Evaluation of golfers’ performances in the ladies professional golf association tour based on bootstrapped data envelopment analysis and latent growth curve model

A latent growth curve model and bootstrapped data envelopment analysis were used to examine the performance and changes in professional golfers on the Ladies Professional Golf Association tour. The panel data for both analyses were obtained for the last three seasons (from 2020 to 2022). The dependent variable was the official money list of players, whereas the independent variables consisted of efficiency factors, technical factors (number of birdies, eagles, and hole-in-ones), mental factors (driving and putting accuracies), and career length. Each factor, other than the efficiency factor, was determined by the weighted combination of parenthesized variables using principal component analysis and was measured as two latent variables of the intercept and the slope of the growth pattern for the three seasons. The efficiency factor was measured using data envelopment analysis and its z with the output factors of scoring average and the percentage of rounds in the 60s, and the input factors of driving distance, greens in regulation, number of putts per green hit in regulation, and sand savings. The results confirm the homogeneity in players’ efficiency and prove Penick’s claim that golf performance is dependent on various factors and that golf is psychological.