Who wins the Super Bowl? Use this NFL Prediction Python Environment to find out.

Create a predictive algorithm using common machine learning techniques and use it to predict NFL results. In time for the Super Bowl!

View in browser The best NFL handicappers have a 66% success rate. Our algorithm had a success rate >70% over the past season. Can it predict the Super Bowl? You bet. In this blog post, we explain how to create a predictive algorithm using common data analysis and machine learning techniques in order to predict the winners of NFL games. The sports-reference package pulls in key performance stats modified by Nate Silver's ELO rating to produce a model you can use out of the box, or fine tune to your liking. Get started right away with our NFL Game Predictions Python environment for Windows or Linux, which contains a version of Python and all the packages you need to try it out. Game on! Read: How to predict NFL winners with Python You are receiving this email because you signed up for the latest insights from ActiveState. Code for Thought by ActiveState is a monthly email that shares a topic handpicked for you by our Dev Content team. Received this email from a friend? Sign up here. ActiveState Software, 1000 - 1177 West Hastings Street, Vancouver, BC V6E 2K3 Unsubscribe Manage preferences