deep-analysis

Analyze football matches with a 10-step process integrating odds and injury data.

3|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/philipbo/openclaw-pansuan --skill deep-analysis-philipbo
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deep-analysis
Source: https://github.com/philipbo/openclaw-pansuan/tree/main/skills/deep-analysis
Command: npx skills add https://github.com/philipbo/openclaw-pansuan --skill deep-analysis-philipbo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive, step-by-step analysis of football (soccer) matches, moving beyond basic statistics to offer deep insights into team form, tactical nuances, and betting market movements.

Core Features & Use Cases

  • 10-Step Analysis: Covers fundamentals, injuries, odds movements (European, Asian, Over/Under), value assessment, risk, and score prediction modeling.
  • Data Integration: Leverages real-time odds data from multiple bookmakers and historical match data.
  • Use Case: A user wants to understand the true value of a specific match. They can ask the AI to perform a deep analysis, which will output a detailed breakdown of factors influencing the game, including a predicted score and betting recommendations with confidence levels.

Quick Start

Use the deep-analysis skill to analyze the match with ID 2950979.

Frequently Asked Questions about deep-analysis

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

FAQPage Schema
How do I analyze football match odds to find betting value?

To find betting value, this analysis integrates real-time odds from multiple bookmakers with fundamental data and historical performance, modeling score probabilities using Poisson distribution to identify discrepancies between AI predictions and market odds.

How does Poisson distribution work for predicting football match outcomes?

Poisson distribution models score probabilities by calculating the likelihood of goal counts based on historical team performance. It outputs predicted match outcomes, handicaps, and total goals by comparing these mathematical probabilities against actual bookmaker odds.

Can I use match prediction data to analyze both Asian and European handicaps?

Yes, the analysis covers odds movements across European, Asian, and Over/Under markets. It processes these handicap formats by assessing risk and value, providing actionable betting recommendations with specific confidence levels for each market type.

What data do I need for a deep analysis of a specific football match?

You need to provide a specific match ID to retrieve fundamental data, injury reports, and historical performance. The analysis automatically fetches real-time odds from multiple bookmakers to execute its 10-step evaluation process.

What is the best way to integrate injury reports into match prediction modeling?

The best way to integrate injury reports is through a multi-step fundamental analysis that weighs player availability alongside tactical nuances and historical performance. This produces a holistic match prediction that adjusts score probabilities for missing key players.