Ndanda vs Azam: result 2-1 and analysis
Ligi kuu BaraRegular Season - 6Kick-off on September 24, 2016 at 12:00 PM (UTC)Nangwanda Sijaona Stadium, Mtwara
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What was the result of Ndanda vs Azam?
Ndanda won 2-1 on September 24, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Ndanda have 3 wins, 8 draws and 4 defeats; Azam have 8, 6 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 17, 2016 | Maji Maji(away) | 2-1 | Ligi kuu Bara |
| Sep 10, 2016 | Kagera Sugar(home) | 0-0 | Ligi kuu Bara |
| Sep 7, 2016 | Young Africans(home) | 0-0 | Ligi kuu Bara |
| Aug 27, 2016 | Mtibwa Sugar(away) | 1-2 | Ligi kuu Bara |
| Aug 20, 2016 | Simba(away) | 1-3 | Ligi kuu Bara |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 17, 2016 | Simba(home) | 0-1 | Ligi kuu Bara |
| Sep 10, 2016 | Mbeya City(away) | 2-1 | Ligi kuu Bara |
| Sep 7, 2016 | Tanzania Prisons(away) | 1-0 | Ligi kuu Bara |
| Aug 27, 2016 | Maji Maji(home) | 3-0 | Ligi kuu Bara |
| Aug 20, 2016 | African Lyon(home) | 1-1 | Ligi kuu Bara |
What does the head-to-head say?
Across the last 2 meetings: 0 Ndanda wins, 1 draw, 1 Azam win.
| Date | Score | Competition |
|---|---|---|
| Apr 6, 2016 | Azam 2-2 Ndanda | Ligi kuu Bara |
| Oct 22, 2015 | Ndanda 0-1 Azam | Ligi kuu Bara |
How many goals should we expect?
Ndanda score 0.9 and concede 1.1 goals per match over their last 15; Azam score 1.4 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Ndanda | 0.9 | 1.1 | 6 | 7/15 | 7/15 |
| Azam | 1.4 | 0.7 | 6 | 8/15 | 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 |
|---|---|---|---|---|---|---|---|---|
| 3 | Azam | 8 | 5 | 2 | 1 | 13 | 7 | 17 |
A question about Ndanda vs Azam?
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