Maharlika vs Azkals: prediction and stats
PFLRegular Season - 9Kick-off on May 24, 2023 at 08:00 AM (UTC)Mckinley Hill Football Field, Taguig
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Maharlika have 1 win, 1 draw and 13 defeats; Azkals have 5, 3 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 20, 2023 | Kaya(home) | 1-5 | PFL |
| Apr 26, 2023 | Stallion(away) | 1-4 | PFL |
| Mar 29, 2023 | Dynamic Herb Cebu(home) | 0-2 | PFL |
| Mar 19, 2023 | Dynamic Herb Cebu(home) | 1-2 | PFL |
| Mar 12, 2023 | Mendiola(away) | 1-0 | PFL |
| 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 |
What does the head-to-head say?
Across the last 5 meetings: 0 Maharlika wins, 1 draw, 4 Azkals wins.
| Date | Score | Competition |
|---|---|---|
| Feb 25, 2023 | Azkals 4-1 Maharlika | PFL |
| Oct 15, 2022 | Maharlika 1-1 Azkals | PFL |
| Aug 20, 2022 | Azkals 4-0 Maharlika | PFL |
| Apr 25, 2022 | Azkals 3-1 Maharlika | Copa Paulino Alcantara |
| Nov 6, 2020 | Maharlika 0-5 Azkals | PFL |
How many goals should we expect?
Maharlika score 0.5 and concede 2.8 goals per match over their last 15; Azkals score 1.5 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Maharlika | 0.5 | 2.8 | 1 | 7/15 | 9/15 |
| Azkals | 1.5 | 1.4 | 3 | 8/15 | 10/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Maharlika | 24 | 12 | 3 | 9 | 55 | 42 | 39 |
A question about Maharlika vs Azkals?
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