Lokomotiv G. Oryahovitsa vs CSKA Sofia II: match statistics

CSKA Sofia II holds a clear statistical advantage: 54 goals scored this season versus Lokomotiv G. Oryahovitsa’s 34, and a superior record in the last 5 matches — 12 goals and a 3-1-1 record, while the hosts have scored 5 goals and sit at 0-1-4. The form gap is decisive: CSKA averages 2.0 points per match over the last 5, Lokomotiv only 0.2; league positions are 5th for CSKA and 13th for the hosts. Defensively Lokomotiv looks fragile — conceding 16 goals in the last 5 matches (3.2 per game), and 49 conceded this season versus CSKA’s 32; although Lokomotiv’s seasonal home concession rate is only 1.07 goals per match, recent results indicate a serious crisis. Chance quality (xG) is similar (avg xG 1.26 for Lokomotiv vs 1.36 for CSKA), but the visitors attempt more shots per game (10.87 vs 9.4), have higher finishing efficiency 13% vs 11% and less often finish matches goalless (20% vs 33%), which favors the away team. Considering the seasonal goal advantage, better last-5 metrics and higher efficiency, I predict an away win; I propose probability distribution: 65% for CSKA win, 20% draw and 15% for the hosts.

Seasonal indicators are mixed: the home team has BTTS 31% and 50% clean sheets, while the away team has BTTS 67% and only 20% clean sheets. However, the last 5 matches strongly support both teams scoring – both sides have 60% BTTS in their last 5, the home side conceded 16 goals in those 5 matches (avg 3.2), and the away side scored 12 goals (avg 2.4). xG and shooting metrics back this trend: the home team generates 1.83 xG per match versus 1.45 xG conceded by the away team, and shots on target average 7.69 for the home team against 5.4 for the away team. Considering the stronger form signals (last5) and the high seasonal BTTS for the away side (67%) versus the home side (31%), I tip BTTS - Yes with a probability of 70% versus 30% for No.

The xG- and recent-form-based model points to a high-scoring outcome: home average xG is 1.83 while the away defensive xG is 1.45, yielding an expected 1.64 goals for Lokomotiv; similarly away xG 1.36 and home defensive xG 1.02 yield 1.19 expected goals for CSKA II, totaling 2.83 expected goals. In the last 5 matches the home side scored 5 and conceded 16 (1.0/3.2 per match), while the visitors scored 12 and conceded 5 (2.4/1.0), which increases the probability of goals from the away team and raises the total. Seasonal metrics confirm the trend: Over 1.5 occurred for Lokomotiv in 63% of matches and for CSKA II in 87%, giving roughly 75% support on average for Over 1.5, whereas Over 2.5 is 31%/67% (average ~49%). Constructing a Poisson distribution with lambda=2.83 yields estimated probabilities of Over 1.5 ≈78%, Over 2.5 ≈54% and Over 3.5 ≈32%, therefore the strongest signal from the data is to play the Over line at 1.5.

Hosts have a seasonal advantage: they score an average of 2.0 goals and concede 0.5 per match with an xG of 1.83, while CSKA II register 1.47 scored and 1.6 conceded with an xG of 1.36. At half-time Lokomotiv led in 44% of matches and have 63% clean sheets at the break, and a half-time draw occurs for the hosts in 38% (33% for the visitors), so a host lead or draw at the break is a frequent scenario. In the second half the hosts score on average 1.19 goals and concede only 0.13, whereas the visitors score 0.53 and concede 0.73; the hosts also have 50% wins in second halves, which increases the chance of maintaining/expanding a lead. Therefore the strongest signal is 1/1 (hosts leading at half-time and winning) — I assess its probability at around 29%, the second strongest is X/1 (~21%). Nevertheless the visitors in their last 5 matches have won 60% and score an average of 2.4 goals in that period, so draw scenarios (X/X 11%) or surprises cannot be entirely ruled out.