keeks

A python library for bankroll allocation strategies

Python MIT
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Python 98.4% Makefile 1.6%

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Project Info

Created
December 9, 2017
Last Updated
December 12, 2025
License
MIT
Default Branch
master

About This Project

Keeks is a Python library for optimal bankroll management and betting strategies. It implements the Kelly Criterion and various fractional Kelly strategies for making mathematically optimal betting decisions.

Features

  • Kelly Criterion: Full and fractional Kelly calculations
  • Risk Management: Conservative betting strategies
  • Simulation: Monte Carlo bankroll simulations
  • Multiple Outcomes: Support for multi-outcome scenarios

Installation

pip install keeks

Quick Start

from keeks import KellyCriterion

# Create a Kelly calculator
kelly = KellyCriterion(bankroll=1000)

# Calculate optimal bet size
# For a bet with 60% win probability and 2:1 odds
bet_size = kelly.bet_size(win_prob=0.6, odds=2.0)

print(f"Optimal bet: ${bet_size:.2f}")

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