FH vs Fram: match statistics

I predict an away win (Fram). Fram sit 5th in the table while FH are 11th; this season Fram have 2 wins, 1 draw and 1 loss versus FH’s 0 wins, 1 draw and 3 losses. Fram have scored 11 goals in 4 matches (2.75 per match) compared to FH’s 5 goals (1.25 per match). In the last 5 matches Fram have scored 13 and conceded 10 (avg 2.6/2.0), while FH have scored 9 and conceded 13 (avg 1.8/2.6); Fram also have higher PPG in the last 5: 1.4 vs 0.8 for FH. Additionally, Fram’s away data shows average xG 2.02 with xG against 0.72, 61% possession and about 20 shots per match, indicating control and quality of chances, whereas FH’s home data shows 0 average shots and 0 shots on target, indicating issues creating opportunities. Considering Fram’s advantage in goals, xG, possession and PPG, their victory is the most likely outcome.

Signals for BTTS are strong — the league average is 71% of matches with both teams scoring, and in the last 5 games both teams have 80% BTTS appearances. In the last 5 matches the home side averaged 1.8 goals scored and conceded 2.6, while the away side scored 2.6 and conceded 2.0, translating to 9 and 13 goals scored and 13 and 10 conceded respectively — i.e. matches with goals at both ends. xG confirms chance creation: home have 1.84 xG with 1.32 xG against, away 2.02 xG with 0.72 xG against, so both teams generate opportunities (1.84 vs 2.02) though the home team is more defensively exposed. Seasonal indicators are divergent — season BTTS for home is 100% versus 0% for away and seasonal goals averages 3.67 (home) versus 0.0 (away) — this suggests instability in historical data and requires greater reliance on the last 5 matches and league trend. Considering 71% league BTTS, 80% in the last 5 for both teams and the high goals conceded averages in the last 5 (2.6 and 2.0), I assign 80% probability to BTTS - Yes and 20% to No.

I estimate total expected goals at approximately 2.95 (expected_goals_home = 1.28, expected_goals_away = 1.67), calculated as the average of the team’s xG attack and the opponent’s xG defense: (1.84 + 0.72)/2 = 1.28 and (2.02 + 1.32)/2 = 1.67. In the last 5 matches FH averaged 1.8 goals, Fram 2.6 goals, and both teams had 80% of matches with Over 2.5 goals in those five fixtures. FH at home has a season average of 3.67 goals, 5.67 shots on target and a conversion rate of 24% (15 shots × 24% ≈ 3.6 convertible goals), whereas Fram has only 2.0 shots on target and 0% conversion in the data. A Poisson model for a mean of 2.95 yields roughly a 79% probability of Over 1.5, ~57% for Over 2.5 and ~34% for Over 3.5; therefore the strongest and most reliable signal from the data is Over 1.5. Considering FH’s seasonal 100% of matches over 2.5 goals in the provided data and the high prevalence of Over 2.5 in both teams’ last 5 matches, I recommend playing Over 1.5.

I rate 1/1 as the strongest signal because the home team led at the break in 2 of 3 matches (67%) and averages 1.0 goals by half-time versus Fram’s 0.0. Over the season FH scores an average of 3.67 goals per match and has a 67% win rate with 0% losses at HT/FT, while Fram’s seasonal average is 0.0 goals and 0% wins, yielding a clear home advantage. The home side averages 5.67 shots on target versus the visitors’ 2.0 and converts at 24% compared to the visitors’ 0%; although the visitors’ xG is 2.02 versus the home team’s 1.84, the visitors’ lack of finishing reduces their chances of a turnaround. Draws at half-time occur in 33% of matches, so the HT distribution is approximately 67% home lead and 33% draw; from these data the most probable scenario is 1/1, which I assign a 64% probability. I assign small stakes to scenarios with a draw at half-time and a draw at full-time (3% for X/1 and 30% for X/X) and practically zero chance that Fram will lead at the break (0%).