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Journal of Quantitative Analysis in Sports

An official journal of the American Statistical Association

Editor-in-Chief: Glickman, PhD, Mark

4 Issues per year


SCImago Journal Rank (SJR): 0.257
Source Normalized Impact per Paper (SNIP): 0.379

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Estimating the effects of age on NHL player performance

1 / Edward J. Egan2 / Louisa Yeung1

1Sauder School of Business, University of British Columbia, 2053 Main Mall, Vancouver, BC, V6T 1Z2 Canada

2National Bureau of Economic Research (NBER), 1050 Massachusetts Avenue, Cambridge, MA 02138, USA

Corresponding author: James A. Brander, Sauder School of Business, University of British Columbia, 2053 Main Mall, Vancouver, BC, Canada V6T 1Z2, e-mail:

Citation Information: Journal of Quantitative Analysis in Sports. Volume 10, Issue 2, Pages 241–259, ISSN (Online) 1559-0410, ISSN (Print) 2194-6388, DOI: 10.1515/jqas-2013-0085, March 2014

Publication History

Published Online:
2014-03-18

Abstract

Using NHL data for the 1997–1998 through 2011–2012 seasons, we examine the effect of age on scoring performance and plus-minus for NHL skaters (non-goalies) and on save percentage for goaltenders. We emphasize fixed-effects regression methods that estimate a representative age-performance trajectory. We also use a method based on the best performances over time, a method based on the age distribution of NHL players, and a “naïve” specification that does not correct for selection bias. In addition we estimate individual age-performance relationships to obtain a distribution of peak ages. All methods provide similar results (with small but understandable differences) except the naïve specification, which yields implausible results, indicating that correcting for selection bias is very important. Our best estimate of the scoring peak age is between 27 and 28 for forwards and between 28 and 29 for defencemen. Both forwards and defencemen exhibit near-peak performance over a wide range, going from about 24 to 32 and 24 to 34, respectively. Goaltenders display little systematic performance variation over most of the age range from the early 20s to late 30s.

Keywords: age and performance; fixed-effects regression; hockey; NHL; selection bias

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