Shanghai SIPG vs Sichuan Jiuniu: match statistics

Shanghai SIPG holds a clear advantage in key metrics: at home they score on average 2.4 goals and concede 1.2 per match, while Sichuan Jiuniu score only 0.5 and concede 2.5 on the road. The hosts control the game with 64% possession versus 38% for the visitors, average 16 shots per match versus 8 and 5.4 on target versus 3.5, which translates into higher xG: 1.88 for the home side against 0.93 for the visitors, with average xG against of 1.17 for Shanghai and 2.01 for Sichuan. Additionally Shanghai has not failed to score at home (FTS 0%) and posts a shot conversion rate of around 15%, while Sichuan only has 6% and fails to score in 50% of their away matches. Form trends also favor the hosts – the visitors have lost all away games (Loss% 100%, away goal difference -8) and have conceded 9 goals in their last 5 matches versus 7 conceded by Shanghai in the same period. Therefore I forecast a home win, considering dominance in possession, double the number of shots (16 vs 8) and superior xG (1.88 vs 0.93).

Shanghai SIPG scores on average 2.0 goals per match (xG 1.46) and concedes 1.4, while Sichuan Jiuniu averages 0.5 goals per match (xG 0.93) and concedes 2.5. This suggests the home side are favorites to score, while the visitors, despite a low scoring output, possess some xG potential. Season BTTS rates are 40% for the home team and 50% for the visitors, with the league average at 56%; in the last 5 matches Shanghai had BTTS 60% versus Sichuan 40%, which presents a mixed signal, but the league context favors BTTS. Shanghai averages 14.2 shots and 4.2 on target with a 14% conversion, and Sichuan 8.0 shots and 3.5 on target with a 6% conversion, so the opportunity advantage is with the hosts increasing the likelihood of their goal, but it does not eliminate the visitors’ chances (Sichuan have 0% away clean sheets). Averaging the xG of both sides (approximately 1.73 for Shanghai = mean of 1.46 and 2.01, and approximately 1.13 for Sichuan = mean of 0.93 and 1.33), a simple model estimates roughly ~55–56% for BTTS; accordingly I assign 60% probability to BTTS - Yes and 40% to No and recommend a Yes tip as the strongest signal from the data.

Based on a comparison of attacking xG and opponent xG, I project 1.74 goals for Shanghai (attacking xG 1.46 vs xG conceded to Sichuan 2.01 → average 1.735) and 1.13 for Sichuan (attacking xG 0.93 vs xG conceded to Shanghai 1.33 → 1.13), totaling 2.87 goals. With λ=2.87 the Poisson distribution yields probability of Over 1.5 around 78%, Over 2.5 around 55% and Over 3.5 around 32%. Season data reinforce an expectation of at least 2 goals: Shanghai scores on average 2.0 goals per match, records 14.2 shots (4.2 on target) and a 14% conversion, while Sichuan scores 0.5 but concedes on average 2.5 goals and has xG against 2.01; the league average is 2.94 goals per match. In the last 5 matches Shanghai scored 7 goals (1.4 per match) and had a 60% occurrence of over 2.5, which further supports a higher total. Consequently the strongest signal is Over 1.5 (recommendation: “over” at the 1.5 line) — Over 2.5 is only marginally favored (~55%) and carries higher risk.

The most likely scenario is Shanghai SIPG leading at the break and winning at full-time (HT/FT = 1/1), as the home side lead at the break in 40% of matches and score an average of 1.2 goals before half-time while conceding 0.6. Shanghai also has a clear advantage in chance creation: home xG averages 1.46 versus 0.93 for the visitors, and shots 14.2 vs 8.0 with conversion rates of 14% vs 6%. Sichuan scores only 0.5 goals per match on the season and concedes 2.5, and records an average of 0.0 goals in the second half, which limits their chances of a turnaround. As a result, the probability distribution gives 1/1 28% and X/1 24%, which together with 2/1 12% yields a total chance of a home win at 64% (28%+24%+12%); a draw after 90 minutes is assessed at 25% (1/X 8% + X/X 12% + 2/X 5%), and an away win at 11% in total (1/2 4% + X/2 4% + 2/2 3%).