Shanghai Jiading vs Nantong Zhiyun: match statistics

Shanghai Jiading have scored 12 goals in their last 5 matches (2.4 per match) and won 4 of those 5 games. Over the same period Nantong Zhiyun scored 4 goals and averages 1.4 points per match. At home Shanghai averages 11 shots and 3.25 on target per match, with a 14% conversion rate and an average xG of 1.49 (actual 1.5 goals per match), while Nantong away averages 8.75 shots, 2.5 on target, converts only 6% and scores 0.5 goals on average with an xG of 1.14. Defensively the hosts concede 1.75 goals at home on average (xG against 1.25), whereas the visitors concede 1.0 goal away and keep 50% clean sheets, although in the last 5 matches Nantong conceded 5 goals (1.0 per match). Additionally, Nantong fail to score in half of their away matches (50% of games without a goal) and according to the data have 0% away wins with 75% draws and 25% losses. Considering 12 goals vs 4 goals and the hosts’ superior finishing (14% vs 6%), I give Shanghai Jiading the higher probability of winning.

I pick “No” (no BTTS) because the home side has 80% clean sheets this season and concedes only 0.2 goals per match on average, while the away team scores just 0.5 goals per match. Home seasonal BTTS is only 20% versus 50% for the visitors, against a league average BTTS of 46%, indicating the hosts more frequently close matches with a clean sheet. Both teams have similar xG (1.15 vs 1.14), but the hosts are far more clinical: conversion 13% compared to 6% for the away side, and in the last 5 matches the home team averaged 2.4 goals vs 0.8 for the visitors. Although BTTS in the home side’s last 5 matches was 60% and their recent xG conceded is about 1.0, the visitors’ poor scoring form (4 goals in 5 matches) and the high rate of home clean sheets (80%) prevail, so I give 75% to “No” and 25% to “Yes” as the most likely scenario.

Combined offensive xG is 1.15 (Shanghai) and 1.14 (Nantong), defensive xG 0.93 (Shanghai) and 1.29 (Nantong), which averaged gives an expected 1.22 goals for the home side and 1.03 for the away side, totaling 2.25 goals. With that expectation the model indicates roughly a 66% chance for Over 1.5 goals, ~39% for Over 2.5 and ~19% for Over 3.5, therefore Over 1.5 is the strongest probabilistically. The last 5 matches reinforce this: Shanghai scored 12 goals in the last 5 (avg. 2.4), while Nantong have 4 in the last 5 (avg. 0.8), and the home side’s shot conversion is 13% vs 6% for the visitors. At the same time, seasonally Shanghai have 80% clean sheets at home and only 20% of home matches over 1.5, which explains the reduced probability for Over 2.5 and 3.5; thus the recommendation is Over 1.5 as the best risk-to-reward option.

The home team are clear favorites: they have a 100% home win rate (winPercentage_home 100%) and average 3.0 points per home match (seasonPPG_home 3.0), whereas the away side have not won any games (winPercentage_away 0%) and average 0.75 points per match (seasonPPG_away 0.75). At Half-Time draws dominate — the hosts are level at the break in 80% of matches (drawingAtHTPercentage_home 80%) and have kept a clean sheet at Half-Time in 100% of cases (seasonCSPercentageHT_home 100%), so an HT outcome toward a draw is the most likely. In the second half, however, the home team have the edge: they score on average 1.2 goals per match (seasonScoredAVG_home 1.2) versus 0.5 for the visitors, have a higher shot conversion (13% vs 6%) and lower xG conceded (0.93 vs 1.29), indicating a greater chance of the hosts scoring after the break. In the last five matches the hosts led at Half-Time in 60% of games (last5_leadingAtHTPercentage_overall_home 60%), which further supports the 1/1 scenario as the second most significant signal. Therefore the best bet is X/1 (draw at Half-Time, home win Full-Time), which I treat as the most probable outcome (approximately 40% of the scenario distribution).