2026-09-18T20:13:23Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1393452022-01-15T03:32:30Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Hosoi, Anette
Lyons, Kevin Andrew
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-01-14T15:05:25Z
2022-01-14T15:05:25Z
2021-06
2021-06-17T20:13:40.683Z
https://hdl.handle.net/1721.1/139345
The ability to measure key physical parameters of athletes is becoming increasingly critical for today’s sports organizations. Force-velocity profiling is a well-understood and studied technique for measuring the relationship between speed and output force in sport-specific contexts. Accurate force-velocity profiling systems can enable a wide variety of applications for sports organizations to improve player performance, cater better training programs, and potentially reduce injury rates in the long term. A current limitation of many of these systems is that they can require context-specific testing that impacts workflows for players, coaches, and trainers. Given the recent rise of wearable sensor technologies that track player movement in dynamic contexts, there is a clear opportunity to leverage new data streams to enhance this process.
We present a novel system for automated force-velocity profiling using publicly available high-frequency tracking data of NFL players. We demonstrate that our derived force-velocity envelopes match observed position and player performance, and provide a proof of concept framework that would allow teams to leverage automated force-velocity profiling in their internal operations.
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
Automated Force-Velocity Profiling of NFL Athletes via High-Frequency Tracking Data
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
unknown
unknown
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<Abstract>The ability to measure key physical parameters of athletes is becoming increasingly critical for today’s sports organizations. Force-velocity profiling is a well-understood and studied technique for measuring the relationship between speed and output force in sport-specific contexts. Accurate force-velocity profiling systems can enable a wide variety of applications for sports organizations to improve player performance, cater better training programs, and potentially reduce injury rates in the long term. A current limitation of many of these systems is that they can require context-specific testing that impacts workflows for players, coaches, and trainers. Given the recent rise of wearable sensor technologies that track player movement in dynamic contexts, there is a clear opportunity to leverage new data streams to enhance this process.
We present a novel system for automated force-velocity profiling using publicly available high-frequency tracking data of NFL players. We demonstrate that our derived force-velocity envelopes match observed position and player performance, and provide a proof of concept framework that would allow teams to leverage automated force-velocity profiling in their internal operations.</Abstract>
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