Kagera Sugar vs Tanzania Prisons: result 0-3 and analysis
Ligi kuu BaraRegular Season - 6Kick-off on October 4, 2015 at 01:00 PM (UTC)Kaitaba Stadium, Bukoba
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What was the result of Kagera Sugar vs Tanzania Prisons?
Tanzania Prisons won 0-3 on October 4, 2015.
What is the recent form of both teams?
Over their last 5 matches in all competitions, Kagera Sugar have 1 win, 2 draws and 2 defeats; Tanzania Prisons 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 30, 2015 | Ruvu Stars(home) | 0-0 | Ligi kuu Bara |
| Sep 26, 2015 | Toto Africans(home) | 0-0 | Ligi kuu Bara |
| Sep 20, 2015 | Simba(away) | 1-3 | Ligi kuu Bara |
| Sep 16, 2015 | Maji Maji(away) | 0-1 | Ligi kuu Bara |
| Sep 12, 2015 | Mbeya City(away) | 1-0 | Ligi kuu Bara |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 30, 2015 | Mwadui(home) | 0-0 | Ligi kuu Bara |
| Sep 26, 2015 | JKT Mgambo(home) | 1-0 | Ligi kuu Bara |
| Sep 19, 2015 | Mbeya City(home) | 1-0 | Ligi kuu Bara |
| Sep 16, 2015 | Young Africans(away) | 0-3 | Ligi kuu Bara |
| Sep 12, 2015 | Azam(away) | 1-2 | Ligi kuu Bara |
How many goals should we expect?
Kagera Sugar score 0.4 and concede 0.8 goals per match over their last 5; Tanzania Prisons score 0.6 and concede 1.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kagera Sugar | 0.4 | 0.8 | 3 | 1/5 | 1/5 |
| Tanzania Prisons | 0.6 | 1.0 | 3 | 1/5 | 2/5 |
Over the last 5 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 14 | Kagera Sugar | 8 | 1 | 3 | 4 | 9 | 16 | 6 |
A question about Kagera Sugar vs Tanzania Prisons?
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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