Document Type
Working Paper
Publication Date
1-29-2023
Abstract
In sports, an aging curve depicts the relationship between average performance and age in athletes' careers. This paper investigates the aging curves for offensive players in the Major League Baseball. We study this problem in a missing data context and account for different types of dropouts of baseball players during their careers. In particular, the performance metric associated with the missing seasons is imputed using a multiple imputation model for multilevel data, and the aging curves are constructed based on the imputed datasets. We first perform a simulation study to evaluate the effects of different dropout mechanisms on the estimation of aging curves. Our method is then illustrated with analyses of MLB player data from past seasons. Results suggest an overestimation of the aging curves constructed without imputing the unobserved seasons, whereas a better estimate is achieved with our approach.
Recommended Citation
Nguyen, Quang and Matthews, Gregory J.. Filling in the Gaps: A Multiple Imputation Approach to Estimating Aging Curves in Baseball. , , : , 2023. Retrieved from Loyola eCommons, Mathematics and Statistics: Faculty Publications and Other Works, http://dx.doi.org/10.48550/arXiv.2210.02383
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright Statement
© The Authors, 2023.
Comments
Author Posting © The Authors, 2023. This working paper is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this working paper are included in the working paper's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the working paper's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. https://doi.org/10.48550/arXiv.2210.02383