Predictive Analytics for Fantasy Football: Predicting Player Performance Across the NFL

Author

Jack W. Porter, University of New Hampshire, DurhamFollow

Date of Award

Spring 2018

Project Type

Senior Honors Thesis

College or School

PAUL

Department

Decision Sciences; Accounting and Finance

Program or Major

Business Administration

Degree Name

Bachelor of Science

First Advisor

Ali Hojjat

Abstract

The goal of this research is to develop a quantitative method of ranking and listing players in terms of performance. These rankings can then be used to evaluate players prior to and during a fantasy football draft. To produce these rankings, we develop a methodology for forecasting the performance of each individual player (on different metrics) for the upcoming season (16 games) and use these forecasts to estimate player fantasy football scores for the 2018 season.

More specifically, this work answers the following:

1. In what order should players be drafted in a 2018 fantasy football draft and why?
2. Which players can be expected to perform the best at their given position (Quarterback, Running back, Wide Receiver, Kicker, Team Defense) in 2018, and which players should we expect to perform poorly?

Recommended Citation

Porter, Jack W., "Predictive Analytics for Fantasy Football: Predicting Player Performance Across the NFL" (2018). Honors Theses and Capstones. 406.
https://scholars.unh.edu/honors/406