Comparative Analysis of Performance by Skill Level and Score Prediction for Screen Golf Users

This study aimed to analyze and compare various performance variables, such as hole-by-hole scores, putts, greens in regulation, and par save rates among screen golf users at different skill levels, to identify their characteristics and predict round scores based on these variables. To achieve this, images of 'screen golf score cards' were collected from an internet portal using the keyword, resulting in a total of 441 records. Performance variables, including putts per hole, greens in regulation, and par save rates, were input into an Excel program for calculation. The analysis revealed differences in performance variables such as hole-by-hole scores, total putts, occurrences of three-putts or more, greens in regulation, and par save rates across different skill levels. Specifically, greens in regulation was found to have the greatest impact on scores. The proportion of putts in scores did not differ between the under and single handicap groups, and differences in par save opportunities were not observed except in the double bogey group. Therefore, it is essential to focus on improving greens in regulation through accurate iron shots and developing the ability to finish with a one-putt even if greens are missed. Future research should consider including variables related to tee shots, such as driver distance and fairway accuracy.

Publication Details

Journal
The Korean Data Analysis Society
Published
2024-10-31
DOI
https://doi.org/10.37727/jkdas.2024.26.5.1553
Primary Topic
Sports Analytics and Performance
Type
article
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article

Comparative Analysis of Performance by Skill Level and Score Prediction for Screen Golf Users

The Korean Data Analysis Society
Sports Analytics and Performance
article

Comparative Analysis of Performance by Skill Level and Score Prediction for Screen Golf Users

article en

Abstract

This study aimed to analyze and compare various performance variables, such as hole-by-hole scores, putts, greens in regulation, and par save rates among screen golf users at different skill levels, to identify their characteristics and predict round scores based on these variables. To achieve this, images of 'screen golf score cards' were collected from an internet portal using the keyword, resulting in a total of 441 records. Performance variables, including putts per hole, greens in regulation, and par save rates, were input into an Excel program for calculation. The analysis revealed differences in performance variables such as hole-by-hole scores, total putts, occurrences of three-putts or more, greens in regulation, and par save rates across different skill levels. Specifically, greens in regulation was found to have the greatest impact on scores. The proportion of putts in scores did not differ between the under and single handicap groups, and differences in par save opportunities were not observed except in the double bogey group. Therefore, it is essential to focus on improving greens in regulation through accurate iron shots and developing the ability to finish with a one-putt even if greens are missed. Future research should consider including variables related to tee shots, such as driver distance and fairway accuracy.

The Korean Data Analysis SocietyVol. 26(5)
Quality Education
Openalex Percentile: Top 77%
Sports Analytics and Performance
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