Shaanxi Union vs Nanjing City: match statistics

A draw appears most likely. Shaanxi Union at home has 67% of matches ending in a draw and 0% losses, conceding only 0.33 goals per game on average and keeping a clean sheet in 67% of home fixtures. Nanjing City away has yet to win an away match (0% wins), records 50% draws on the road and concedes 1.00 goal per away game on average, with just 0% clean sheets. Both teams have low offensive output: Shaanxi scores 0.67 goals per home game with an xG of 1.23, while Nanjing averages 0.5 goals away with an xG of 1.15; additionally the share of goalless games is 33% for the hosts and 50% for the visitors. Considering the hosts’ stable defense, the visitors’ poor away efficiency and the form balance (Shaanxi 7 goals in the last 5 matches and 1.8 points per game over the last 5, Nanjing 4 goals and 1.4 points), I predict a draw (X) as the most reliable outcome: home 30%, draw 55%, away 15%.

I project BTTS = No: Shaanxi Union kept a clean sheet in 60% of their matches this season, while Nanjing City failed to score in 50% of games, which strongly favors a shutout for the visitors. The hosts average 1.2 goals per game (xG 1.37) and have scored 7 goals in their last 5 matches (1.4 avg) while conceding only 0.4, so they are the more likely source of any sole goals. The visitors have a season scoring average of 0.5 goals, only 2.0 shots on target per game and a 4% conversion rate, despite a recent xG of 1.36 — they create chances but rarely convert. Additionally, BTTS in the last 5 matches is 40% for Shaanxi and 20% for Nanjing, while the league average BTTS is 46%; the combination of the hosts' 60% clean sheets and the visitors' poor finishing lowers the probability of both teams scoring. Based on this I assign BTTS probabilities: 35% for 'yes' and 65% for 'no', therefore I recommend 'no' as the strongest signal.

The xG-based model uses home xG 1.37 and xG against 1.38, and away xG 1.15 with xG against home 1.03, yielding expected goals of ~1.38 for Shaanxi and ~1.09 for Nanjing, total ~2.47. With λ=2.47 and a Poisson distribution the probability of Over 1.5 goals is about 71%, Over 2.5 about 45%, and Over 3.5 about 24%. Season stats support a moderate goals environment: Shaanxi has Over 1.5 in 60% of matches and scored 7 goals in the last 5 (1.4 per game), Nanjing has Over 1.5 in 50% and scored 4 in the last 5 (0.8 per game). On the other hand both teams have low Over 2.5 rates (Shaanxi 40%, Nanjing 0%), which reduces the likelihood of a high-scoring game, so Over 2.5 is clearly less certain than Over 1.5. Considering the total xG ~2.47, form and the Poisson distribution, the strongest signal is Over 1.5 (pick: over on the 1.5 line) with the model edge around 71%.

Shaanxi Union led at the break in 40% of matches (leadingAtHTPercentage_home = 40.0) and won matches in 60% of cases (winPercentage_home = 60.0), therefore the scenario of leading at half-time and winning at full-time (1/1) is the strongest signal. The hosts score on average 0.6 goals by half-time versus 0.25 for the visitors (scoredAVGHT_home = 0.6 vs scoredAVGHT_away = 0.25), have higher xG (1.37 vs 1.15) and more shots on target (4.0 vs 2.0), and a conversion rate of 11% versus 4% increases their efficiency in front of goal. Nanjing City has not kept a clean sheet this season (seasonCSPercentage_away = 0.0) and scores only 0.5 goals per match (seasonScoredAVG_away = 0.5), which limits their ability to produce a turnaround after half-time. As a result I assign 34% to 1/1 as the primary option, with alternatives X/1 = 18% and X/X = 18%; scenarios with an away win are unlikely (7% in total for all away-win variants).