Generating novel tennis racket shape concepts using a theoretical morphospace

Statistical shape analysis, or morphometrics, is a technique commonly used in evolutionary biology to summarise a population of samples. Theoretical morphometrics extends the current population of samples into a theoretical space. Using the lawn tennis racket as an example, this paper showcases the potential of morphometrics as a tool for inspiring design concepts for novel sporting goods. It showcases how morphometrics can be applied to summarise the shape of a sample of rackets and applies theoretical morphometrics to systematically present new candidate designs that fall outside of the inputted existing, racket population. The input population was 514 tennis rackets dating back to the origins of the game. The shape analysis was performed on “front-on” silhouette images of the rackets using the R Package Momocs. The outline shape of each racket was reconstructed using the elliptical Fourier transform curve fitting technique. A principal component analysis performed on the reconstructed outlines showed that >90% of the variance in the shape of the rackets was captured by the first two principal components. An evenly spaced grid of theoretical racket shape outlines was then created in a principal component 2 vs. principal component 1 “morphospace”. The limits of this space were then expanded to give a theoretical morphospace that extended beyond the range of the first two principal components for the 514 samples. We propose that the shapes located within such a theoretical morphospace could inspire designers and help them to systematically identify candidates for novel products. Specifically, we suggest that experimenting with wide-angled throats and heads with angled sides might be an interesting starting point for exploring future tennis racket design concepts. The novel technique presented here could be used by a sporting goods brand during the ideation phase of product development to schematically summarise current designs and identify candidates for new ones.