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: