This project uses Monte Carlo Simulation to predict players' win rates given their hands on a game of Texas Holdem.
The codebase is written using Python 3.8.8 with a virtual environment attached. Feel free to execute the code without this since it only utilizes basic Python packages such as random.
To clone and run this application, you'll need Git installed on your computer. From your command line:
# Clone this repository
$ git clone https://github.com/hele2069/WinTexasHoldem
# Go into the repository
$ cd WinTexasHoldem
# Activate Virtual Environment (if needed)
$ conda activate myenv
# Run the code
$ python run.py----- SETTINGS -----
Number of Players: 3
Number of Simulations: 1000
----- SUMMARY -----
PLAYER 1: ['5h', '2s'] (Win Rate: 0.186)
PLAYER 2: ['Jd', 'Qs'] (Win Rate: 0.429)
PLAYER 3: ['As', '2d'] (Win Rate: 0.394)
Tie Rate: 0.003
----- HAND WIN RATE -----
PLAYER 1:
high_card: 0
pair: 0.04194
two_pair: 0.29614
three_of_a_kind: 0.3617
straight: 0.86047
flush: 0.84211
full_house: 0.875
four_of_a_kind: 1.0
straight_flush: 0
royal_flush: 0
PLAYER 2:
high_card: 0
pair: 0.18653
two_pair: 0.61628
three_of_a_kind: 0.52113
straight: 0.88406
flush: 0.75
full_house: 0.86364
four_of_a_kind: 0
straight_flush: 0
royal_flush: 0
PLAYER 3:
high_card: 0.016
pair: 0.23056
two_pair: 0.65532
three_of_a_kind: 0.55556
straight: 0.69231
flush: 0.75
full_house: 0.8
four_of_a_kind: 1.0
straight_flush: 0
royal_flush: 0
----- HAND DRAW RATE -----
PLAYER 1:
pair: 0.763
two_pair: 0.233
three_of_a_kind: 0.047
straight: 0.043
flush: 0.019
full_house: 0.016
four_of_a_kind: 0.001
straight_flush: 0.0
royal_flush: 0.0
PLAYER 2:
pair: 0.772
two_pair: 0.258
three_of_a_kind: 0.071
straight: 0.069
flush: 0.012
full_house: 0.022
four_of_a_kind: 0.0
straight_flush: 0.0
royal_flush: 0.0
PLAYER 3:
pair: 0.746
two_pair: 0.235
three_of_a_kind: 0.045
straight: 0.013
flush: 0.012
full_house: 0.01
four_of_a_kind: 0.001
straight_flush: 0.0
royal_flush: 0.0