Ethiopia Nigd Bank vs Bahardar: match statistics

Ethiopia Nigd Bank has an offensive edge at home — averaging 1.5 goals per match with 3.06 on-target shots and a 20% conversion rate, while Bahardar scores only 0.72 goals away with 2.33 on-target shots and 9% conversion. However, the visitors’ defense is very solid: Bahardar concedes just 0.56 goals on the road and keeps a clean sheet in 61% of matches, versus 1.0 goals conceded by the hosts at home and 33% clean sheets. In the last 5 matches the hosts have scored 3 goals (1 win, 2 draws, 2 losses) and earn 1.0 point per game, while the visitors have scored only 1 goal (0 wins, 3 draws, 2 losses) and 0.6 points per game, indicating poor form for both sides. xG is essentially even (1.14 xG for the hosts at home vs 1.16 xG for the visitors away), so the hosts’ higher conversion rate and home advantage will be decisive (hosts win 50% of home matches vs 28% away wins for visitors). Therefore I expect a narrow home victory, with a significant probability of a draw due to the visitors’ defensive profile.

I assign a 70% probability to the “No” scenario and 30% to “Yes”. This season the share of matches with both teams scoring was 32% for the home side and 28% for the away side, versus a league average of 40%, indicating a relatively low BTTS tendency. Clean sheets are common: home teams have 47% of matches without conceding, away teams 61%, and the league clean sheet rate reaches 81%, so in many fixtures one side keeps a clean sheet. Average goals are only 0.68 (home) and 0.72 (away) with xG 1.34 and 1.16 and low conversion rates of 8% and 9% and just 3.33/2.33 shots on target, suggesting created chances rarely translate into goals. The last 5 matches confirm this trend: home side BTTS 40% with an average of 0.6 goals per game (3 goals in 5), away side BTTS 20% with 0.2 goals per game (1 goal in 5), therefore a No Goal/No Goal scenario appears more likely.

The xG-based model yields total xG ≈2.44: 1.23 for Ethiopia Nigd Bank (xG attack 1.34 vs Bahardar defense 1.11) and 1.21 for Bahardar (xG attack 1.16 vs hosts’ defense 1.25). Actual goal averages are lower — hosts score 0.68 goals per match, visitors 0.72 — and shot conversion rates are only 8% and 9%, meaning xG does not fully convert into goals. Season-long Over/Under stats confirm reduced scoring: Over 2.5 occurs in 21% of hosts’ matches and 11% of visitors’ matches, while Over 3.5 happens in only 16% and 6% respectively. Additionally, clean sheets are frequent — 47% for hosts and 61% for visitors — and the share of matches with both teams scoring is low (32% and 28%), therefore the strongest signal from the data is Under 3.5 (estimated probability Under 3.5 ≈80%).

Both teams very frequently draw at half-time: the home side were level at the break in 63% of matches, the visitors in 78%, yielding an average of about a 71% chance of an HT draw. A draw is also the most common full-time outcome — the home team drew 53% of games, the visitors 56% (approximately 54.5% FT on average). Additionally, average goals are low: 0.68 for the home team and 0.72 for the away team, with xG of 1.34 versus 1.16 respectively, and average goals to half-time of 0.26 vs 0.17, all indicating a low-scoring profile. As a result I assigned the highest probability to the scenario draw at half-time and draw at full-time (HT/FT X/X 46%), while the scenario draw at half-time and an away win (HT/FT X/2 18%) is the second option due to the higher away win share of 28% versus 21% for home wins. Furthermore, home teams lead at the break in only 11% of matches, so scenarios starting with a home lead received low weights (for example HT/FT 1/1 = 7%), and the likelihood of a turnaround after half-time was assessed as low (HT/FT 1/2 = 1% and HT/FT 2/1 = 3%).