loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Michael Hamilton 1 ; Phuong Hoang 2 ; Lori Layne 3 ; Joseph Murray 2 ; David Padget 3 ; Corey Stafford 4 and Hien Tran 2

Affiliations: 1 Rutgers University, United States ; 2 North Carolina State University, United States ; 3 MIT Lincoln Laboratory, United States ; 4 Columbia University, United States

ISBN: 978-989-758-018-5

Keyword(s): Pitch Prediction, Feature Selection, ROC, Hypothesis Testing, Machine Learning.

Related Ontology Subjects/Areas/Topics: Applications ; Classification ; Economics, Business and Forecasting Applications ; Feature Selection and Extraction ; Pattern Recognition ; Theory and Methods

Abstract: Major League Baseball, a professional baseball league in the US and Canada, is one of the most popular sports leagues in North America. Partially because of its popularity and the wide availability of data from games, baseball has become the subject of significant statistical and mathematical analysis. Pitch analysis is especially useful for helping a team better understand the pitch behavior it may face during a game, allowing the team to develop a corresponding batting strategy to combat the predicted pitch behavior. We apply several common machine learning classification methods to PITCH f/x data to classify pitches by type. We then extend the classification task to prediction by utilizing features only known before a pitch is thrown. By performing significant feature analysis and introducing a novel approach for feature selection, moderate improvement over former results is achieved.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.227.240.31

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Hamilton, M.; Hoang, P.; Layne, L.; Murray, J.; Padget, D.; Stafford, C. and Tran, H. (2014). Applying Machine Learning Techniques to Baseball Pitch Prediction.In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 520-527. DOI: 10.5220/0004763905200527

@conference{icpram14,
author={Michael Hamilton. and Phuong Hoang. and Lori Layne. and Joseph Murray. and David Padget. and Corey Stafford. and Hien Tran.},
title={Applying Machine Learning Techniques to Baseball Pitch Prediction},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={520-527},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004763905200527},
isbn={978-989-758-018-5},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Applying Machine Learning Techniques to Baseball Pitch Prediction
SN - 978-989-758-018-5
AU - Hamilton, M.
AU - Hoang, P.
AU - Layne, L.
AU - Murray, J.
AU - Padget, D.
AU - Stafford, C.
AU - Tran, H.
PY - 2014
SP - 520
EP - 527
DO - 10.5220/0004763905200527

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.