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match-simulation-system

Forecast esports match outcomes using normal distribution and BO-series rules.

2|Updated Feb 7, 2026
Search Tags:#probability#esports#trait-system#match-simulation#normal-distribution#bo-format#meta-engine
One-click install
npx skills add https://github.com/Showiix/EsportManager2 --skill match-simulation-system
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: match-simulation-system
Source: https://github.com/Showiix/EsportManager2/tree/main/.claude/skills/match-simulation-system
Command: npx skills add https://github.com/Showiix/EsportManager2 --skill match-simulation-system

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Match Simulation System provides a probabilistic engine to forecast esports match outcomes using a normal distribution, accounting for different BO formats and dynamic team power.

Core Features & Use Cases

  • Normal-distribution based power sampling to simulate games
  • Supports Bo1, Bo3, Bo5 match formats and calculated win probabilities
  • Trait-aware adjustments and meta-weight integration for season-long campaigns
  • Integration with engine components and front/back-end interfaces for end-to-end simulations

Quick Start

Run a default BO5 simulation to forecast the winner using current meta weights.

Frequently Asked Questions about match-simulation-system

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

FAQPage Schema
How do I simulate esports match outcomes using a normal distribution?▼

To simulate esports match outcomes using a normal distribution, you model team performance by sampling power values and applying BO-series rules. This system uses a default standard deviation of 6.0 to calculate win probabilities across different match formats.

Can I forecast Bo1, Bo3, and Bo5 match results with a trait system?▼

Yes, you can forecast Bo1, Bo3, and Bo5 match results with a trait system. The simulation engine applies trait-aware adjustments and meta-weighted power calculations to determine the winner across these various best-of formats.

What is the best way to calculate win probability for a season-long esports campaign?▼

The best way to calculate win probability for a season-long esports campaign is to use meta-weighted power calculations and trait adjustments. This allows the simulation engine to account for dynamic team power shifts throughout the season.

How do I run a default BO5 simulation to forecast an esports winner?▼

You run a default BO5 simulation to forecast an esports winner by invoking the configurable engine with current meta weights. The engine handles game sampling and match simulation to output the predicted winning team.

Does the match simulation engine support custom standard deviations for team performance?▼

The match simulation engine uses a default standard deviation of 6.0 for team performance sampling. It is configurable, allowing you to adjust power calculations and trait systems for deterministic match outcomes.

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