Seoul E-Land vs Yongin City: match statistics

Seoul E-Land sit 3rd in the table vs Yongin City in 15th; the hosts have scored 18 and conceded 13 this season, while the visitors have 13 scored and 17 conceded. In the last 5 matches Seoul E-Land scored 8 goals and won 3/5 (avg 1.8 points per game), whereas Yongin have 9 goals and 2 wins in five fixtures (avg 1.4 points), but their away goals average is only 0.75. Seoul E-Land show superior home efficiency: 5 shots on target and 12.8 total shots with a 14% conversion and xG 1.53, versus Yongin’s 3.75 shots on target, 12.5 total shots and 6% conversion (xG 1.46). The visitors do have higher possession (53% vs 50%) and similar defensive xG conceded (1.1 vs 1.07), but away they fail to score in 50% of matches and concede 1.5 goals on average. Considering Seoul E-Land’s 60% home win rate, zero home clean-sheet rate for opponents (0%) and a positive home goal difference (+3), I forecast a home victory.

Seoul E-Land scores on average 1.67 goals and concedes 1.83 per match this season, while Yongin City averages 0.75 goals scored and 1.5 conceded. xG shows Yongin generates more expected chances (xG 1.46 vs 1.13 for Seoul) but has low shot conversion (6% vs 22% for the home side) despite more attempts (12.5 shots vs 7.67) and a similar number of shots on target (3.75 vs 3.83). Seasonal BTTS rates are significant: Seoul has 83% of home matches with both teams scoring, Yongin 50% away, and the league average is 61%; in the last 5 matches BTTS occurred in 60% of Seoul’s games and 80% of Yongin’s. Additionally, Seoul has no clean sheets this season (0%), and over the last 5 matches both teams conceded on average 1.4 (Seoul) and 1.6 (Yongin) goals, which increases the likelihood of BTTS. Considering the 83% home BTTS for Seoul, Yongin’s 80% BTTS in the last 5, and the league average of 2.67 goals per match, I back BTTS - Yes; estimated probability 75% for 'yes' and 25% for 'no'.

I project 1.65 goals for Seoul E-Land and 1.22 goals for Yongin City, totaling 2.87 goals. Seoul averages 1.67 goals per game this season and has an xG of 1.59 over the last 5 matches, while Yongin averages 0.75 goals per game season-to-date but has been scoring 1.8 goals on average in the last 5 rounds with an xG of 1.30, indicating an improvement in the visitors’ attack. Season-long data show Over 1.5 occurred in 83% of Seoul’s matches and 75% of Yongin’s matches, and Over 2.5 was recorded in 83% of Seoul’s fixtures and 50% of Yongin’s; additionally, Over 2.5 has appeared in 80% of both teams’ last 5 matches. A Poisson distribution with an expected total of 2.87 yields approximately a 78% probability for Over 1.5, 55% for Over 2.5 and 32% for Over 3.5, so the strongest and most reliable signal from the data is Over 1.5.

I assess the most likely scenario as 1/1 (home team leading at half-time and winning the match). The home side averages 1.67 goals per game and 1.0 goals by half-time versus the visitors’ 0.75 goals per game and only 0.25 by half-time; the hosts led at the break in 2 matches (33%) while the visitors did not lead at half-time in any (0%). The visitors generate higher xG (1.46 vs 1.13) and more shots (12.5 vs 7.67), but have a very low conversion rate (6% vs the hosts’ 22%), which reduces their ability to turn their advantage into goals. In the last five matches the home team won 60% of fixtures, and in the second halves of those five games they averaged 1.2 goals with a +3 goal differential, which supports maintaining or extending a lead. For these reasons 1/1 is the strongest signal, although X/1 or X/X scenarios remain possible given the visitors’ higher xG.