• Journal of Industrial Convergence
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• v.18 no.1
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• pp.65-71
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• 2020

Recently, the field of using data has begun to attract attention in professional sports. In the field of data utilization, in addition to the classic records obtained within the economy, secondary records that emphasize efficiency are also actively used. Therefore, in this study, we try to study the correlation with the pitcher's strikeout ability through the daily average humidity, which is data outside the competition. For this reason, referring to the daily average record of the area of the home base of 10 teams belonging to the KBO league and the auxiliary stadium, the top 5 in the win, hold, save section to grasp the characteristics of the starting pitcher and the rescue pitcher We analyzed K / 9 records for each person. Through the results of this study, we found a significant difference in the K / 9 record between the starting pitcher and the rescue pitcher, and we can expect to investigate the use of professional sports data and develop the industry in general.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.179-183
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• 2020

Seligman argues that an optimistic athlete wins based on a study of US professional baseball and professional basketball players.(trans. Choi, 2008). So, the purpose of this study was to investigate whether optimism can predict the performance of badminton youth representatives. 60 high school students were divided into two groups according to their performance. We used the revised Life Orientation Test (LOT-R) developed by Scheier, Carver and Bridges(1994) and translated into Korean version by Shin Hyun-sook(2005). For this study, the data were analyzed by frequency analysis, reliability analysis, and independent t - test. As a result, there was a statistically significant higher level of optimism in the excellent group than in the non-excellent group. So, in order to improve sports performance, we need psychological skills training that can improve optimism as well as physical training and skills training.

• Journal of the Korean Society of Costume
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• v.66 no.4
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• pp.18-31
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• 2016

This study examined the consumption of licensed sports fashion products by sports fans in order to provide useful information to apparel companies that are interested in sports sponsorship marketing. Grounded theory approach was adopted to explore consumers' attitude toward the sponsoring companies, and motives of buying licensed fashion products. In-depth interviews were conducted with female fans of professional baseball clubs. The main phenomena of interest was consumer purchase of licensed fashion product, with the emphasis on cultural consumption as a causal condition. Providing support for victory, vicarious consumption, social identification, and needs to differentiate were identified as strategies related to licensed product purchase. Economic situations and limitations to purchase are identified as the mediating conditions. The study identified the effects of the consumption on the fan as well as the sponsoring companies as consequences of the phenomena. Sports marketing strategies were suggested for apparel companies based on the analysis of the consumption rituals for licensed fashion goods.

• Journal of Industrial Convergence
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• v.19 no.4
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• pp.17-21
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• 2021

Recently, in the field of sports, the use of data in conducting games, planning seasons, and operating teams has increased significantly. Also, in order to develop better players, it has become necessary to use data to accurately analyze their performance. Therefore, in this study, various data about rookie players was collected and pre-processed in order to analyze and visualize their performance. Additionally, an analysis was conducted to determine at least how many opportunities should be given to foster rookie players. Then, a data analysis method was presented for nurturing athletes by using data in the field of sports. It is expected that this study will contribute to fostering rookie players by utilizing data.

• Journal of Information Technology Applications and Management
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• v.21 no.1
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• pp.17-34
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• 2014

As the numbers of Internet users have grown dramatically in recent years due to increased use of mobile devices, businesses using internet are also expanding rapidly. Internet marketing has the advantage of expanding business without any constraint of time and space using the global network which connects tens of thousands of world's computers and mobile devices. In a way of utilizing internet marketing, the present study examines the applicability of Customer Relationship Management (CRM) to the domestic professional baseball industry in Korea. The study focuses on the issue of whether the intangible value of customer satisfaction can create higher profits. We combine both inductive and conductive methods for this study. First, we carry out a random survey of baseball spectators and find that customers are willing to pay more when their satisfaction level is improved. Next, we recognize satisfaction factors that are considered as important by customers through literature survey. Then we use Decision Tree to find which satisfaction factors are most important to each clustered customer group. Finally we estimate how much they would pay more when the most important satisfaction factor improves by each customer group. Therefore, this study demonstrates that CRM implementation to one-to-one internet marketing can improve the profitability of baseball industry. The major contribution of the present study is to show that the introduction of CRM can be used as a profit-generating strategy in various industries for future internet marketing.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.209-217
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• 2016

Recently, the outdoor activities were increased in accordance with economic growth and improved quality of life. In addition, weather and outdoor activities are closely related. Currently, Outdoor Activities decisions are determined by the Korea Meteorological Administrator's forecasts and subjective experience. Therefore, we need the analysis method that can provide a basis for the decision on outdoor activities based on meteorological information. In this paper, we propose an algorithm that can analyze meteorological information to support decision-making outdoor activities. And the algorithm is based on the data mining. In addition, we have constructed a baseball game schedule with automatic weather system's observation data in the training data. We verified the improved performance of the proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.224-229
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• 2019

This study was undertaken to provide correct posture guidance and reference material for sports injury and injury prevention programs, by analyzing body alignment and plantar pressure distribution in high school baseball players. Totally, 32 subjects were enrolled for the study. Body alignment was measured from the trunk imbalance, kyphotic angle, lordotic angle, pelvic tilt, and pelvic torsion. Foot pressure was measured from the left maximum pressure, right maximum pressure, left weight, and right weight. The mean and standard deviation of the measured factors were calculated and tabulated, and the correlation between body alignment and foot pressure distribution was analyzed using Pearson's correlation analysis. All statistical significance levels were set at 0.05. Body alignment and foot pressure distribution show a positive correlation between the lordotic angle of lumbar spine and the left maximum pressure. There was no correlation between trunk imbalance, kyphotic angle, lordotic angle, pelvic tilt, pelvic torsion, and the left·right weight distribution and the left·right maximum pressure of each foot. Results of this study determined that the increase of the lordotic angle of lumbar spine results in more force on one side of the foot, thereby increasing the maximum pressure. We believe our data could be a reference for exercise programs on physical alignment and plantar pressure distribution of athletes.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.50.3-50.3
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• 2018

2018년부터 한국천문학회 특별 사업단으로 교육, 홍보위원회에 해외교육지원단이 만들어졌다. 해외교육지원단은 지난 2년 동안 한국천문학회가 지원해오던 캄보디아 천문교육지원 활동을 확장하고 체계적인 운영을 목표로 만들어졌다. 먼저, 그동안의 활동에 대해 보고하고 좀 더 내실 있는 계획을 세우기 위해 천문학회 회원들의 의견과 조언을 듣고자 한다. 첫 번째 캄보디아 천문학 교육은 2016년 6월 13-24일(2주) 동안 수도 프롬펜에서 북서쪽, 차편으로 4시간 거리에 있는 뿌삿시 끄로압에서 이루어졌다. 초. 중등학생 50여명이 참여하여 망원경 조작 방법을 배우고, 종이 망원경과 카메라 만들기, 태양과 행성 관측, 축구공, 야구공, 풍선과 찰흙을 이용한 태양계 행성들 크기 비교, 별자리판 만들기와 천문학 여러 현상들에 대한 비디오 영상 보기와 같은 다양한 프로그램을 수행하였다. 두 번째 교육은 국립청소년우주센터와 캄보디아의 Xavier Jesuit School이 연계하여 2017년 4월 3-7일(5일) 동안 지역 중등과학교사 18명을 대상으로 천문교육을 진행하였다. 시간과 좌표, 간이 망원경 제작, 결상의 원리, 분광, 망원경의 조립과 분해 및 천체관측 등 천체관측과 관련된 내용을 위주로 교육을 진행하였다.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.255-262
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• 2013

Data envelopment analysis(DEA) is a linear programming procedure designed to evaluate the relative efficiency of a set of peer entities called decision making units which use the same inputs to produce the same outputs. It has been widely employed in a variety of disciplines as an efficiency or performance measurement tool for comparing a set of entities such as firms, banks, hospitals, nations and organizations. The method, however, cant's make the priority of their performance when many units have efficiency score of unity or 100 percent. In this paper, we propose a new approach which combine qualitative method(graphical approach using network analysis) and quantitative method(super-efficient analysis using DEA), and present the results of an empirical analysis using the data of the Korean professional baseball players. As a result, there were 12 DMU that priority is hardly realized through DEA. However, this problem could be solved with super-efficiency analyzing. Also, more in-depth interpretation was able through integrating results of dendrogram and super-efficiency analyzing and prospecting it in qualitative, quantitative ways.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.8-17
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• 2014

In this research, we employed various data mining techniques to build predictive models for win-loss prediction in Korean professional baseball games. The historical data containing information about players and teams was obtained from the official materials that are provided by the KBO website. Using the collected raw data, we additionally prepared two more types of dataset, which are in ratio and binary format respectively. Dividing away-team's records by the records of the corresponding home-team generated the ratio dataset, while the binary dataset was obtained by comparing the record values. We applied seven classification techniques to three (raw, ratio, and binary) datasets. The employed data mining techniques are decision tree, random forest, logistic regression, neural network, support vector machine, linear discriminant analysis, and quadratic discriminant analysis. Among 21(= 3 datasets${\times}$7 techniques) prediction scenarios, the most accurate model was obtained from the random forest technique based on the binary dataset, which prediction accuracy was 84.14%. It was also observed that using the ratio and the binary dataset helped to build better prediction models than using the raw data. From the capability of variable selection in decision tree, random forest, and stepwise logistic regression, we found that annual salary, earned run, strikeout, pitcher's winning percentage, and four balls are important winning factors of a game. This research is distinct from existing studies in that we used three different types of data and various data mining techniques for win-loss prediction in Korean professional baseball games.