Hegelmann Litauen vs Sūduva: match statistics

I assess the most likely outcome as a draw. Hegelmann records as many as 63% draws at home, while Sūduva has no away wins (0% victories) and 50% of their away matches end in draws. Over the season Sūduva has more wins (4 vs 2) and a superior overall goal difference (16 scored vs Hegelmann’s 11), giving the visitors a statistical edge that diminishes away from home due to low finishing efficiency. Hegelmann scores on average 1.13 goals per home match with xG 1.33 and a 10% conversion rate, and they have scored 9 goals in the last 5 matches (1.8 per game), indicating improved attacking efficiency. The visitors have higher away xG (1.43 vs 1.33) and more shots (12.17 vs 11.13) and 4.33 shots on target per game, but actually score only 0.67 goals on the road with a 5% conversion; defensively Sūduva concedes 1.17 goals away and Hegelmann concedes 1.00 at home, so the match should be balanced. Considering these figures (63% home draws, 0% away wins for Sūduva and better home conversion 10% vs 5%), I back a draw with a moderate probability of a home win.

Although Hegelmann has only 29% of matches with BTTS this season and as many as 71% clean sheets, conceding an average of 0.43 goals per match, recent results shift the outlook. Sūduva has a seasonal BTTS of 67% and scores an average of 0.67 goals away, but in the last 5 matches holds an 80% BTTS rate and averages 1.2 goals, indicating improved offense. The xG of both teams is almost identical (1.44 vs 1.43), and xG against is also similar (1.26 vs 1.29), meaning both sides create comparable chances. Hegelmann conceded 9 goals in the last 5 matches (1.8 avg), which deviates significantly from the seasonal 0.43 and increases the likelihood of the visitors scoring. Considering 80% BTTS for both teams in L5, similar xG figures and Sūduva’s improvement, I favor the “Yes” (BTTS - Yes) scenario with an estimated probability of 68% versus 32% for “No” (No Goal).

The combined xG of both teams is almost identical: Hegelmann 1.44 and Sūduva 1.43; combining each team’s attacking xG with the opponent’s defensive xG (1.29 and 1.26) yields projected xG ≈1.36 for the home side and ≈1.34 for the visitors, totaling 2.70 expected goals. This season Hegelmann scores 1.71 goals at home on average and has 71% clean sheets, while Sūduva averages only 0.67 goals away but records BTTS in 67% of matches; these divergences are balanced by their chance-creation potential. Additionally Hegelmann has a 15% conversion rate versus Sūduva’s 5%, and in the last 5 matches the home team scored 9 goals (1.8 avg) while the visitors scored 6 goals (1.2 avg), which increases the likelihood of goals. A Poisson model with a total of 2.70 gives probabilities of over 1.5 ≈75%, over 2.5 ≈51% and over 3.5 ≈29%, therefore the strongest signal from the data is a play on Over 1.5.

Hegelmann led at the break in 3 of 7 home matches (43%) and kept a clean sheet at half-time in 86% of home games, while winning 4 of 7 at home (57%), indicating control of the first half and an ability to carry the result. Sūduva averages 0.67 goals scored and concedes 1.17 per game, whereas Hegelmann scores 1.71 and concedes 0.43; the xG of both teams is similar (1.44 vs 1.43), but the hosts have better shot conversion (15% vs the visitors’ 5%). At half-time the hosts rarely trail (lead at the break_home 0%) and average 0.86 goals by HT versus Sūduva’s 0.5, increasing the probability of a Hegelmann lead at 45 minutes. The visitors have not yet won away (winPercentage_away 0%) and in the last 5 matches have only a 20% win rate and 60% draws, so a turnaround by Sūduva appears unlikely. Therefore I assign a 45% probability to the 1/1 scenario, 30% to X/1, 20% to X/X and 5% to 1/X; all options with an away victory I assess as effectively 0%.