Skip to main content

NFL.com's Football Freakanomics

EDIT: All of this content appears to have been removed from NFL.com. If anyone has any luck finding it, please email me at hartnett004@gannon.edu

The NFL and the statistics folks over at Freakonomics got together and made some...learning modules? Let's call them learning modules. They are interactive websites that teach users about very specific questions related to football (like home field advantage, instances when football player statistics don't tell the whole story about a player/team, whether or not firing a head coach improves a failing team, the effects of player injury on team success, etc.) and then answer these questions via statistics.

Most of the modules include interactive tables, data, and videos (featuring the authors of Freakanomics) in order to delve into the issue at hand.

For example:

The Home Field Advantage: This module features a video, as well as a interesting interactive map that illustrates data about the exact sleep lost experienced by teams that travel from one coast to another and the teams that have to travel the most during seasons. This module uses data to demonstrate that home field advantage does exist, but it also describes all of the factors that may cause home-field advantage (player sleep quality/stadium noise/etc.). This opens up a discussion of multivariate statistics and co-variates.



How to use in your class: Engaging examples of real life questions that can be answered via data collection and analysis.
Labels:

Comments

  1. AnonymousOctober 26, 2017 at 4:14 AM

    Professionally written blogs are rare to find, however I appreciate all the points mentioned here. I also want to include some other writing skills which everyone must aware of.ไฮไลท์บอล

    ReplyDelete

Post a Comment

Popular posts from this blog

Ways to use funny meme scales in your stats classes

Have you ever heard of the theory that there are multiple people worldwide thinking about the same novel thing at the same time? It is the multiple discovery hypothesis of invention . Like, multiple great minds around the world were working on calculus at the same time. Well, I think a bunch of super-duper psychology professors were all thinking about scale memes and pedagogy at the same time. Clearly, this is just as impressive as calculus. Who were some of these great minds? 1) Dr.  Molly Metz maintains a curated list of hilarious "How you doing?" scales.  2) Dr. Esther Lindenström posted about using these scales as student check-ins. 3) I was working on a blog post about using such scales to teach the basics of variables.  So, I decided to create a post about three ways to use these scales in your stats classes:  1) Teaching the basics of variables. 2) Nominal vs. ordinal scales.  3) Daily check-in with your students.  1. Teach your students the basics...
Post a Comment
Read more

Leo DiCaprio Romantic Age Gap Data: UPDATE

Does anyone else teach correlation and regression together at the end of the semester? Here is a treat for you: Updated data on Leonardo DiCaprio, his age, and his romantic partner's age when they started dating. A few years ago, there was a dust-up when a clever Redditor r/TrustLittleBrother realized that DiCaprio had never dated anyone over 25. I blogged about this when it happened. But the old data was from 2022. Inspired by this sleuthing,  I created a wee data set, including up-to-date information on his current relationship with Vittoria Ceretti, so your students can suss out the patterns that exist in this data.
Post a Comment
Read more

If your students get the joke, they get statistics.

Gleaned from multiple sources (FB, Pinterest, Twitter, none of these belong to me, etc.). Remember, if your students can explain why a stats funny is funny, they are demonstrating statistical knowledge. I like to ask students to explain the humor in such examples for extra credit points (see below for an example from my FA14 final exam). Using xkcd.com for bonus points/assessing if students understand that correlation =/= causation What are the numerical thresholds for probability?  How does this refer to alpha? What type of error is being described, Type I or Type II? What measure of central tendency is being described? Dilbert: http://search.dilbert.com/comic/Kill%20Anyone Sampling, CLT http://foulmouthedbaker.com/2013/10/03/graphs-belong-on-cakes/ Because control vs. sample, standard deviations, normal curves. Also,"skewed" pun. If you go to the original website , the story behind this cakes has to do w...
1 comment
Read more