Measuring Grit in NFL Cornerbacks using Statistical Analysis
Using the pass play tracking data from the 2018 National Football League (NFL) season, I compiled a Grit Score that measured cornerback responses to an adverse result to a play. I calculated this Grit Score using the results of whether a cornerback allowed their opposing receiver to catch the ball t...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/151676 |
| _version_ | 1826218018349252608 |
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| author | Kingston, Cole |
| author2 | Hosoi, Anette |
| author_facet | Hosoi, Anette Kingston, Cole |
| author_sort | Kingston, Cole |
| collection | MIT |
| description | Using the pass play tracking data from the 2018 National Football League (NFL) season, I compiled a Grit Score that measured cornerback responses to an adverse result to a play. I calculated this Grit Score using the results of whether a cornerback allowed their opposing receiver to catch the ball to measure change in performance. When comparing performance, I used the difference in average distance between the cornerback and opposing receiver to compile one score for each player in the NFL. I validated my calculations with Pro Football Focus Coverage Ratings and was able to classify players into 6 different categories based on talent and Grit Score. Overall, I found that most NFL players have high grit, or play consistently through adversity, which explains why they have made it to the highest level of football. NFL coaches and general managers prefer players who have increased performance following a bad event as those players tend to stay in the NFL for longer than those with decreased performance. |
| first_indexed | 2024-09-23T17:12:51Z |
| format | Thesis |
| id | mit-1721.1/151676 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T17:12:51Z |
| publishDate | 2023 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1516762023-08-01T03:01:03Z Measuring Grit in NFL Cornerbacks using Statistical Analysis Kingston, Cole Hosoi, Anette Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Using the pass play tracking data from the 2018 National Football League (NFL) season, I compiled a Grit Score that measured cornerback responses to an adverse result to a play. I calculated this Grit Score using the results of whether a cornerback allowed their opposing receiver to catch the ball to measure change in performance. When comparing performance, I used the difference in average distance between the cornerback and opposing receiver to compile one score for each player in the NFL. I validated my calculations with Pro Football Focus Coverage Ratings and was able to classify players into 6 different categories based on talent and Grit Score. Overall, I found that most NFL players have high grit, or play consistently through adversity, which explains why they have made it to the highest level of football. NFL coaches and general managers prefer players who have increased performance following a bad event as those players tend to stay in the NFL for longer than those with decreased performance. M.Eng. 2023-07-31T19:58:13Z 2023-07-31T19:58:13Z 2023-06 2023-06-06T16:35:37.178Z Thesis https://hdl.handle.net/1721.1/151676 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Kingston, Cole Measuring Grit in NFL Cornerbacks using Statistical Analysis |
| title | Measuring Grit in NFL Cornerbacks using Statistical Analysis |
| title_full | Measuring Grit in NFL Cornerbacks using Statistical Analysis |
| title_fullStr | Measuring Grit in NFL Cornerbacks using Statistical Analysis |
| title_full_unstemmed | Measuring Grit in NFL Cornerbacks using Statistical Analysis |
| title_short | Measuring Grit in NFL Cornerbacks using Statistical Analysis |
| title_sort | measuring grit in nfl cornerbacks using statistical analysis |
| url | https://hdl.handle.net/1721.1/151676 |
| work_keys_str_mv | AT kingstoncole measuringgritinnflcornerbacksusingstatisticalanalysis |