KCB vs Sofapaka: result 2-1 and analysis
FKF Premier LeagueRegular Season - 29Kick-off on November 4, 2012 at 10:00 AM (UTC)Kenyatta Stadium, Machakos
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What was the result of KCB vs Sofapaka?
KCB won 2-1 on November 4, 2012.
What is the recent form of both teams?
Over their last 15 matches in all competitions, KCB have 4 wins, 3 draws and 8 defeats; Sofapaka have 4, 7 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 27, 2012 | Mathare United(home) | 0-1 | FKF Premier League |
| Oct 21, 2012 | Nairobi City Stars(away) | 0-1 | FKF Premier League |
| Sep 30, 2012 | Western Stima(away) | 1-0 | FKF Premier League |
| Sep 24, 2012 | Posta Rangers FC(home) | 3-1 | FKF Premier League |
| Sep 17, 2012 | Tusker(home) | 0-2 | FKF Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 27, 2012 | Sony Sugar(home) | 2-2 | FKF Premier League |
| Oct 21, 2012 | Posta Rangers FC(away) | 2-0 | FKF Premier League |
| Sep 30, 2012 | Oserian(home) | 0-0 | FKF Premier League |
| Sep 21, 2012 | Western Stima(home) | 1-2 | FKF Premier League |
| Sep 16, 2012 | Ulinzi Stars(away) | 0-1 | FKF Premier League |
What does the head-to-head say?
In the last meeting: 0 KCB wins, 0 draws, 1 Sofapaka win.
| Date | Score | Competition |
|---|---|---|
| Feb 19, 2012 | Sofapaka 2-1 KCB | FKF Premier League |
How many goals should we expect?
KCB score 1.0 and concede 1.1 goals per match over their last 15; Sofapaka score 1.1 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| KCB | 1.0 | 1.1 | 5 | 5/15 | 5/15 |
| Sofapaka | 1.1 | 0.9 | 6 | 6/15 | 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 |
|---|---|---|---|---|---|---|---|---|
| 5 | KCB | 1 | 0 | 1 | 0 | 2 | 2 | 1 |
A question about KCB vs Sofapaka?
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