Abstract

In kinesiology and exercise science, researchers want to identify factors associated with players’ performance. In racquet sports, matches are played in a tournament format, and researchers often find observational data for their studies rather than collecting experimental data. Even when an experiment is conducted, which is very rare in literature, a randomized design has been considered to produce unbiased results. Given a small number of participants and limited time, in theory, an optimal experimental design can produce more statistical information about parameters of interest than a completely randomized design. This article includes simulations and a real application of an optimal experimental design to racquet sports research. In our research plan, there were some logistical considerations (e.g., no replicated matches, computation time), and simulations demonstrated that the c- and D-optimal designs result in higher statistical power for single- and multiple-parameter hypothesis testing, respectively, than the completely randomized design. For our research, the D-optimal design was applied to a doubles pickleball tournament with 16 subjects and one half of a day. Participants’ fitness and skill levels were measured in the morning, the doubles tournament was designed in real time on site using a pre-written algorithm, and the tournament design was executed on the same day. To make this computation accessible, an interactive applet is provided in the Appendix of this article with instructions.

This work is licensed under a Creative Commons Attribution 4.0 License.