Kagera Sugar vs JKT Tanzania: result 0-1 and analysis
Ligi kuu BaraRegular Season - 4Kick-off on September 29, 2019 at 01:00 PM (UTC)Kaitaba Stadium, Bukoba
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What was the result of Kagera Sugar vs JKT Tanzania?
JKT Tanzania won 0-1 on September 29, 2019.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Kagera Sugar have 8 wins, 5 draws and 2 defeats; JKT Tanzania have 2, 1 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 26, 2019 | Simba(home) | 0-3 | Ligi kuu Bara |
| Sep 21, 2019 | Mbao(away) | 1-0 | Ligi kuu Bara |
| Sep 15, 2019 | Alliance(away) | 2-1 | Ligi kuu Bara |
| Aug 24, 2019 | Biashara United(away) | 2-0 | Ligi kuu Bara |
| May 28, 2019 | Mbao(away) | 1-1 | Ligi kuu Bara |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 25, 2019 | Biashara United(away) | 1-0 | Ligi kuu Bara |
| Sep 21, 2019 | Mtibwa Sugar(home) | 0-0 | Ligi kuu Bara |
| Sep 14, 2019 | Lipuli(home) | 0-1 | Ligi kuu Bara |
| Aug 29, 2019 | Simba(home) | 1-3 | Ligi kuu Bara |
| May 28, 2019 | Stand United(home) | 2-0 | Ligi kuu Bara |
How many goals should we expect?
Kagera Sugar score 1.1 and concede 0.9 goals per match over their last 15; JKT Tanzania score 0.8 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kagera Sugar | 1.1 | 0.9 | 6 | 7/15 | 6/15 |
| JKT Tanzania | 0.8 | 0.8 | 3 | 1/5 | 1/5 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Kagera Sugar sit 15th in Ligi kuu Bara (6 points from 10 matches) and JKT Tanzania sit 4th (17 points from 10 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | JKT Tanzania | 10 | 5 | 2 | 3 | 12 | 12 | 17 |
| 15 | Kagera Sugar | 10 | 1 | 3 | 6 | 9 | 18 | 6 |
A question about Kagera Sugar vs JKT Tanzania?
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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