2026 FIFA World Cup | About Us · Data & Strategy Analytics

About Us · Data-Driven · Strategy Intelligence

Transparent Algorithms | Quantitative Football | Decision Support zh-zg-pg.com

Core Philosophy · Redefining Football Data Analytics

Data Truth · Strategy Beyond

Data-Driven Decisions

Rejecting subjective bias, we build a quantitative system based on xG, Tempo Index, ELO, and odds dispersion — every strategy is grounded in evidence.

Transparent & Reproducible

Model logic, data sources, and backtest results are fully disclosed, allowing third-party verification to ensure rigor and credibility.

Rational Risk Control

Implementing Kelly-CVaR hybrid position sizing, single-match risk exposure ≤2%, dynamic adjustments in knockout stage for long-term stability.

We believe: within the uncertainty of football matches lie quantifiable patterns. By integrating multi-source data and iterative optimization, we offer a professional perspective for fans and strategy researchers.

Analytical Methodology · Quantitative Models & Data Pipeline

Scientific · Rigorous · Explainable

Expected Goals (xG)

XGBoost regression model based on 100k+ shot samples, integrating distance, angle, defensive pressure, etc. Accuracy R² = 0.86.

Match Tempo Index

Integrating PPDA, transition speed, high-intensity running to quantify pressing intensity and match control.

Odds Value Engine

Aggregates 7 major books, computes dispersion, expected value, and Kelly fraction in real time to identify traps and value betting windows.

Data sources include Opta official events, major odds APIs, team/player profiles. ETL pipeline auto-updates daily to ensure timeliness.

Core Team · Cross-Disciplinary Integration

Football × Data × Engineering

Zhang Lianghua

Quantitative Strategy Director

Former quant fund analyst, specializing in football models & risk management

Li Shuju

Data Engineering Lead

10+ years in sports data architecture, leading ETL and real-time computing

Wang Zhanshu

Football Tactical Analyst

UEFA B license, former youth academy technical advisor

Chen Suanfa

Machine Learning Expert

Kaggle Grandmaster, responsible for xG & odds model iterations
The team spans finance, sports, and computer science, dedicated to applying cutting-edge quantitative methods to football strategy analysis.

Contact & Legal Statement

zh-zg-pg.com · Research Data
Email: contact@zh-zg-pg.com
Website: https://zh-zg-pg.com
Social: @worldcup_analytics
Disclaimer
All data, model outputs, and strategy analysis on this site are for research purposes only and do not constitute actual betting advice. Football matches involve significant randomness; past performance does not guarantee future results. Simulated data is clearly labeled; official schedules are subject to FIFA release. This site does not offer betting services and bears no responsibility for any decision losses.
© 2025-2026 World Cup Data & Strategy Analytics Center | All rights reserved. Commercial reproduction without permission is prohibited.
Data update cycle: odds every 15-20 minutes, match events real-time. Models recalculated daily at 2 AM. Some displayed data are simulated projections.
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