Masaka LC vs URA: result 0-0 and analysis
Premier LeagueRegular Season - 7Kick-off on October 18, 2013 at 01:30 PM (UTC)
Full time
What was the result of Masaka LC vs URA?
Masaka LC and URA drew 0-0 on October 18, 2013.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Masaka LC have 6 wins, 3 draws and 6 defeats; URA have 10, 4 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 8, 2013 | BUL(away) | 0-2 | Premier League |
| Oct 4, 2013 | Proline(away) | 2-2 | Premier League |
| Sep 27, 2013 | KCCA(home) | 1-2 | Premier League |
| Sep 20, 2013 | Kira Young(away) | 0-2 | Premier League |
| Sep 13, 2013 | CRO(home) | 1-0 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 8, 2013 | Bright Stars(home) | 3-0 | Premier League |
| Oct 4, 2013 | Tooro United(away) | 0-0 | Premier League |
| Sep 27, 2013 | Police(home) | 2-1 | Premier League |
| Sep 17, 2013 | SC Villa(away) | 4-0 | Premier League |
| Sep 13, 2013 | Simba(home) | 2-0 | Premier League |
What does the head-to-head say?
Across the last 2 meetings: 1 Masaka LC win, 0 draws, 1 URA win.
| Date | Score | Competition |
|---|---|---|
| Mar 8, 2013 | URA 3-0 Masaka LC | Premier League |
| Oct 29, 2012 | Masaka LC 2-1 URA | Premier League |
How many goals should we expect?
Masaka LC score 1.2 and concede 1.3 goals per match over their last 15; URA score 1.6 and concede 0.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Masaka LC | 1.2 | 1.3 | 4 | 7/15 | 8/15 |
| URA | 1.6 | 0.3 | 12 | 2/15 | 5/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 15 | URA | 5 | 1 | 1 | 3 | 3 | 7 | 4 |
A question about Masaka LC vs URA?
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