A Team-Compatibility Decision Support System for the National Football League
Author:
Affiliation:
1. Department of Analytics and Information Systems, College of Business , Ohio University , Athens , OH 45701
2. Department of Industrial and Systems Engineering, Russ College of Engineering and Technology , Ohio University , Athens , OH 45701
Abstract
Publisher
Walter de Gruyter GmbH
Subject
Biomedical Engineering,General Computer Science
Link
https://www.sciendo.com/pdf/10.2478/ijcss-2020-0005
Reference68 articles.
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3. Barron, D., Ball, G., Robins, M., & Sunderland, C. (2018). Artificial Neural Networks and Player Recruitment in Professional Soccer. PLoS ONE, 13(10). doi:https://doi.org/10.1371/journal.pone.020581810.1371/journal.pone.0205818
4. Beyer, K., Fukuda, D., Redd, M., Stout, J., & Hoffman, J. (2016). Player Selection Bias in National Football League Draftees. The Journal of Strength & Conditioning Research, 30(11), 2965-2971.10.1519/JSC.0000000000001426
5. Birnbaum, P. (2019). A Guide To Sabermetric Research. Retrieved February 11, 2019, from https://sabr.org/sabermetrics
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