Super League Match Analysis
A data-driven analysis summary 11Stat produced for Super League (China): model probabilities, team form, model agreement, data quality and risk level. 10 matches analyzed. This is data analysis, not betting advice.
This page compiles the Super League matches 11Stat analyzed with its multi-engine probability model (Poisson/Dixon-Coles, Elo/form, Monte Carlo). Each match is assessed through 1X2 probability, xG, team form, model agreement and data quality, then summarized with a risk level. No outcome is guaranteed.
Analyzed matches
| Date | Match | Confidence | Star |
|---|---|---|---|
| 2026-07-31 | Henan Jianye - Dalian Zhixing | 6.4/10 | ★★★ |
| 2026-07-27 | Olmaliq - Mash'al | 6.4/10 | ★★★ |
| 2026-07-22 | Mash'al - Nasaf | 6.2/10 | ★★★ |
| 2026-07-21 | Sogdiana - Neftchi | 6.2/10 | ★★★ |
| 2026-07-21 | Pakhtakor - Xorazm | 6.1/10 | ★★★ |
| 2026-07-18 | Dalian Zhixing - Shandong Luneng | 6.4/10 | ★★★ |
| 2026-07-16 | Neftchi - Buxoro | 6.5/10 | ★★★ |
| 2026-07-14 | Hangzhou Greentown - Qingdao Jonoon | 6.1/10 | ★★★ |
| 2026-07-05 | Shanghai Shenhua - Hangzhou Greentown | 6.2/10 | ★★★ |
| 2026-07-04 | Dalian Zhixing - Wuhan Three Towns | 6/10 | ★★★ |
FAQ
How is Super League match analysis done?
11Stat models the league's matches with independent statistical engines, combining probability, model agreement and data quality, then summarizes a risk level. No guarantees.
Does this page give betting tips?
No. It is data-driven probability analysis; not coupons or betting advice.