Ndanda vs African Sports: result 2-1 and analysis
Ligi kuu BaraMatchday 20Kick-off on February 21, 2016 at 01:00 PM (UTC)Nangwanda Sijaona Stadium, Mtwara
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What was the result of Ndanda vs African Sports?
Ndanda won 2-1 on February 21, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Ndanda have 3 wins, 7 draws and 5 defeats; African Sports have 3, 4 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 13, 2016 | Maji Maji(home) | 1-0 | Ligi kuu Bara |
| Feb 7, 2016 | Mtibwa Sugar(home) | 1-1 | Ligi kuu Bara |
| Feb 4, 2016 | Coastal Union(away) | 1-0 | Ligi kuu Bara |
| Jan 31, 2016 | JKT Mgambo(away) | 1-1 | Ligi kuu Bara |
| Jan 20, 2016 | Mbeya City(home) | 4-1 | Ligi kuu Bara |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 13, 2016 | JKT Mgambo(away) | 1-0 | Ligi kuu Bara |
| Feb 6, 2016 | Stand United(home) | 0-0 | Ligi kuu Bara |
| Feb 3, 2016 | Mwadui(home) | 1-0 | Ligi kuu Bara |
| Jan 30, 2016 | Simba(away) | 0-4 | Ligi kuu Bara |
| Jan 21, 2016 | Mtibwa Sugar(home) | 0-0 | Ligi kuu Bara |
What does the head-to-head say?
In the last meeting: 0 Ndanda wins, 0 draws, 1 African Sports win.
| Date | Score | Competition |
|---|---|---|
| Sep 27, 2015 | African Sports 1-0 Ndanda | Ligi kuu Bara |
Last archived meeting: African Sports vs Ndanda on Sep 27, 2015
How many goals should we expect?
Ndanda score 0.9 and concede 1.0 goals per match over their last 15; African Sports score 0.3 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Ndanda | 0.9 | 1.0 | 4 | 8/15 | 4/15 |
| African Sports | 0.3 | 0.9 | 5 | 2/15 | 1/15 |
Over the last 15 matches in all competitions.
A question about Ndanda vs African Sports?
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