← Projects
PLOScope Stack

PLOScope Stack

Poker platform orchestration system. Analytics, hand tracking, and session management for serious PLO players.

PythonGoRedis

Poker platform orchestration system. Analytics, hand tracking, and session management for serious PLO players.

PythonGoRedis
GitHub ↗

PLOScope

A platform for analyzing Pot-Limit Omaha poker hands. It brings together multiple microservices. hand history parsing, equity calculation, range analysis, and a web frontend. into a single orchestrated stack.

The Problem

PLO is a complex game with massive decision trees. Existing tools are either expensive, Windows-only, or don’t handle PLO well. I needed something purpose-built for the game I actually play. something I could run locally and extend as my study evolved.

Architecture

graph TB
    subgraph Frontend["Frontend"]
        UI[React Web App]
        DASH[Dashboard & Charts]
    end

    subgraph Gateway["API Gateway"]
        GW[FastAPI Gateway]
        AUTH[Auth Middleware]
    end

    subgraph Services["Microservices"]
        HHP[Hand History Parser]
        EQ[Equity Engine]
        RA[Range Analyzer]
        GTO[GTO Solver]
    end

    subgraph Data["Data Layer"]
        PG[(PostgreSQL)]
        REDIS[Redis Cache]
        FS[Hand History Files]
    end

    UI --> GW
    DASH --> GW
    GW --> AUTH
    AUTH --> HHP
    AUTH --> EQ
    AUTH --> RA
    AUTH --> GTO
    HHP --> PG
    HHP --> FS
    EQ --> PG
    EQ --> REDIS
    RA --> PG
    GTO --> REDIS

How It Works

  • Hand history parsing. ingests hand histories from major poker sites, normalizes formats, and stores structured data in PostgreSQL
  • Equity engine. Monte Carlo simulations for calculating hand equities across board textures
  • Range analysis. builds and stores range profiles against different opponent types
  • GTO solver. runs game-theory-optimal calculations for decision review
  • Microservice orchestration via Docker Compose with a central stack repo

What I Learned

  • Monte Carlo performance matters when you’re running millions of equity simulations. Caching intermediate results in Redis cut computation time by 10x for repeated range queries.
  • Parsing hand histories from different poker sites is an exercise in dealing with inconsistent formats. Every site has its own quirks.
  • Docker Compose as a microservice orchestrator works surprisingly well for a project this size. no need for Kubernetes when you have 5 services and one developer.