| dc.contributor.advisor | Hosoi, Anette (Peko) | |
| dc.contributor.author | Wright, Mark Joseph | |
| dc.date.accessioned | 2022-08-29T15:52:06Z | |
| dc.date.available | 2022-08-29T15:52:06Z | |
| dc.date.issued | 2022-05 | |
| dc.date.submitted | 2022-05-27T16:19:52.403Z | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/144505 | |
| dc.description.abstract | Force-velocity profiles are a well-established approach to generating key parameters of an athlete’s overall fitness profile. They are currently utilized by NFL teams for their players. However, athletes run the risk of injury while testing to create these profiles since they must sprint with a weight attached to them at max speed. As such, teams are not utilizing these profiles as well as they could as they prefer not to jeopardize their athletes.
In this paper, we present a novel approach to generating force-velocity profiling inspired by former work in the MIT Sports Lab to create these profiles directly from tracking data generated by wearable technology sensors. The techniques presented in this paper allow NFL teams to create force-velocity profiles over any time frame of tracking data they have available and allow them to better assess, train, and rehabilitate their players. | |
| dc.publisher | Massachusetts Institute of Technology | |
| dc.rights | In Copyright - Educational Use Permitted | |
| dc.rights | Copyright MIT | |
| dc.rights.uri | http://rightsstatements.org/page/InC-EDU/1.0/ | |
| dc.title | Automated Force-Velocity Profiling of National Football League Athletes | |
| dc.type | Thesis | |
| dc.description.degree | M.Eng. | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| mit.thesis.degree | Master | |
| thesis.degree.name | Master of Engineering in Electrical Engineering and Computer Science | |
