Fortune Sacco vs MCF: prediction and stats
Super LeagueRegular Season - 32Kick-off on June 2, 2023 at 12:00 AM (UTC)Kianyaga Stadium, Kianyaga
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Fortune Sacco have 8 wins, 2 draws and 5 defeats; MCF have 6, 4 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jan 11, 2023 | APS Bomet(away) | 2-2 | Super League |
| Jan 7, 2023 | Coastal Heroes(home) | 0-2 | Super League |
| Dec 21, 2022 | Mwatate United(home) | 0-2 | Super League |
| Jul 24, 2022 | Gusii(away) | 2-0 | Super League |
| Jul 18, 2022 | MCF(home) | 2-0 | Super League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 28, 2023 | Mwatate United(away) | 1-1 | Super League |
| May 24, 2023 | Darajani Gogo(home) | 1-1 | Super League |
| May 20, 2023 | Mara Sugar(home) | 0-1 | Super League |
| May 14, 2023 | Vihiga United FC(away) | 2-1 | Super League |
| May 10, 2023 | Mombasa Elite(home) | 3-2 | Super League |
What does the head-to-head say?
Across the last 2 meetings: 1 Fortune Sacco win(s), 1 draw(s), 0 MCF win(s).
| Date | Score | Competition |
|---|---|---|
| Jul 18, 2022 | Fortune Sacco 2-0 MCF | Super League |
| Dec 5, 2021 | MCF 0-0 Fortune Sacco | Super League |
How many goals should we expect?
Fortune Sacco score 1.2 and concede 0.9 goals per match over their last 15; MCF score 1.2 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Fortune Sacco | 1.2 | 0.9 | 7 | 3/15 | 4/15 |
| MCF | 1.2 | 0.9 | 5 | 6/15 | 5/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Fortune Sacco sit 6th in Super League (63 points from 38 matches) and MCF sit 18th (34 points from 38 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 6 | Fortune Sacco | 38 | 18 | 9 | 11 | 61 | 41 | 63 |
| 18 | MCF | 38 | 9 | 10 | 19 | 24 | 42 | 34 |
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