JMC Hippos vs URA: result 1-3 and analysis
Premier LeagueRegular Season - 4Kick-off on September 10, 2016 at 01:00 PM (UTC)Kakindu Municipal Stadium, Jinja
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What was the result of JMC Hippos vs URA?
URA won 1-3 on September 10, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, JMC Hippos have 4 wins, 3 draws and 8 defeats; URA have 5, 7 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 6, 2016 | SC Villa(away) | 0-1 | Premier League |
| Aug 23, 2016 | Busoga United(home) | 0-0 | Premier League |
| Aug 19, 2016 | KCCA(away) | 1-2 | Premier League |
| May 27, 2016 | Simba(home) | 1-2 | Premier League |
| May 24, 2016 | Sadolin Paints(away) | 1-2 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 6, 2016 | Vipers(home) | 1-1 | Premier League |
| Aug 23, 2016 | BUL(home) | 1-1 | Premier League |
| Aug 19, 2016 | Busoga United(away) | 0-0 | Premier League |
| May 27, 2016 | SCVU(home) | 6-1 | Premier League |
| May 24, 2016 | Vipers(away) | 1-1 | Premier League |
What does the head-to-head say?
Across the last 2 meetings: 0 JMC Hippos wins, 0 draws, 2 URA wins.
| Date | Score | Competition |
|---|---|---|
| Apr 12, 2016 | URA 2-0 JMC Hippos | Premier League |
| Nov 3, 2015 | JMC Hippos 1-2 URA | Premier League |
How many goals should we expect?
JMC Hippos score 0.9 and concede 1.2 goals per match over their last 15; URA score 1.6 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| JMC Hippos | 0.9 | 1.2 | 4 | 7/15 | 6/15 |
| URA | 1.6 | 0.9 | 5 | 9/15 | 6/15 |
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 JMC Hippos 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