NAME: NFL Scores by Day.csv

TYPE: Time series

SIZE: 588 records, 9 variables

ARTICLE TITLE: Analysis of Thursday Night NFL Scores

DESCRIPTIVE ABSTRACT:
This dataset contains the score of every regular season NFL game from the 2012 and 2013 seasons, as well as the first five weeks of the 2014 regular season.  

SOURCES: 
Data was collected at www.nfl.com/scores . 

VARIABLE DESCRIPTIONS:
File is CSV, comma separated values.  Fields are:
Record Number	Sequential record number tying the record back to the original data source
Season			Season {2012, 2013, 2014} in which the game was played
Week			Week number within the regular season the game was played
Day			Day of week on which the game was played
Visitor Team		Name of the visitor (away) team 
Visitor Score		Points scored by the visitor team
Home Team		Name of the home team
Home Team Score	Points scored by the home team
Margin			Absolute difference between the two team scores

SPECIAL NOTES:
Not every week of the NFL season has a Thursday night game.  Within one week of the NFL season, the order of days would be {Wed, Thu, Sat, Sun, Mon} 

STORY BEHIND THE DATA:
The dataset was assembled from online sources, in the interest of addressing media attention to “lop sided” Thursday night games during the early part of the 2014 season.

PEDAGOGICAL NOTES:
This data provides an interesting case for the introductory class, or as part of an early semester review in a course that follows the introductory statistics class.  (The latter is the context in which the author developed the case.) t-tests, time series plots, and statistical process control charts all combine to provide an understanding of what is happening with the data.  There is not enough data (at the time of submission) for analysis of what might be causing the apparently uncharacteristic results in the 2014 season, but the analysis does seem to indicate that “something” is indeed happening to alter the behavior of Thursday night NFL scores, in comparison to the behavior seen over the 2012 and 2013 seasons.

SUBMITTED BY:
Tim Vaughan
University of Wisconsin – Eau Claire
College of Business
Eau Claire, WI  54702-4004
vaughats@uwec.edu