Match

Baltika vs Fakel: result 0-0 and analysis

First LeagueRegular Season - 18Kick-off on October 22, 2016 at 02:00 PM (UTC)Rostec Arena, Kaliningrad

Baltika
0-0
Fakel

Full time

What was the result of Baltika vs Fakel?

Baltika and Fakel drew 0-0 on October 22, 2016.

Official lineup for Baltika vs Fakel

The starting elevens fielded at kick-off.

Baltika

  1. 9A. Podbeltsev
  2. 13P. Solomatin
  1. 25E. Tsimbal
  2. 93Vitali Kalenkovich
  3. 7S. Pomogaev
  4. 18K. Marushchak
  5. 22V. Timofeev
  6. 39V. Sarmont
  1. 21K. Rodionov
  2. 26V. Pochivalin
  1. 95D. Vambolt

Fakel

  1. 17Mikhail Biryukov
  1. 7A. Murnin
  2. 10I. Alshin
  3. 5D. Ivanov
  4. 11A. Rylov
  5. 87N. Satalkin
  1. 13V. Shakhov
  2. 27D. Tikhiy
  3. 71Mikhail Bagaev
  4. 93G. Burnash
  1. 1A. Sautin
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Baltika have 0 wins, 7 draws and 8 defeats; Fakel have 6, 5 and 4.

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

Baltika
DateOpponentScoreCompetition
Oct 15, 2016Kuban(away)1-1First League
Oct 8, 2016Mordovia Saransk(home)1-2First League
Oct 2, 2016Sibir(away)1-1First League
Sep 26, 2016Khimki(home)0-0First League
Sep 17, 2016Ska-khabarovsk(away)0-1First League
Fakel
DateOpponentScoreCompetition
Oct 15, 2016Dynamo(home)2-1First League
Oct 8, 2016Enisey(away)0-2First League
Oct 2, 2016Tyumen(home)0-0First League
Sep 26, 2016Shinnik Yaroslavl(away)2-0First League
Sep 17, 2016FK Sokol Saratov(home)1-2First League

How many goals should we expect?

Baltika score 0.6 and concede 1.3 goals per match over their last 15; Fakel score 1.3 and concede 0.9.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Baltika0.61.339/155/15
Fakel1.30.968/156/15

Over the last 15 matches in all competitions.

Where do both teams sit in the table?

2025-26 standings
#ClubPWDLGFGAPts
2Fakel342086442268

A question about Baltika vs Fakel?

Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.

Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.

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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