Nanjing City vs Suzhou Dongwu: match statistics

Nanjing City holds a slight edge in chance creation at home: average xG 1.30 versus 1.04 for Suzhou, and 10.67 shots with 3.67 on target per match compared to 8.33 and 3.00 for the visitors, translating to an average of 1.00 goal per match for the hosts versus 0.67 for the visitors. The hosts show higher finishing efficiency (conversion 9% vs 8%) and score in 67% of home games (fail to score in 33%), while Suzhou fail to score in 67% of away matches. Defensively the visitors are marginally better on averages: they concede 1.00 goal away versus 1.33 conceded by Nanjing at home, but Suzhou have no clean sheets on the road (0%). In the last 5 matches the hosts have 0 wins, 2 draws and 3 losses (0.4 points per game, goal difference 2:6), while the visitors have 2 wins and 3 losses (1.2 points per game, goal difference 3:4). Considering Nanjing’s superior xG and greater volume of created chances, combined with Suzhou’s high share of goalless away games (67%), I indicate a home win as the most likely outcome.

Both teams average 0.67 goals scored per season and concede 1.00 goals per match; seasonal BTTS rate is only 33% for Nanjing and 33% for Suzhou, below the league BTTS average of 40%. The league records a very high clean sheet rate — 70% of matches — which is 37 percentage points higher than the seasonal BTTS for both teams (70% vs 33%), strongly arguing against a scenario where both teams score. In the last 5 matches the home side had BTTS in 40% (2/5) and the away side in 20% (1/5), averaging roughly 30% and showing a weak BTTS trend in recent form. Both teams have higher xG than actual goals — Nanjing xG 1.13 vs 0.67 goals, Suzhou xG 1.04 vs 0.67 goals (differences ~0.46 and 0.37) — and the low shots on target 2.0 vs 3.0 plus conversion rates 10%/8% further limit the probability of goals from both sides. For these reasons I prefer the No variant and estimate a 30% chance for BTTS - Yes and 70% for No.

Both teams have low goal output: Nanjing City averages 0.67 goals, Suzhou Dongwu 0.67, yielding an expected 1.34 goals per match. Although xG is 1.13 for the home side and 1.04 for the away side (total 2.17), the low number of shots (6.67 and 8.33), few shots on target (2.0 and 3.0) and conversion rates of 10% and 8% indicate finishing is below what xG suggests. Seasonally only 33% of these teams’ matches finish Over 2.5 goals and 0% exceed 3.5 goals; in the last 5 meetings Over 2.5 occurred in just 20% of cases. A model based on seasonal averages (expected 1.34 goals) gives approximately 39% for Over 1.5, 15% for Over 2.5 and 5% for Over 3.5, therefore the strongest signal is Under 3.5.

Nanjing City led at the break in 1 of 3 home matches (33%) and were trailing in 2 of 3 (67%), so statistically Suzhou Dongwu is more likely to lead at the break. In the second half the visitors score on average 1.33 goals versus 0.67 for the hosts, but they also concede on average 1.0 goal after the break, which increases the chance of a turnaround. xG shows a slight advantage for the hosts in chance creation (xG 1.13 vs 1.04), yet the hosts allow more xG (1.64 vs 1.20) and have fewer on-target shots (2.0 vs 3.0), suggesting Suzhou has a defensive HT advantage but is not immune to conceding. In the last 5 matches the hosts averaged 0.4 points per game while the visitors averaged 1.2 points, which further favors the visitors at half-time. Given these data I select HT/FT 2/X (visitors lead at the break, draw after full-time) as the most likely scenario.