Azkals vs Stallion: prediction and stats
PFLRegular Season - 9Kick-off on June 7, 2023 at 08:00 AM (UTC)Rizal Memorial Stadium, Manila
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Azkals have 5 wins, 3 draws and 7 defeats; Stallion have 7, 2 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 20, 2023 | Mendiola(home) | 0-3 | PFL |
| Apr 15, 2023 | Kaya(away) | 2-3 | PFL |
| Mar 18, 2023 | Kaya(home) | 1-3 | PFL |
| Mar 11, 2023 | Dynamic Herb Cebu(home) | 1-2 | PFL |
| Feb 25, 2023 | Maharlika(home) | 4-1 | PFL |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 4, 2023 | Maharlika(away) | 1-0 | PFL |
| May 27, 2023 | Kaya(away) | 1-3 | PFL |
| May 24, 2023 | Dynamic Herb Cebu(away) | 0-0 | PFL |
| May 21, 2023 | Dynamic Herb Cebu(away) | 0-1 | PFL |
| May 14, 2023 | Mendiola(home) | 2-0 | PFL |
What does the head-to-head say?
Across the last 5 meetings: 3 Azkals wins, 1 draw, 1 Stallion win.
| Date | Score | Competition |
|---|---|---|
| Nov 13, 2022 | Stallion 1-2 Azkals | PFL |
| Sep 24, 2022 | Azkals 0-2 Stallion | PFL |
| Apr 11, 2022 | Azkals 1-1 Stallion | Copa Paulino Alcantara |
| Nov 16, 2021 | Stallion 1-2 Azkals | Copa Paulino Alcantara |
| Nov 9, 2020 | Stallion 0-2 Azkals | PFL |
How many goals should we expect?
Azkals score 1.5 and concede 1.4 goals per match over their last 15; Stallion score 1.6 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Azkals | 1.5 | 1.4 | 3 | 8/15 | 10/15 |
| Stallion | 1.6 | 0.9 | 7 | 5/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 6 | Stallion | 26 | 9 | 10 | 7 | 65 | 36 | 37 |
A question about Azkals vs Stallion?
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