This repo contains a Jupyter notebook showing how to build a basic Sklearn logistic regression model. We use this algorithm to make predictions related to NFL historical betting lines. In particular, our goal is to estimate the probability that a team with a given line wins a particular game.

Contents

Logistic Regression Example -- .ipynb -- A Jupyter Notebook containing the example code

data -- .csv -- a comma separated value file containing data about past NFL games

conversions -- .csv -- a comma separated value file containing the conversions between NFL teams' long-form names and their three letter abbreviations

An article accompanying this repo can be found at TheDataJocks.com/sklearn-logistic-regression-example