Tusker vs Oserian: result 3-1 and analysis
FKF Premier LeagueRegular Season - 16Kick-off on June 24, 2012 at 02:00 PM (UTC)Ruaraka Stadium, Nairobi
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What was the result of Tusker vs Oserian?
Tusker won 3-1 on June 24, 2012.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Tusker have 8 wins, 5 draws and 2 defeats; Oserian have 2, 4 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 20, 2012 | Oserian(away) | 0-0 | FKF Premier League |
| May 11, 2012 | Chemelil Sugar(home) | 2-0 | FKF Premier League |
| May 5, 2012 | Posta Rangers FC(away) | 4-2 | FKF Premier League |
| Apr 30, 2012 | Sofapaka(home) | 0-1 | FKF Premier League |
| Apr 21, 2012 | AFC Leopards(away) | 2-0 | FKF Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 20, 2012 | Tusker(home) | 0-0 | FKF Premier League |
| May 13, 2012 | Karuturi Sports(away) | 0-1 | FKF Premier League |
| May 6, 2012 | Thika United(home) | 0-1 | FKF Premier League |
| Apr 29, 2012 | KCB(away) | 0-3 | FKF Premier League |
| Apr 21, 2012 | Muhoroni Youth(home) | 0-0 | FKF Premier League |
What does the head-to-head say?
In the last meeting: 0 Tusker wins, 1 draw, 0 Oserian wins.
| Date | Score | Competition |
|---|---|---|
| May 20, 2012 | Oserian 0-0 Tusker | FKF Premier League |
How many goals should we expect?
Tusker score 1.3 and concede 0.6 goals per match over their last 15; Oserian score 0.4 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tusker | 1.3 | 0.6 | 9 | 4/15 | 4/15 |
| Oserian | 0.4 | 1.3 | 4 | 3/15 | 5/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Tusker | 1 | 1 | 0 | 0 | 2 | 0 | 3 |
A question about Tusker vs Oserian?
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