African Lyon vs Tanzania Prisons: result 1-1 and analysis
Ligi kuu BaraRegular Season - 13Kick-off on October 29, 2016 at 11:00 AM (UTC)Karume Memorial Stadium, Dar-es-Salaam
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What was the result of African Lyon vs Tanzania Prisons?
African Lyon and Tanzania Prisons drew 1-1 on October 29, 2016.
What is the recent form of both teams?
Over their last 12 matches in all competitions, African Lyon have 3 wins, 4 draws and 5 defeats; Tanzania Prisons have 6, 7 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 22, 2016 | Mbeya City(home) | 2-0 | Ligi kuu Bara |
| Oct 19, 2016 | Maji Maji(home) | 0-2 | Ligi kuu Bara |
| Oct 15, 2016 | Stand United(away) | 1-1 | Ligi kuu Bara |
| Oct 12, 2016 | Mwadui(away) | 0-2 | Ligi kuu Bara |
| Oct 8, 2016 | Ndanda(home) | 1-0 | Ligi kuu Bara |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 23, 2016 | Mbao(home) | 1-1 | Ligi kuu Bara |
| Oct 19, 2016 | Stand United(home) | 2-1 | Ligi kuu Bara |
| Oct 15, 2016 | Mtibwa Sugar(away) | 0-0 | Ligi kuu Bara |
| Oct 12, 2016 | Ruvu Stars(away) | 0-0 | Ligi kuu Bara |
| Oct 2, 2016 | Kagera Sugar(away) | 0-2 | Ligi kuu Bara |
How many goals should we expect?
African Lyon score 0.7 and concede 1.1 goals per match over their last 12; Tanzania Prisons score 0.7 and concede 0.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| African Lyon | 0.7 | 1.1 | 4 | 3/12 | 2/12 |
| Tanzania Prisons | 0.7 | 0.5 | 9 | 4/15 | 1/15 |
Over the last 12 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 14 | Tanzania Prisons | 27 | 7 | 5 | 15 | 19 | 37 | 26 |
A question about African Lyon 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