The importance of advanced analytics and managerial foresight is rapidly growing across professional sports. This project developed insights into player performance in the National Football League (NFL) using advanced player metrics, draft data, and general manager experience from 1970-2023. Using multiple mathematical techniques, including multiple linear regression, fixed effects modeling, and random effects modeling, this study identified critical factors in an NFL general manager’s success. The analysis suggests that NFL general managers with more experience in the role are associated with drafting higher-performing players, while those with more executive experience outside of the general manager position are associated with drafting lower-performing players. These findings provide valuable insights for NFL franchises to make informed decisions when employing general managers.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Bettencourt, Evan

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042524-102651
• 121655

Keyword

• Multiple linear regression
• Sports analytics
• Data analysis
• Fixed effects regression
• Mixed effects regression

Advisor

• Paffenroth, Randy Clinton
• Ching, Kenny

Year

• 2024

Date created

• 2024-04-25

Resource type

• Major Qualifying Project

Major

• Mathematical Sciences

Source

• E-project-042524-102651

Rights statement

• In Copyright