This paper explores how changing various end game statistics effects a given teams probability of winning a game in the National Football League (NFL). Data from the 2000-2016 NFL seasons is split into two subsets, one for teams winning at halftime, another for losing teams. Using this data an empirical model is estimated to study how the determinants of a team’s success differ between the two sets of data. Overall, the factors which determine a team’s outcome are consistent between the two subsets, varying primarily by magnitude of the effect.
| Identifer | oai:union.ndltd.org:CLAREMONT/oai:scholarship.claremont.edu:cmc_theses-2432 |
| Date | 01 January 2016 |
| Creators | Alleva, Zach |
| Publisher | Scholarship @ Claremont |
| Source Sets | Claremont Colleges |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | CMC Senior Theses |
| Rights | © 2016 Joseph Z. Alleva, default |
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