Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp016d56zw70r| Title: | The Analytic GM: Using Data Mining to Predict NFL Performance |
| Authors: | Lyons, Maxwell |
| Advisors: | Papanicolaou, Andrew |
| Department: | Operations Research and Financial Engineering |
| Class Year: | 2013 |
| Abstract: | NFL General Managers are constantly faced with high-risk, multi-million dollar decisions of selecting football players for their teams that maximize their teams ability to win while minimizing cost. This paper seeks to provide an analytical approach to measure player performance by creating a framework based on expected points and then valuing players, specifically running backs, based on this framework. |
| Extent: | 71 pages |
| URI: | http://arks.princeton.edu/ark:/88435/dsp016d56zw70r |
| Access Restrictions: | Walk-in Access. This thesis can only be viewed on computer terminals at the Mudd Manuscript Library. |
| Type of Material: | Princeton University Senior Theses |
| Language: | en_US |
| Appears in Collections: | Operations Research and Financial Engineering, 2000-2020 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| LYONS Maxwell.thesis.pdf | 1.97 MB | Adobe PDF | Request a copy |
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