0-6Third League - Northeast

What does the head-to-head say?

Across the last 3 meetings: 1 Benkovski Byala win, 0 draws, 2 Kubrat wins.

DateScoreCompetition
Sep 29, 2019Kubrat 1-0 Benkovski ByalaThird League - Northeast
Apr 14, 2019Benkovski Byala 2-1 KubratThird League - Northeast
Oct 28, 2018Kubrat 1-0 Benkovski ByalaThird League - Northeast

Last archived meeting: Kubrat vs Benkovski Byala on Sep 29, 2019

How many goals should we expect?

Benkovski Byala score 0.9 and concede 2.7 goals per match over their last 15; Kubrat score 0.7 and concede 2.2.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Benkovski Byala0.92.717/1512/15
Kubrat0.72.245/158/15

Over the last 15 matches in all competitions.

A question about Benkovski Byala vs Kubrat?

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

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