Suzhou Dongwu vs Guangxi Hengchen: match statistics

The favorites in this fixture appear to be the visitors: Guangxi sit 8th in the table vs 14th for Suzhou, have scored 5 goals this season vs 3 for the hosts and have found the net 6 times in their last five matches compared to Suzhou’s 4. The visitors create more chances — on average 12 shots per match and 4 on target vs 8 shots and 1 on target for the hosts — and average xG of 1.46 for Guangxi vs 1.17 for Suzhou, despite the hosts having a higher conversion rate (13% vs 8%). Both teams concede on average 2.0 goals per match, but Suzhou have a higher home xG against at 1.59 vs 1.32 for the visitors and an alarming 100% loss rate in home matches, which is a strong defensive weakness signal. Recent form over the last five matches is similar — both teams average 1.2 points per match and have 2 wins in that period — however the visitors’ superiority in chance creation and the better season goal balance of 5–3 favor Guangxi. Therefore I tip an away win, with an estimated probability distribution of 45% for an away win, 30% for a draw and 25% for a home win.

I back BTTS - Yes because Guangxi Hengchen has a seasonal BTTS rate of 100% and 80% in the last 5 matches, while Suzhou Dongwu records 50% for the season and 40% in their last five. The visitors concede an average of 2.0 goals over the season (1.4 in the last 5) and score 1.0 in the season (1.2 in the last 5), indicating their matches regularly feature goal exchanges. The home side concedes only 0.5 goals for the season and keep clean sheets in 50% of matches, but their seasonal xG is 1.93 (last 5: 1.19) and they average 7.0 shots on target versus the visitors’ 4.0, so they also have scoring potential. Additionally, Guangxi’s matches this season have been over 2.5 goals in 100% of cases and BTTS in 100% of cases; the league shows 45% BTTS and 57% clean sheets, so the strong individual profile of the visitors shifts the balance towards both teams scoring. Based on this I assess BTTS probability at 75% (Yes) and 25% (No).

Average xG indicates 1.63 expected goals for the home side (1.93 xG attack vs 1.32 xG defense of the away team) and 1.23 expected goals for the visitors (1.46 xG attack vs 1.00 xG defense of the home team), totaling 2.86 expected goals. The home side averages 16.5 shots with 7.0 on target and a 9% conversion, aligning with a seasonal average of 1.5 goals; the away side averages 12.0 shots with 4.0 on target with an 8% conversion and a seasonal average of 1.0 goal. In a Poisson model with lambda=2.86 the probability of over 1.5 goals (>=2) is about 78%, and over 2.5 goals (>=3) about 54%. Season statistics reinforce the offensive profile: the away team has 100% of matches over 2.5 goals this season and 80% in the last 5, the home team 50% seasonally and 40% in the last 5, hence an adjusted probability for over 1.5 at 86% and over 2.5 at 68%. The absence of matches over 3.5 goals in both teams' stats (seasonOver35 0% vs 0%) reduces confidence in very high scores, so over 3.5 is priced at 16% and I recommend over 1.5 as the strongest signal.

The home team are clear favorites: they have a 100% win rate and average 1.5 goals scored and only 0.5 conceded per match (winPercentage_home 100.0; seasonScoredAVG_home 1.5; seasonConcededAVG_home 0.5), while the away side have no wins and concede an average of 2.0 goals per game (winPercentage_away 0.0; seasonConcededAVG_away 2.0). In attack the hosts generate higher xG — 1.93 versus the visitors’ 1.46 — and register more on-target shots (7.0 vs 4.0), which translates into a greater number of scoring opportunities. At Half-Time the home team do not concede on average (concededAVGHT_home 0.0) and led in 50% of matches with an average of 0.5 goals at the break (leadingAtHTPercentage_home 50.0; scoredAVGHT_home 0.5), so they are most often leading or level after 45 minutes. In the second half the hosts score an average of 1.0 and concede 0.5 (scored_2hg_avg_home 1.0; conceded_2hg_avg_home 0.5), while the away team concedes an average of 1.5 after the break (conceded_2hg_avg_away 1.5), which increases the chance of maintaining or extending the lead. For these reasons I pick 1/1 (home team leading at Half-Time and winning Full-Time) as the strongest scenario.