• Title/Summary/Keyword: 미국여자프로골프협회 투어 통계

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Effectiveness of golf skills to average score using records of PGA, LPGA, KPGA, KLPGA : Multi-group path analysis (프로골프 경기기록을 활용한 다중집단분석 : 경로분석 적용)

  • Kim, Sae Hyung;Cho, Jung Hwan
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.3
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    • pp.543-555
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    • 2013
  • This study is to analyze effectiveness of golf skills (driving distance, rating of fairway, green in regulation, sand save ratio, recovery ratio, putting average) to average score using records of PGA, LPGA, KPGA, KLPGA. Independent variables were driving distance, rating of fairway, green in regulation, sand save ratio or recovery ratio, putting average. Dependent variable was the scoring average in this study. To analyze these variables, multi-group (PGA vs LPGA, KPGA vs KLPGA, PGA vs KPGA, LPGA vs KLPGA) path analysis was used through AMOS 18.0 program and significance level was set at 0.05. As the result, the variables that show significant differences of path coefficient between PGA model and LPGA model were driving distance and green in regulation to average score. The variables that show significant differences of path coefficient between KPGA model and KLPGA model were driving distance, recovery ratio, and putting average to average score. The variables that show significant differences of path coefficient between PGA model and KPGA model were driving distance, recovery ratio, and putting average to average score. There was not significant difference of path coefficient between LPGA model and KLPGA model.

An exploration of tour skill factors influential to game results of LPGA players (LPGA 선수들의 시즌성적에 영향을 미치는 경기 기술요인 탐색)

  • Son, Seung Bum;Lee, Chang Jin
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.2
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    • pp.369-377
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    • 2013
  • The purpose of this study was to explore which factors mostly influenced players' tour results employing tour skill factors provided by LPGA. For this study, Top 10 LPGA players' stats during 9 years (2004 2012) were used. As matter of fact, 10 variables were used like average score, top 10 finish, average putt, average birdies, average eagles, driving distance, driving accuracy, greens in regulation, sand saves, putts per GIR. and prize money earning. Stepwise multiple regression was conducted using SPSS win 20.0. Results indicated that the most influential tour skill factor to 9 seasons' results was average score, second influential factor was average putt, and the third factor was driving distance, and then top 10 finish was the fourth. Also on a year on year basis, 2004 was average score, 2005 was GIR., 2006 was average eagles, 2007 was top 10 finish, 2008 was average score, 2009 was average putt, 2010 were average score, GIR. and putt per GIR, 2011 was average birdies and 2012 was putt per GIR.