⚽ Quantitative In-Play Corner Rate Engine

Live Demo:

A real-time quantitative sports trading and risk management engine designed to identify Expected Value (+EV) mispricings in live football corner markets. Powered by a Negative Binomial probability distribution model and an interactive Streamlit frontend.

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🌟 Key Features

• Statistical Pricing Engine: Uses Negative Binomial distribution (scipy.stats.nbinom, $r=12$) over standard Poisson to capture variance, clustering, and tail risk in corner counts.
• Non-Linear Time Decay: Models remaining corner intensity ($\lambda_{rem}$) using a non-linear $t^{0.85}$ decay function combined with live momentum rates ($P$).
• Tactical Score & Heat Modifiers: Dynamically adjusts expected rates based on shot heat (total vs. target shots), goal-line margins, aggregate leg scores, and red card impact.
• Automated Trading Diagnostics: Triggers Sniper Over / Sniper Under signals only when strict $+EV$ (>15%), time window, momentum ($P$), and line buffer conditions are met.
• Dynamic League Risk Tiers: Persistent JSON storage (leagues.json) enforcing 3-tier risk control:
  • ALLOWED: Full trading.
  • NO_UNDER: Prohibits Under trades in high-variance leagues (e.g., MLS, Eredivisie, Scandinavian divisions).
  • BANNED: Suspends trading on volatile markets (e.g., South American domestic leagues).
• Interactive Dashboard: Full Streamlit interface featuring dynamic metric cards, pass/fail signal breakdowns, and real-time league tier management.

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🛠️ Tech Stack

• Language: Python 3.10+
• Data & Analytics: SciPy, NumPy
• Frontend: Streamlit
• Persistence: JSON (leagues.json)
• Version Control: Git / GitHub

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🚀 Quick Start

1. Clone Repository

git clone https://github.com/nick6988/corner-rate-engine.git
cd corner-rate-engine

2. Set Up Environment & Install Dependencies

python -m venv venv
# On Windows PowerShell:
.\venv\Scripts\Activate.ps1

pip install -r requirements.txt

3. Launch Streamlit Dashboard

streamlit run app.py

Open http://localhost:8501 in your browser.

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📂 Project Architecture

├── app.py               # Streamlit dashboard & UI logic
├── corner_engine.py     # Quantitative engine & probability calculation core
├── league_filter.py     # Dynamic JSON reader/writer for league risk tiers
├── leagues.json         # Storage file for league translations and risk tiers
├── requirements.txt     # Python package dependencies
└── .gitignore           # Git exclusion rules