Football play type prediction and tendency analysis
Name
1016455954-MIT.pdf
Description
Full printable version
Size
536.01 KB
Format
Adobe PDF
Checksum (MD5)
fb63633159284c4e1c3c66e8ec59b1c7
Author(s)
Ota, Karson L
Advisor(s)
Christina Chase.
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
In any competition, it is an advantage to know the actions of the opponent in advance. Knowing the move of the opponent allows for optimization of strategy in response to their move. Likewise, in football, defenses must react to the actions of the offense. Being able to predict what the offense is going to do before the play represents a tremendous advantage to the defense. This project applies machine learning algorithms to situational NFL data in order to more accurately predict play type as opposed to the widely used and overly general method of general statistics. Additionally, this project creates a way to discern tendencies in specific situations to help coaches create game plans and make in game decisions.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 33).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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