KRA vs Chemelil Sugar: result 0-2 and analysis
FKF Premier LeagueRegular Season - 29Kick-off on November 1, 2014 at 12:00 PM (UTC)Nyayo National Stadium, Nairobi
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What was the result of KRA vs Chemelil Sugar?
Chemelil Sugar won 0-2 on November 1, 2014.
What is the recent form of both teams?
Over their last 15 matches in all competitions, KRA have 3 wins, 1 draw and 11 defeats; Chemelil Sugar 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 |
|---|---|---|---|
| Oct 24, 2014 | Tusker(home) | 0-2 | FKF Premier League |
| Oct 16, 2014 | Sofapaka(away) | 2-3 | FKF Premier League |
| Oct 4, 2014 | Muhoroni Youth(away) | 1-3 | FKF Premier League |
| Sep 19, 2014 | Sony Sugar(home) | 0-1 | FKF Premier League |
| Sep 14, 2014 | Mathare United(away) | 0-2 | FKF Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 26, 2014 | AFC Leopards(home) | 0-1 | FKF Premier League |
| Oct 19, 2014 | KCB(away) | 2-1 | FKF Premier League |
| Oct 3, 2014 | Ulinzi Stars(home) | 1-2 | FKF Premier League |
| Sep 20, 2014 | GOR Mahia(away) | 0-2 | FKF Premier League |
| Sep 13, 2014 | Nakuru AllStars(away) | 1-0 | FKF Premier League |
What does the head-to-head say?
In the last meeting: 0 KRA wins, 1 draw, 0 Chemelil Sugar wins.
| Date | Score | Competition |
|---|---|---|
| Mar 29, 2014 | Chemelil Sugar 0-0 KRA | FKF Premier League |
Last archived meeting: Chemelil Sugar vs KRA on Mar 29, 2014
How many goals should we expect?
KRA score 0.8 and concede 1.5 goals per match over their last 15; Chemelil Sugar score 0.8 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| KRA | 0.8 | 1.5 | 2 | 6/15 | 6/15 |
| Chemelil Sugar | 0.8 | 0.7 | 7 | 4/15 | 3/15 |
Over the last 15 matches in all competitions.
A question about KRA vs Chemelil Sugar?
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