Extra Point Under Review: Machine Learning And The NFL Field Goal
DOI:
https://doi.org/10.6017/eurj.v12i2.9448Keywords:
Statistics, Machine Learning, Field Goal, NFL, EconometricsAbstract
The new NFL extra point rule first implemented in the 2015 season requires a kicker to attempt his extra point with the ball snapped from the 15-yard line. This attempt stretches an extra point to the equivalent of a 32-yard field goal attempt, 13 yards longer than under the previous rule. Though a 32-yard attempt is still a chip shot to any professional kicker, many NFL analysts were surprised to see the number of extra points that were missed. Should this really have been a surprise, though? Beginning with a replication of a study by Clark et. al, this study aims to explore the world of NFL kicking from a statistical perspective, applying econometric and machine learning models to display a deeper perspective on what exactly makes some field goal attempts more difficult than others. Ultimately, the goal is to go beyond the previous research on this topic, providing an improved predictive model of field goal success and a better metric for evaluating placekicker ability.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2016 James LeDoux
This work is licensed under a Creative Commons Attribution 4.0 International License.