Saraburi vs Navy FC: result 0-1 and analysis
FA Cup2nd RoundKick-off on April 23, 2014 at 11:00 AM (UTC)Saraburi Stadium, Saraburi
Full time
What was the result of Saraburi vs Navy FC?
Navy FC won 0-1 on April 23, 2014.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Saraburi have 6 wins, 5 draws and 4 defeats; Navy FC have 6, 5 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 19, 2014 | Nakhon Ratchasima FC(away) | 1-1 | Thai League 2 |
| Apr 9, 2014 | Grakcu Sai Mai United(away) | 3-2 | FA Cup |
| Apr 6, 2014 | Nakhon Pathom(home) | 1-1 | Thai League 2 |
| Mar 29, 2014 | Chiangmai FC(away) | 2-4 | Thai League 2 |
| Mar 26, 2014 | Bbcu(home) | 3-0 | Thai League 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 20, 2014 | Phitsanulok(away) | 1-1 | Thai League 2 |
| Apr 6, 2014 | Chiangmai FC(home) | 1-0 | Thai League 2 |
| Apr 2, 2014 | Rayong United(home) | 1-1 | FA Cup |
| Mar 29, 2014 | Nakhon Pathom(away) | 1-1 | Thai League 2 |
| Mar 26, 2014 | Trat FC(home) | 1-0 | Thai League 2 |
What does the head-to-head say?
Across the last 4 meetings: 3 Saraburi wins, 0 draws, 1 Navy FC win.
| Date | Score | Competition |
|---|---|---|
| Jul 6, 2013 | Saraburi 2-1 Navy FC | Thai League 2 |
| Mar 2, 2013 | Navy FC 0-1 Saraburi | Thai League 2 |
| Sep 8, 2012 | Saraburi 2-1 Navy FC | Thai League 2 |
| May 20, 2012 | Navy FC 2-1 Saraburi | Thai League 2 |
How many goals should we expect?
Saraburi score 1.9 and concede 1.5 goals per match over their last 15; Navy FC score 0.9 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Saraburi | 1.9 | 1.5 | 2 | 12/15 | 11/15 |
| Navy FC | 0.9 | 0.9 | 7 | 6/15 | 3/15 |
Over the last 15 matches in all competitions.
A question about Saraburi vs Navy FC?
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