• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.863-874
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• 2017

Wins above replacement (WAR) is the most commonly used statistics of the many sabermetrics that measure baseball players' abilities. The advantage of a WAR is that it enables to compare performances of players even though they have different roles such as pitcher and hitter. However, WAR is difficult to obtain with common records. Thus, in this paper, we have calculated the sabermetrics variable based on Korean professional baseball records for the past three years (2014-2016). Using these variables, we suggest starting pitcher ability index that can replace WAR. Starting pitcher ability index was calculated by means of arithmetic mean, weighted average and principal component regression. Then, compared to the WAR, the most relevant method was selected, which would be useful to identify for the starting pitcher ability.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.409-420
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• 2018

This is a convergence study to investigate the factors affecting the psychological happiness of leisure sports participants(social baseball club) and to present a strategy for effective program development. The subjects of this study were 151 participants of social baseball clubs in J-do area and collected data by self-reported questionnaire. Data were analyzed by descriptive statistics, t-test, ANOVA, correlation analysis and stepwise multiple regression analysis. The results of this study were the explanatory power was 54.1% with psychological happiness, quality of life, self-efficacy. As a result, it was confirmed that strengthening interpersonal relationship ability, positive reinforcement of self-efficacy, and quality of life were important for improvement of psychological happiness. and in the future, it is necessary to study repeatedly to confirm the influence of psychological through objective measurement.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.37-42
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• 1998

In the 11th AQCS(1997), the paper entitled 'Statistical Analysis of Baseball Records - Jinx and National Characteristics -' was presented by the same authors. At that time, the differences between Japanese characteristics and those of Europeans, using baseball data were discussed, mainly from the viewpoint of 'ways of thinking about chance cause and assignable cause.' In this paper, the authors described also on the same subject from the different viewpoint, 'ways of thinking at the design and development stage of new products', From this viewpoint, the difference also be found. It seems that the most significant difference between Japan and Germany exists in the field of aeroplanes design. The German ideas in the field were very unique, therefore the authors classified and named their ideas as: A) 'Quantitative analysis' type idea, and B) 'Chemical synthetic' type idea. The former concept is composed of two ways of thinking: a) All parts essential for just flying must be used, but b) All other parts shall be rejected, as far as possible. The latter concept is that, the all additional parts necessary for the development of the above 'purified' original product should be added respectively, depending on the requests of customers. These ideas are outlined using the actual examples of German aeroplane.

• Journal of Fashion Business
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• v.20 no.3
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• pp.17-29
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• 2016

To develop baseball catcher leg guards, 3-dimensional (3D) methodologies, which are 3D human body data, reverse engineering, modeling, and printing, optimized guard design for representative positions. Optimization was based on analysis of 3D body surface data and subjective evaluation using 3D printing products. Reverse engineering was used for analysis and modeling based on data in three postures: standing, $90^{\circ}$ knee flexion, and $120^{\circ}$ knee flexion. During knee flexion, vertical skin length increased, with the thigh and knee larger in anterior area compared to the horizontal dimension. Moreover, $120^{\circ}$ knee flexion posture had a high radius of curvature in knee movement. Therefore, guard designs were based on increasing rates of skin deformation and numerical values of radius of curvature. Guards were designed with 3-part zoning at the thigh, knee, and shin. Guards 1 and 2 had thigh and knee boundaries allowing vertical skin length deformation because the shape of thigh and knee significantly affects to its performance. Guard 2 was designed with a narrower thigh and wider knee area than guard 1. The guards were manufactured as full-scale products on a 3D printer. Both guards fit better in sitting than standing position, and guard 2 received better evaluations than guard 1. Additional modifications were made and an optimized version (guard 3) was tested. Guard 3 showed the best fit. A design approach based on 3D data effectively determines best fitting leg guards, and 3D printing technology can customize guard design through immediate feedback from a customer.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1095-1106
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• 2016

The quantile regression method proposed by Koenker et al. (1978) focuses on conditional quantiles given by independent variables, and analyzes the relationship between response variable and independent variables at the given quantile. Considering the linear programming used for the estimation of quantile regression coefficients, the model fitting job might be difficult when large data are introduced for analysis. Therefore, dimension reduction (or variable selection) could be a good solution for the quantile regression of large data sets. Regression tree methods are applied to a variable selection for quantile regression in this paper. Real data of Korea Baseball Organization (KBO) players are analyzed following the variable selection approach based on the regression tree. Analysis result shows that a few important variables are selected, which are also meaningful for the given quantiles of salary data of the baseball players.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1238-1245
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• 2012

The main purpose of this study was to identify the current awareness and preference on the promotions of products in Korean professional baseball teams. For this study, the subjects were randomly selected where they have experienced purchasing any products in the Korean professional baseball stadium. Totally, 520 subjects were asked to answer the questionnaire relevant to the current awareness and preference of promotion of products. There were 11 questions for the current awareness and 14 questions for the preference on the promotion of products. The data gathered was determined within a frequency analysis, an independent sample T-test and one-way ANOVA tests. The results were discussed when the p-value were lest than .05. There were a couple of results found throughout this study. Firstly, there were no significant differences of the current awareness between gender. Secondly, there were significant differences of the preference on the promotion between age(p<.05). Especially, there were significant differences on the value of products and price between 20's, 30's and 40's groups. Thirdly, there were significant differences of the preference on the promotion between level of earing per year statistically(p<.05). In addition, there were significant differences on the price of products between 2000-2500 million won, 2500-3000 million won and 4000 million won groups. Consequently, the product promotion by the Korean professional baseball teams has to be more variety and structured.

• Archives of Plastic Surgery
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• v.46 no.3
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• pp.198-203
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• 2019

Background Professional affiliation between medical centers and professional sports teams can be mutually beneficial in the provision of healthcare and marketing strategy. Anecdotal evidence suggests a link between trauma volume and sporting events; however, there is limited data. This study aims to characterize the incidence of operative hand and facial trauma during professional baseball home games. Methods A retrospective review of surgical cases for traumatic hand or facial injuries at a level 1 center between 1999 and 2012 was performed. Demographic information including date of injury, admission status, and operative repair were collected. Patients were grouped based on whether their trauma occurred on the date of a home game. Results Operative hand and facial trauma occurred at a rate of 33.4 injuries per 100 days with home games, compared to 22.2 injuries per 100 days (incidence rate ratios, 1.50; 95% confidence interval, 1.34-1.69). When home games were played, patients were more likely to present as a result of motorcycle accidents (3.1% vs. 1.5%; P=0.04) or bicycle accidents (5.0% vs. 2.6%; P=0.01). Other mechanisms of trauma were not statistically different. There was an increase incidence of injuries during home games in August; weekly variability showed an increased incidence during the weekends. Conclusions There was an increased rate of operative hand and facial injuries on dates with professional home games. The incidence of injuries during home games was higher in the late summer and on the weekends. Further analysis may allow improved resource allocation and strategies for injury prevention and treatment.

• The Journal of Bigdata
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• v.5 no.2
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• pp.77-84
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• 2020

In this study, we conducted a study on the win-loss predicton analysis of korean professional baseball by artificial intelligence models. Based on the model, we predicted the winner as well as each team's final rank in the league. Additionally, we developed a website for viewers' understanding. In each game's first, third, and fifth inning, we analyze to select the best model that performs the highest accuracy and minimizes errors. Based on the result, we generate the rankings. We used the predicted data started from May 5, the season's opening day, to August 30, 2020 to generate the rankings. In the games which Kia Tigers did not play, however, we used actual games' results in the data. KNN and AdaBoost selected the most optimized machine learning model. As a result, we observe a decreasing trend of the predicted results' ranking error as the season progresses. The deep learning model recorded 89% of the model accuracy. It provides the same result of decreasing ranking error trends of the predicted results that we observe in the machine learning model. We estimate that this study's result applies to future KBO predictions as well as other fields. We expect broadcasting enhancements by posting the predicted winning percentage per inning which is generated by AI algorism. We expect this will bring new interest to the KBO fans. Furthermore, the prediction generated at each inning would provide insights to teams so that they can analyze data and come up with successful strategies.

• The Journal of Bigdata
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• v.7 no.1
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• pp.49-61
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• 2022

In sports, the proportion of data analysis in team management such as team strategy planning and marketing is increasing. In KBO(Korea Baseball Organization) league, in particular, plans such as recruiting players and fostering players are established to devise team strategies for the next year, such as FA and trade, at the end of a season. For these reasons, it is very important to predict players' performance for the next year. In this study, the target was limited to only the batter and tried to find out how to predict whether the performance of the next year will improve. As a standard record for rising and falling, OPS(On-Base Plus Slugging), which is easy to calculate and has a high relationship with team score, was used. In this study, 40 years of regular season data from 1982 to 2021 were used as data, and 11 machine learning classification models were used as experimental methods. Predicting the rise and fall of OPS, RBF SVM, Neural Net, Gaussian Process, and AdaBoost were more accurate than other classification models, and age did not significantly affect accuracy.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.225-230
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• 2020

The KBO League is held over a long period of time due to the large number of games. Also, Korea has a diverse and distinct climate. Therefore, this study analyzed the relationship between the daily average temperature and the record of batting power such as home runs, triples, doubles, number of bases, batting percentage, and net batting percentage, and a third baseball record was defined. For this study, the correlation between the daily average temperature data and the batter who entered the standard at-bat in the KBO League in 2019 was analyzed through the SEMMA method. From the results of this study, it was found that the average daily temperature had an effect on a batter's hitting power. In particular, it was found that a batter's hitting power decreased on the day of temperatures recorded between 20.0 degrees and 24.9 degrees, and it was discussed that this may have been related to the physical condition of the pitcher the batter was facing. Therefore, it can be expected that players, coaching staff, and the front desk can use them in the game through conditions outside the game. In addition, it is expected that it will be a more useful analysis model by analyzing the records of pitching, base running, and defense as well as subsequent batting records.