Abstract
This study will collect the tournament data related to prize ranking of KLPGA players in 2019, predict the prize ranking from changing specific performance factors, and analyze the economic value of players. Performance factors for analyzing performance are as follows; putting average, green in regulation, buddy average, par save, par break, recovery, driver accuracy, driver distance, tournament participation, championship winning, and Top 10 finish. In order to define the factors to affect tournament winning prize money, multiple regression analysis is applied. Additionally, deterministic frontier approach is applied to compare maximum differences between winning prize and predicted winning prize through multiple regression analysis, for defining efficiency of players. Collected data is analyzed through frequencies and regression procedure which is provided from SPSS, and expected prize ranking of players can be found. Therefore, it is possible for players to analyze strengths and weaknesses from comparing current prize ranking and expected prize ranking by performance factors. Especially, when weak performance factors are reinforced, players can enter the upper class level and become efficient golf players. This study will be the reference for predicting promotion and growth of golf industry, and making sponsors to support many high potential players effectively.
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