Mebrat Hayl vs Awassa Kenema: match statistics

Mebrat Hayl has a clear defensive edge at home: they concede only 0.44 goals per game and keep a clean sheet in 56% of matches, with a home goal difference of +7. Awassa Kenema score 0.83 goals per away game, have a negative away goal difference (-2) and only 33% clean sheets on the road. In terms of quality of chances both teams are similar — home xG for Mebrat is 1.05 versus 1.08 xG for the visitors away, although the visitors register more shots on target (2.83 vs 2.12). Over the last 5 matches both sides average 1 point per game, but Mebrat have scored 5 goals in their last five fixtures compared to Awassa’s 2, giving the hosts a short-term offensive advantage. Due to the hosts’ superior defense and favorable home statistics I forecast a Mebrat Hayl win, although a draw is realistic given the low finishing efficiency of both teams (the hosts failed to score in 50% of home matches, the visitors failed to score in 44% of away matches).

I predict No BTTS with a 65% probability versus 35% for BTTS - Yes. Season BTTS rates are 44% for Mebrat Hayl and 39% for Awassa Kenema (avg ~41%), while the league BTTS rate is 40% with a low goals average of 1.77. Recent form shows a clear divergence: Mebrat posts 80% BTTS in the last 5 matches with 1.0 GF and 1.2 GA on average, whereas Awassa has only 20% BTTS, scoring 0.4 and conceding 0.6. xG and shot metrics confirm limited scoring potential for both sides — xG: 1.04 (home) vs 1.08 (away), xG against: 1.25 vs 1.21, and averages of 6.22 and 6.94 shots with 2.39 and 2.83 on target. Additionally, the home side has 44% clean sheets this season, the visitors 33%, and the league clean sheet rate is 81%, with shot conversion rates of 16% vs 12%, all of which increase the likelihood of a No Goal/clean sheet expected scenario rather than Goal/Goal.

Based on xG and defensive data I estimated 1.13 goals for Mebrat Hayl (attacking xG 1.04 and Awassa’s average xG conceded 1.21 → (1.04+1.21)/2=1.13) and 1.17 for Awassa Kenema (attacking xG 1.08 and hosts’ average xG conceded 1.25 → 1.17), giving a total of 2.30 expected goals. A Poisson model with λ=2.30 suggests roughly a 67% chance of at least 2 goals (Over 1.5), about 40% for Over 2.5 and around 20% for Over 3.5. Seasonal data confirm a moderate scoring potential: Over 1.5 occurred in 56% of home matches and 44% of away matches (average 50%), while Over 2.5 only in 22% (home) and 28% (away), which reduces the appeal of the 2.5 line. Additionally, hosts average 2.39 shots on target with a 16% conversion, visitors 2.83 on target with a 12% conversion, and clean sheet rates are 44% and 33%, indicating a moderate but not excessive risk of multiple goals. Consequently the strongest signal from the data is Over 1.5 (selection: Over, line 1.5) — the 2.30 expected goals and ~67% probability support this line, whereas Over 2.5 is less convincing (seasonally 22–28%).

Statistics show that a draw at half-time is the most common outcome — both teams were level at the break in 56% of matches, and first-half goals average only 0.39 (home) versus 0.33 (away). After the break the home side performs better — they score an average of 0.61 goals in the second half while conceding only 0.28, whereas visitors score 0.5 and concede 0.39. The performance differential also reflects in points: the home team averages 1.61 points per match versus 1.11 for the away side and collects more points in second halves (31 vs 23), which suggests they are capable of a turnaround after the break. Given the high proportion of half-time draws (56%) and the superior home goal production after the break (0.61 vs 0.5), the most likely HT/FT scenario is a draw at half-time and a home win at full-time (X/1). I therefore assign the highest probability to this scenario, while leaving a moderate chance for the draw to hold through (X/X) due to the low first-half goals average.