APS Bomet vs Naivas: prediction and stats
Super LeagueRegular Season - 25Kick-off on April 22, 2023 at 12:00 AM (UTC)Bomet Stadium, Bomet
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, APS Bomet have 7 wins, 5 draws and 3 defeats; Naivas have 5, 5 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| 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 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 8, 2023 | Mwatate United(home) | 0-1 | Super League |
| Apr 1, 2023 | Mara Sugar(away) | 0-0 | Super League |
| Mar 25, 2023 | Vihiga United FC(away) | 0-2 | Super League |
| Mar 20, 2023 | Mombasa Elite(home) | 3-1 | Super League |
| Mar 15, 2023 | Assad(away) | 2-1 | Super League |
What does the head-to-head say?
Across the last 3 meetings: 1 APS Bomet win, 0 draws, 2 Naivas wins.
| Date | Score | Competition |
|---|---|---|
| Jan 7, 2023 | Naivas 2-0 APS Bomet | Super League |
| Jun 22, 2022 | APS Bomet 1-0 Naivas | Super League |
| Mar 2, 2022 | Naivas 1-0 APS Bomet | Super League |
How many goals should we expect?
APS Bomet score 1.1 and concede 0.7 goals per match over their last 15; Naivas score 0.8 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| APS Bomet | 1.1 | 0.7 | 8 | 4/15 | 3/15 |
| Naivas | 0.8 | 0.7 | 8 | 3/15 | 4/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 7 | Naivas | 38 | 17 | 10 | 11 | 47 | 30 | 61 |
A question about APS Bomet vs Naivas?
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