Tusker vs Shabana: result 0-1 and analysis
FKF Premier LeagueRegular Season - 5Kick-off on October 6, 2023 at 12:00 PM (UTC)Moi International Sports Centre, Nairobi
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What was the result of Tusker vs Shabana?
Shabana won 0-1 on October 6, 2023.
Goalscorers
- 70′?Shabana
What is the recent form of both teams?
Over their last 15 matches in all competitions, Tusker have 7 wins, 5 draws and 3 defeats; Shabana have 8, 4 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 1, 2023 | Talanta(away) | 0-0 | FKF Premier League |
| Sep 23, 2023 | Muhoroni Youth(home) | 1-0 | FKF Premier League |
| Sep 16, 2023 | Homeboyz(away) | 1-2 | FKF Premier League |
| Sep 2, 2023 | Kariobangi Sharks(home) | 1-1 | FKF Premier League |
| Aug 26, 2023 | Bandari(away) | 1-0 | FKF Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 1, 2023 | AFC Leopards(away) | 1-1 | FKF Premier League |
| Sep 23, 2023 | Kariobangi Sharks(home) | 0-1 | FKF Premier League |
| Sep 16, 2023 | Police(home) | 1-1 | FKF Premier League |
| Sep 1, 2023 | Talanta(away) | 1-1 | FKF Premier League |
| Aug 27, 2023 | Murang'a SEAL(home) | 0-1 | FKF Premier League |
How many goals should we expect?
Tusker score 1.0 and concede 0.5 goals per match over their last 15; Shabana score 1.3 and concede 0.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tusker | 1.0 | 0.5 | 10 | 4/15 | 3/15 |
| Shabana | 1.3 | 0.5 | 8 | 5/15 | 4/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Tusker sit 2nd in FKF Premier League (3 points from 1 match) and Shabana sit 4th (3 points from 1 match).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Tusker | 1 | 1 | 0 | 0 | 2 | 0 | 3 |
| 4 | Shabana | 1 | 1 | 0 | 0 | 1 | 0 | 3 |
A question about Tusker vs Shabana?
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