Full metadata
Title
Player Optimization in the National Football League: Creating a Winning Franchise
Description
The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team be as successful as possible by defining which positions are most important to a team's success. Data from fifteen years of NFL games was collected and information on every player in the league was analyzed. First there needed to be a benchmark which describes a team as being average and then every player in the NFL must be compared to that average. Based on properties of linear regression using ordinary least squares this project aims to define such a model that shows each position's importance. Finally, once such a model had been established then the focus turned to the NFL draft in which the goal was to find a strategy of where each position needs to be drafted so that it is most likely to give the best payoff based on the results of the regression in part one.
Date Created
2015-05
Contributors
- Balzer, Kevin Ryan (Author)
- Goegan, Brian (Thesis director)
- Dassanayake, Maduranga (Committee member)
- Barrett, The Honors College (Contributor)
- Economics Program in CLAS (Contributor)
- School of Mathematical and Statistical Sciences (Contributor)
Topical Subject
Resource Type
Extent
37 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2014-2015
Handle
https://hdl.handle.net/2286/R.I.28688
Level of coding
minimal
Cataloging Standards
System Created
- 2017-10-30 02:50:57
System Modified
- 2021-08-11 04:09:57
- 3 years 3 months ago
Additional Formats