soccer-lottery

Analyze soccer match data using H2H statistics, injuries, and odds trends.

58|13|Updated Apr 16, 2026
One-click install
npx skills add https://github.com/liming199364/soccer-lottery --skill soccer-lottery
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: soccer-lottery
Source: https://github.com/liming199364/soccer-lottery/tree/main
Command: npx skills add https://github.com/liming199364/soccer-lottery --skill soccer-lottery

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, beautifulsoup4, pyyaml, lxml, and includes scripts (resource) components.

What problem does it solve?

This Skill removes the guesswork from sports betting by automating the collection and synthesis of complex match data, historical trends, and market sentiment.

Core Features & Use Cases

  • Three-Dimensional Analysis: Combines战意 (motivation), odds trends, and historical form to generate high-confidence predictions.
  • Smart De-weighting: Automatically adjusts confidence scores for high-heat matches involving major clubs to prevent over-betting.
  • Use Case: When you are unsure about a weekend match, ask the AI to analyze the fixture; it will cross-reference H2H history, injury reports, and market movements to provide a clear direction and confidence rating.

Quick Start

Ask the AI to provide a soccer analysis for today by saying the phrase today's red list or how should I buy.

Frequently Asked Questions about soccer-lottery

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate soccer match prediction using historical statistics and market odds?

Automate soccer match prediction by integrating historical H2H statistics, injury reports, and market odds trends into a weighted model. This approach applies team motivation and market sentiment to generate high-confidence betting decisions.

What is a three-dimensional analysis model for sports betting data?

A three-dimensional analysis model for sports betting combines team motivation, odds trends, and historical form to evaluate match outcomes. It automatically adjusts confidence scores to prevent over-betting during high-heat matches involving major clubs.

Do I need external API access to run soccer betting analysis?

Yes, you need external API access to football-data.org and web search capabilities to verify real-time match information. These dependencies are required to collect historical statistics and current injury reports for analysis.

What's the best way to analyze high-heat soccer matches and prevent over-betting?

Analyze high-heat soccer matches by applying smart de-weighting to automatically adjust confidence scores for major clubs. This prevents over-betting by prioritizing actual team motivation and market sentiment over public hype.

Can I use web scraping with beautifulsoup4 to collect soccer injury reports and odds data?

Yes, the analysis workflow utilizes beautifulsoup4 and lxml alongside requests to scrape web data for verifying real-time match information. This scraped data supplements external API feeds for comprehensive prediction modeling.

When should I not use automated weighted models for soccer betting predictions?

Avoid using automated weighted models when external API access to football-data.org is unavailable or real-time web search fails. Predictions require accurate historical H2H statistics and current injury reports to function properly.