Correlation of single-round strokes & performance indicators: Paris Olympic elite female golfers.

Abstract

Despite golf's Olympic reinstatement, quantitative research on elite female Olympic golfers remains scarce, with most studies focusing on tour or amateur players. This study aimed to quantify relationships between single-round strokes and 13 performance indicators among top 10 2024 Paris Olympic female golfers (including ties), identify key predictors, and build a predictive model using correlation analysis, principal component analysis (PCA) and LASSO regression with leave-one-out cross-validation (LOOCV) and bootstrap validation to address overfitting concerns inherent to small-sample analyses. Results showed single-round strokes correlated negatively with GIR (r = -0.484), SG: Putting (r = -0.567) (both p < 0.01) and positively with Putt-Total (r = 0.582, p < 0.01). PCA extracted five principal components explaining 77.94% of total variance, representing distinct performance constructs. LASSO regression identified seven stable predictors (bootstrap selection frequency ≥ 90%): Greens in Regulation (100%), Putt-Total (99%), SG: Approach the Green (98%), SG: Around the Green (97%), SG: Putting (94%), SG: Off the Tee (92%), and Scrambling (88%). Model performance yielded an adjusted R² of 0.928 with cross-validated MSE of 0.528 based on 48 rounds from 12 golfers, though external validation is warranted. This study fills Olympic golf research gaps, providing evidence for targeted training and tournament strategy optimization.