Džiugas Telšiai vs Sūduva: match statistics

Džiugas Telšiai sits top of the table with a record of 10-4-4 and 30 goals scored, while Sūduva are 4th with 7-8-3 and 25 goals. In the last 5 matches both teams have 3 wins and 2 draws and average 2.2 points per game, but Džiugas has scored 12 goals in that period versus Sūduva’s 9. At home Džiugas averages 1.89 goals with 12.44 shots and 3.89 shots on target and a 15% conversion rate, while Sūduva away average is 1.13 goals with 13.00 shots and 5.13 shots on target but only 9% conversion. Sūduva generate higher xG (1.50 vs Džiugas 1.36), i.e. they create slightly better chances, however lower finishing efficiency and a lower clean sheet rate (25% vs 44% for the hosts) favor Džiugas. Considering league position, higher goal tally (30 vs 25) and significantly better shooting efficiency (15% vs 9%), I predict a home win: 55% Džiugas, 25% draw, 20% Sūduva.

Both teams generate similar xG: the home side has xG_for 1.48 vs the visitors' 1.50, and a total xG_for = 2.98 suggests around 3 expected goals in the match. In the last 5 matches both teams recorded BTTS at 60% (last5: 60% and 60%), with the hosts scoring 12 in the last 5 (2.4 per match) and conceding 6 (1.2), while the visitors scored 9 and conceded 4 (1.8/0.8). Seasonally the hosts have a high clean sheet rate of 60% and a low average conceded 0.5 goals with a seasonal BTTS of 40%, but the last 5 matches show defensive deterioration to 1.2 conceded, whereas the visitors concede 1.13 per season and have BTTS 63%. Shot stats 12.3 vs 13.0, shots on target 4.1 vs 5.13 and conversion 13% vs 9% indicate both sides create genuine scoring opportunities. Considering the strong signals from the last 5 matches (BTTS 60%/60%), the similar xG and a combined xG ~2.98, I project BTTS (Goal/Goal) as more likely (64% vs 36%).

After analyzing xG and average goals, I expect about 1.33 goals for Džiugas (xG_for 1.48 and xG_against_away 1.18 give (1.48+1.18)/2=1.33). For Sūduva I expect about 1.42 goals (xG_for 1.50 and xG_against_home 1.34 -> (1.50+1.34)/2=1.42), totaling 2.75 goals. Both teams have a high share of matches over 1.5 goals this season: Džiugas 60% and Sūduva 75%, and total goals have increased in the last 5 rounds (last 5: Džiugas average 2.4 goals, Sūduva 1.8). Although Džiugas keeps 60% clean sheets at home, Sūduva has 63% BTTS and scores on average 1.13 goals per game, which raises the probability of at least 2 goals; a Poisson model with lambda=2.75 gives ~76% chance for OVER 1.5 and ~52% for OVER 2.5, therefore I recommend OVER 1.5 as the strongest signal.

Džiugas as the home side has seasonal averages of 1.6 goals scored and only 0.5 conceded, earns on average 2.2 points per home match and has won 60% of games; the home xG is 1.48 versus Sūduva’s 1.50, but Džiugas converts chances more efficiently (conversion 13% vs 9%), which explains the goal advantage. At Half-Time the hosts lead in 30% of matches, are level in 70% and are never losing at the break (0%), with mean HT goals 0.6 scored and 0.2 conceded, so the most likely HT score is a draw. In the second half Džiugas scores 1.0 on average versus Sūduva’s 0.63, wins 50% of second halves (guests only 13%) and has 60% clean sheets on the season, which suggests that from an HT draw they have a realistic chance to turn the game into a win. Modeling simply: with HT draw 70% and an estimated ~45% chance for the hosts to overturn and win after the break gives X/1 ≈ 0.7*0.45≈31.5% (rounded to 32%), whereas if Džiugas leads at the break (30%), I estimate retention of that lead at about 95% (0.3*0.95≈28.5%), hence 1/1 ≈29%. Therefore I recommend X/1 as the strongest signal (~32%), with 1/1 as the second option (~29%), because the HT statistics (70% draws) and the home advantage after the break (1.0 vs 0.63 goals and 50% second-half wins) support such a conversion.