Football play type prediction and tendency analysis

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Ota, Karson L

Advisor dc:contributor.advisor

• Christina Chase.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/113120

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/113120