bracketology 0.0.8

Analyze and simulate NCAA march madness tournaments

Welcome to Bracketology!

The goal of bracketology is to speed up the analysis of NCAA march madness data and help develop algorithms for filling out brackets.

Documentation:

https://bracketology.readthedocs.io/en/latest/

GitHub Repo:

https://github.com/stahl085/bracketology

Issue Tracker:

https://github.com/stahl085/bracketology/issues

Backlog:

https://github.com/stahl085/bracketology/projects/1?fullscreen=true

PyPI:

https://pypi.org/project/bracketology/

Before You Start

Here are the main things you need to know:

• The main parts of this package are the Bracket objects and simulator functions in the simulators module

• A Bracket is composed of Team and Game objects

• Game objects have two Team objects as attributes, and the round number

• Teams have a name, seed, and dictionary for statistics

• Simulator functions have 1 argument of type Game, and return the winning Team of that Game

Installation

Install from pip

pip install bracketology

Or download directly from PyPi

Getting Started

Import bracketology and create a bracket from last year.

from bracketology import Bracket, Game, Team

# Create a bracket object from 2019
year = 2019
b19 = Bracket(year)

Tutorial

Inspecting the Bracket Object

This is how you can look at your brackets

b19.regions
# or
b19.round1
# or
b19.result.get('first')

Creating a Simulator Algorithm

A simulator needs to take in a Game and Return a Team

team1 = Team(name='Blue Mountain State',seed=1)
team2 = Team(name='School of Hard Knocks',seed=2)

game1 = Game(team1, team2, round=1)

def pick_a_random_team(Game):
    return Team

Evaluting Simulator Results

Here we can evaluate two different simulators

# TBD