Migori Youth vs APS Bomet: prediction and stats
Super LeagueRegular Season - 13Kick-off on February 12, 2023 at 12:00 PM (UTC)Migori Stadium, Migori
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Migori Youth have 6 wins, 5 draws and 4 defeats; APS Bomet have 7, 5 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 9, 2023 | Coastal Heroes(away) | 1-2 | Super League |
| Jan 29, 2023 | Naivas(away) | 0-1 | Super League |
| Jan 25, 2023 | Murang'a SEAL(home) | 0-0 | Super League |
| Jan 22, 2023 | Mwatate United(home) | 1-0 | Super League |
| Jan 15, 2023 | Mara Sugar(away) | 0-0 | Super League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jan 16, 2023 | Coastal Heroes(away) | 0-2 | Super League |
| Jan 11, 2023 | Fortune Sacco(home) | 2-2 | Super League |
| Jan 7, 2023 | Naivas(away) | 0-2 | Super League |
| Jul 24, 2022 | Murang'a SEAL(home) | 1-1 | Super League |
| Jul 18, 2022 | Muhoroni Youth(away) | 0-1 | Super League |
What does the head-to-head say?
Across the last 2 meetings: 1 Migori Youth win(s), 1 draw(s), 0 APS Bomet win(s).
| Date | Score | Competition |
|---|---|---|
| May 2, 2022 | Migori Youth 2-0 APS Bomet | Super League |
| Dec 19, 2021 | APS Bomet 1-1 Migori Youth | Super League |
Last archived meeting: Migori Youth vs APS Bomet on May 2, 2022
How many goals should we expect?
Migori Youth score 1.2 and concede 0.7 goals per match over their last 15; APS Bomet score 1.1 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Migori Youth | 1.2 | 0.7 | 8 | 5/15 | 5/15 |
| APS Bomet | 1.1 | 0.7 | 8 | 4/15 | 3/15 |
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 | Migori Youth | 38 | 25 | 6 | 7 | 57 | 29 | 81 |
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy