An asynchronous Python package for https://understat.com/.
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Updated
Dec 16, 2025 - Python
An asynchronous Python package for https://understat.com/.
A machine learning/statistical model to derive prediction probabilities for football matches of the top european leagues.
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Simple python package to identify optimal bet size and odds using basic Kelly Criterion and Expected Values.
Kelly Criterion calculator for sports betting and investing. CLV tracking, bankroll stats, odds conversion. TypeScript, zero deps, tree-shakeable.
Educational probability engine for Cash4Life demonstrating mathematical truth about lottery odds. Created by Shilezi. Live demo: https://shilezi.github.io/cash4life-probability-analyzer/
Binomial distribution expected value.
In this project, the inverse normal Cumulative Distribution Function (CDF), Monte Carlo Expected Value have been implemented with the help of Python functions.
Developed an expected strokes model to identify player performance for the 2011 PGA TOUR Championship
SQL-first retention incentive decision engine: expected value optimization, p95-governed budget allocation, and scenario sensitivity testing (Olist).
Scraping odds and true probabilities (black box) to calculate expected value (EV) on soccer matches.
Statistical and discrete analysis of the normal distribution of six-sided dice
Files for my YouTube video titled 'Frog Jumps Randomly | Value Function Strategy (LIVESOLVE)'.
Clear practical guide to decision trees — the foundational tool for structured decision analysis in business, medicine, and AI
A lightweight, header-only C++ library that provides a result type for monadic error handling .
Statistical decision system to determine when to promise 1-day delivery in a multi-region marketplace.
Repository to preview, describe, and link to Tableau dashboard.
Streamlit app that converts betting odds into implied probability, fair odds, expected value (EV), and recommended stake sizing.
Multi-sport prop betting engine. XGBoost models + FanDuel odds + PrizePicks lines. NBA (17 models) and Tennis (7 models).
Machine Learning Expected Value Variance Co-variance
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