Huiyang Mao is a football data analyst. This site is a working notebook for match analysis, the models behind it, and the parts of the work that sit between raw event data and a usable conclusion.

What I Work On

My current interests center on:

• expected-goals (xG) and shot-quality models
• tactical and match analysis built on event and tracking data
• scouting and player-recruitment metrics
• data pipelines and visualization for football data

Tools I Use

Most posts grow out of day-to-day work with Python, pandas, NumPy, scikit-learn, and plotting libraries like matplotlib and mplsoccer. I care about methods that are reproducible, inspectable, and useful to revisit months later. Public data from sources like StatsBomb, FBref, and Understat shows up often.

What This Site Covers

The site is organized around two streams:

• Analysis for match, tactical, and player breakdowns
• Data & Models for the xG models, metrics, pipelines, and visualizations behind the analysis

The goal is not polished punditry. It is to keep a precise record of methods and findings that were worth understanding once and will probably be worth understanding again.

Contact

• Email: hymao@pmo.ac.cn
• GitHub: LittleCaps