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Journal of Quantitative Analysis in Sports

An official journal of the American Statistical Association

Editor-in-Chief: Steve Rigdon, PhD


CiteScore 2017: 0.67

SCImago Journal Rank (SJR) 2017: 0.290
Source Normalized Impact per Paper (SNIP) 2017: 0.853

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1559-0410
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Volume 15, Issue 1

Issues

Volume 1 (2005)

A mathematical optimization framework for expansion draft decision making and analysis

Kyle E. C. Booth / Timothy C. Y. ChanORCID iD: https://orcid.org/0000-0001-6929-8042 / Yusuf Shalaby
Published Online: 2019-02-15 | DOI: https://doi.org/10.1515/jqas-2018-0024

Abstract

In this paper, we present and analyze a mathematical programming approach to expansion draft optimization in the context of the 2017 NHL expansion draft involving the Vegas Golden Knights, noting that this approach can be generalized to future NHL expansions and to those in other sports leagues. In particular, we present a novel mathematical optimization approach, consisting of two models, to optimize expansion draft protection and selection decisions made by the various teams. We use this approach to investigate a number of expansion draft scenarios, including the impact of “collaboration” between existing teams, the trade-off between team performance and salary cap flexibility, as well as opportunities for Vegas to take advantage of side agreements in a “leverage” experiment. Finally, we compare the output of our approach to what actually happened in the expansion draft, noting both similarities and discrepancies between our solutions and the actual outcomes. Overall, we believe our framework serves as a promising foundation for future expansion draft research and decision-making in hockey and in other sports.

Keywords: expansion draft; mathematical programming; national hockey league; operations research; optimization

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About the article

Published Online: 2019-02-15

Published in Print: 2019-02-25


Citation Information: Journal of Quantitative Analysis in Sports, Volume 15, Issue 1, Pages 27–40, ISSN (Online) 1559-0410, ISSN (Print) 2194-6388, DOI: https://doi.org/10.1515/jqas-2018-0024.

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