ASA vs Interclube: result 1-2 and analysis
GirabolaRegular Season - 11Kick-off on May 11, 2013 at 02:30 PM (UTC)Estádio Cidade Universitária, Luanda
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What was the result of ASA vs Interclube?
Interclube won 1-2 on May 11, 2013.
What is the recent form of both teams?
Over their last 15 matches in all competitions, ASA have 0 wins, 6 draws and 9 defeats; Interclube have 5, 7 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 4, 2013 | Atlético do Namibe(home) | 0-1 | Girabola |
| Apr 27, 2013 | Bravos do Maquis FC(away) | 0-1 | Girabola |
| Apr 20, 2013 | Porcelana(home) | 2-3 | Girabola |
| Apr 14, 2013 | Desportivo Huíla(away) | 0-0 | Girabola |
| Apr 3, 2013 | Petro de Luanda(home) | 0-2 | Girabola |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 4, 2013 | Bravos do Maquis FC(home) | 1-1 | Girabola |
| Apr 27, 2013 | Porcelana(away) | 1-1 | Girabola |
| Apr 20, 2013 | Desportivo Huíla(home) | 1-1 | Girabola |
| Apr 13, 2013 | Petro de Luanda(away) | 0-4 | Girabola |
| Mar 30, 2013 | Kabuscorp(away) | 0-1 | Girabola |
What does the head-to-head say?
Across the last 2 meetings: 1 ASA win, 1 draw, 0 Interclube wins.
| Date | Score | Competition |
|---|---|---|
| Aug 25, 2012 | Interclube 0-0 ASA | Girabola |
| Apr 21, 2012 | ASA 3-1 Interclube | Girabola |
How many goals should we expect?
ASA score 0.4 and concede 1.2 goals per match over their last 15; Interclube score 1.3 and concede 1.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| ASA | 0.4 | 1.2 | 3 | 4/15 | 2/15 |
| Interclube | 1.3 | 1.0 | 4 | 8/15 | 5/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 5 | Interclube | 6 | 3 | 1 | 2 | 7 | 5 | 10 |
A question about ASA vs Interclube?
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