Regression model for Barclay's Premier League. Using Python, Pandas, StatsModels, Numpy and PyPlot a regression model has been built utilizing Ordinary Least Squares regression analysis on the last four seasons of the Barclay's Premier League. Splitting each year's dataset into overall, home, and away this model seeks to learn which is a better predictor of a team's final league position: home or away. Furthermore, given the home and away datasets, this model seeks to understand which features each dataset share and which features are unique in order to better understand key statistics and decisions throughout the course of a season in the Barclay's Premier League.
This repository contains the source code for the model, all original plots and summaries, original datasets, presentation in PDF form, and analysis.
Author: Christopher Clouten || @triplec1988 || triplec1988 [at] gmail [dot] com
Copyright 2013 Christopher Clouten
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.