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    NemoFish

    NemoFish

    ASGCompute March 15, 2026
    3 copies 0 downloads

    Swarm intelligence engine for sports prediction - 6 AI agents analyze 971K+ matches across 57 years to forecast tennis outcomes. Built on MiroFish.

    Agent Definition
    <div align="center">
    
    <img src="./static/image/NemoFish_logo_compressed.jpeg" alt="NemoFish Logo" width="65%"/>
    
    ### Swarm Intelligence Engine for Predictive Analytics
    
    **Multi-agent reasoning · Consensus scoring · Autonomous execution**
    
    [![GitHub Stars](https://img.shields.io/github/stars/ASGCompute/NemoFish?style=flat-square&color=DAA520)](https://github.com/ASGCompute/NemoFish/stargazers)
    [![License](https://img.shields.io/badge/License-GPL--3.0-blue?style=flat-square)](./LICENSE)
    [![ASG Compute](https://img.shields.io/badge/ASG%20Compute-R%26D-000?style=flat-square)](https://asgcompute.com)
    
    [Quick Start](#-quick-start) · [How It Works](#-how-it-works) · [Dashboard](#-unified-control-room) · [Credits](#-credits)
    
    </div>
    
    ---
    
    ## Overview
    
    **NemoFish** is a swarm intelligence platform that coordinates multiple AI agents to generate probabilistic forecasts for competitive sports events. Each agent brings a different analytical lens — statistical modeling, psychological profiling, market signal analysis, scenario simulation — and they reach consensus through weighted voting. The system then scores opportunities by expected value and can execute positions on prediction markets autonomously.
    
    This project began as a fork of [**MiroFish**](https://github.com/666ghj/MiroFish), an open-source multi-agent simulation engine developed by the CAMEL-AI research community. We extended MiroFish with a full-stack sports analytics pipeline and a unified control room for real-time monitoring.
    
    > **An R&D project by [ASG Compute](https://asgcompute.com)** — exploring whether coordinated multi-agent reasoning can identify inefficiencies in prediction markets.
    
    ---
    
    ## 📊 Scale & Data Coverage
    
    <div align="center">
    
    | Metric | Value |
    |:-------|------:|
    | **Historical matches analyzed** | **971,320** |
    | **Unique players profiled** | **33,962** |
    | **Tournaments covered** | **9,201** |
    | **Years of ATP data** | **1968 – 2026** (57 seasons) |
    | **Surfaces modeled** | Hard · Clay · G

    Tags

    aideepseekllmmachine-learningmulti-agent-systemsopen-sourceprediction-marketpredictive-analyticspythonsports-analytics

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