Fantasy Cruncher

A lightweight tool for analyzing Fantasy Football data

Fantasy Cruncher includes two main functions: Linear Regression and Sorting

Linear Regression mode uses the selected metric over two subsequent seasons and averages these regressions over the selected time period

A number of parameters can be set for either mode to customize the search, regression, or sort values and output

Readme

Fantasy Cruncher

How to use the Fantasy Cruncher GUI and how adjusting the different parameters affects the type of analysis and output.

Demo

Features

  • Based on csv data from 1970-2019 directly imported from Fantasy Football Data Pros

  • Uses the raw data to create new categories including averages per game and fantasy points based on customizable league rules

  • 39 customizable search parameters

  • Output options include single categories, all categories, or groups of categories (such as "All Passing Stats")

  • Linear regression accounts for edge cases such as two players with the same name (like two Steve Smiths in the same season)

Skills Learned

  • Using NumPy, pandas, and scikit-learn to analyze raw csv data

  • Creating a GUI using TKinter

  • Packaging a Python project

Acknowledgments

  • Thanks to Fantasy Football Data Pros for providing the raw data for this project