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NHL aging curves using functional principal component analysis

Author

Listed:
  • Cavan Elijah

    (Swish Analytics, Burnaby, Canada)

  • Cao Jiguo

    (Department of Statistics and Actuarial Science, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A1S6, Canada)

  • Swartz Tim B.

    (Department of Statistics and Actuarial Science, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A1S6, Canada)

Abstract

When considering future performance in sport, age is an important feature for prediction models. On average, players tend to improve from their rookie (earliest) season, plateau, and then decline in performance until they retire from the league. In this paper we apply Functional Principal Component Analysis to the careers of players from the National Hockey League in order to construct individual aging curves. The approach is nonparametric in the sense that a parametric structure is not imposed on the aging curves. A main aspect of our work is the consideration of selection bias whereby players who have long careers are not randomly sampled but tend to be exceptional players. Whereas the literature constructs aging curves that represent the average player, we produce aging curves for individual players; this is particularly useful in roster construction.

Suggested Citation

  • Cavan Elijah & Cao Jiguo & Swartz Tim B., 2025. "NHL aging curves using functional principal component analysis," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 21(3), pages 177-189.
    • Handle: RePEc:bpj:jqsprt:v:21:y:2025:i:3:p:177-189:n:1002
    DOI: 10.1515/jqas-2024-0083
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