bracketeer

Generate predicted bracket from a kaggle march madness machine learning competition submission. https://www.kaggle.com/c/march-machine-learning-mania-2017

Installation

To install, do one of the following two things:

pip install bracketeer

OR

git clone https://github.com/cshaley/bracketeer.git
cd bracketeer
python setup.py install

Usage:

from bracketeer import build_bracket
b = build_bracket(
        outputPath='output.png',
        teamsPath='data/Teams.csv',
        seedsPath='data/TourneySeeds.csv',
        submissionPath='data/submit.csv',
        slotsPath='data/TourneySlots.csv',
        year=2017
)

Dependencies

• binarytree
• matplotlib
• numpy
• pandas
• PIL

Additional input data/files not provided on kaggle:

• empty_bracket.jpg - empty ncaa bracket
• slot_coordinates.py - mapping dictionary from slots to image coordinates on empty_bracket.jpg
• ordered_seed_list.py - order of seeds on the bracket

Output is a bracket filled in with team seeds, names, and winning likelihood for each game.
The empty bracket is shown below.

The predicted bracket (this program's output) is shown below: