Ethiopia Bunna vs Sidama Bunna: match statistics

Sidama Bunna lead the table with 17 wins this season versus Ethiopia Bunna’s 12 and hold the edge in goal difference (+8 for Sidama vs -2 for the hosts). Defensively the visitors are markedly superior: Sidama concede an average of 0.76 goals on the road, while Ethiopia concede 1.35 at home, and clean sheets for the visitors are 41% versus 18% for the hosts. Offensively the figures are similar — both teams score on average 1.24 goals per game, xG is 1.29 for Sidama versus 1.26 for the hosts, however the visitors register more shots on target (3.41 vs 2.94). Form over the last 5 matches gives Sidama an average of 1.2 points per game (2 wins, 3 losses), and Ethiopia 1.0 point (1 win, 2 draws, 2 losses), which together with the visitors’ defensive advantage increases Sidama’s chances. Although the hosts have slightly better home shot conversion (16% vs 15%), the goal and defensive statistics favor a Sidama victory, while a draw remains a realistic outcome.

I tip “No” (both teams not to score) as more likely, because the home side have 71% clean sheets this season and only 18% of matches finishing BTTS, with an average of just 0.41 goals conceded at home. The away team have a seasonal BTTS rate of 41% and score 1.24 goals per match on average, but in their last 5 matches their BTTS rate is 0% and they averaged 0.8 goals in those five games. xG shows a moderate chance of goals (home xG 1.20 vs away 1.29), but the home team have a lower xG against (0.96) and actually concede far fewer goals per match (0.41), indicating an effective defense. Although the visitors register 3.41 shots on target vs the home 2.94, the historical defensive resilience of the home side (71% clean sheets) and the visitors’ 0% BTTS in their last 5 matches are the strongest signals. Therefore I assign 75% probability to No BTTS and 25% to BTTS, basing the choice on the figures: 71% CS and 18% BTTS for the home team versus 41% seasonal BTTS and 0% BTTS in the last 5 for the visitors.

xG analysis indicates a moderate goal expectation: home xG 1.20 vs away xG conceded 1.05, yielding ≈1.13 expected goals for the home side; similarly away xG 1.29 vs home xG conceded 0.96 yields ≈1.13 for the visitors and a combined ≈2.26 xG. Seasonal averages confirm moderate attacking output — home teams score 1.06 goals per game, visitors 1.24, and in the last 5 matches they scored 3 and 4 goals respectively (averages 0.6 and 0.8). The away side attempts more shots (8.35 shots and 3.41 on target vs home 7.29 and 2.94) with the same conversion rate of 15%, which increases their scoring chance. At the same time, the hosts have 71% clean sheets and only 18% BTTS matches, while the visitors have 41% BTTS and 41% over 2.5, so there is a risk of a low, one-sided scoreline. Using a Poisson model with λ≈2.26 I estimate Over 1.5 at about 66%, Over 2.5 at ≈39% and Over 3.5 at ≈19%, therefore the strongest and safest signal is Over 1.5 (line 1.5).

At half-time a draw is the most likely: the home team have not trailed at the break this season (trailingAtHTPercentage_home 0%) and keep a clean sheet at half-time in 94% of matches, with an average of 0.35 goals scored and only 0.06 conceded by HT. Over the full match the home side have the stronger defense (seasonConcededAVG_home 0.41 vs 0.76 for Sidama) and more often keep clean sheets (71% vs 41%), which increases the probability of a turnaround from a half-time draw to a home win. Offensively xG is similar (xG 1.20 for the home team vs 1.29 for the visitors) and shooting efficiency is comparable (conversion rate 15% vs 15%), so the advantage will come from the defense and home-field advantage. The home team led at half-time in 5 matches (29%), so the 1/1 outcome is possible, but given the 71% half-time draw rate for the home side the X/1 (draw HT, home win FT) option is the strongest signal.