Odd vs Moss: match statistics

Odd is the clear favorite: at home they sit 1st, with 67% home wins and 0% home losses, scoring 2.33 and conceding 0.67 goals per match. Moss are 9th and away have only 33% wins and 67% losses, scoring 1.33 and conceding 2.67 per match. Odd produce 1.97 xG at home versus Moss’s 1.83 xG away, and the xG difference (1.97 minus 1.21 = +0.76 for Odd vs 1.83 minus 1.70 = +0.13 for Moss) indicates a much stronger control by the hosts over quality chances. Additionally, Odd average 18 shots with 6.67 on target and maintain 67% clean sheets at home, while Moss average 15.33 shots with 6.0 on target and have 0% clean sheets, and goals conversion is 13% vs 9%. Considering 2.6 points per match for Odd in the last 5 games versus 1.2 for Moss and recent goal records over the last 5: 9-4 for Odd vs 6-10 for Moss, I predict a home win.

Both teams have a seasonal BTTS rate of 67% (Odd 67%, Moss 67%), significantly above the league average of 53%. Moss concedes on the road an average of 2.67 goals per match and has no clean sheets (0%), while Odd concedes 1.33 goals per match and has kept a clean sheet in 33% of matches (conceded 4 goals this season). In attack Moss generates xG 1.83 versus Odd's 1.62, and over the last 5 matches xG were similar: 1.59 for Moss and 1.63 for Odd; both sides produce many shots (avg 15.33 and 14.67) with shots on target 6.0 (Moss) vs 4.67 (Odd). Additionally, all Moss away matches have exceeded 2.5 goals (100%), and the last 5 matches of both teams had BTTS at 60%, further confirming the Goal/Goal trend. Considering the 67% seasonal BTTS for both teams, Moss’s weak defense (2.67 conceded away) and the high xG levels for both sides, I assign 75% to BTTS - Yes and 25% to No Goal — BTTS - Yes is my pick.

Based on the last 5 matches the expected goals are: Odd 1.60 (avg xG 1.63 vs opponents’ defensive xG 1.57) and Moss 1.41 (avg xG 1.59 vs Odd defense 1.22), total 3.01 goals. The total 3.01 is clearly above the 2.5 line and close to the league average 3.34, suggesting a higher probability of a multi-goal game. Seasonal percentages confirm goal tendency: Over2.5 occurred in 67% of Odd’s matches and 100% of Moss’s matches, while the league-wide Over2.5 = 70%. A Poisson model with λ=3.01 gives about an 80% chance of at least 2 goals (hence I estimate Over1.5 at 82%) and about 58% for at least 3 goals (after accounting for seasonal tendencies I set Over2.5 at 70%). Therefore I recommend backing the over side with the 1.5 line as the strongest and most reliable signal (Over1.5 = 82%), while Over2.5 also looks attractive (70%), and Over3.5 I rate lower (35%).

Odd clearly has the edge this season: they average 1.67 goals per game versus Moss’s 1.33, and concede 1.33 compared to 2.67 for the visitors; hosts collect an average of 2.0 points per match versus Moss’s 1.0, with a win rate of 67% against the away side’s 33%. Moss produces higher xG (1.83 vs 1.62) and more shots on target (6.0 vs 4.67), but also concedes more xG against (1.7 vs 1.34) and loses more goals over the season, indicating offensive threat coupled with weaker defense. Key for the HT/FT prognosis is that Odd are stronger after the break: in second halves the hosts score on average 1.33 and concede only 0.33, while Moss concedes 1.67 on average after the break, so the hosts are more likely to complete a turnaround after halftime. Odd have scored 4 goals in minutes 76–90 this season, and in the last 5 matches they have an 80% win rate versus Moss’s 40%, further suggesting decisive goals come in the second half. For these reasons I assign the highest probability to a Half-Time/Full-Time scenario of draw at the break and home win (X/1), and a low probability to situations where Moss lead at half-time (Moss led at half in 0% of cases versus 33% for the hosts).