• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.369-383
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• 2018

In this paper, suggests a gamification analysis method applied to screen sports. The analysis method is through the process of comparison, collection and application. In the process of comparison, compare the characteristics of actual sports and screen sports and Data collection to complement the differences derived from the comparison process is done during the collection process. Process of application is verify for application status of Gamification. and analyzed of screen golf and screen baseball. The result shows that screen golf couldn't apply walking exercise in the comparison process, and screen baseball couldn't apply exercise elements except batting. During the collection process, driving distance and swing data were used for screen golf, and driving distance, batting average and RBI (runs batted in) data were used for screen baseball. Lastly, it was revealed during the application process that both screen golf and screen baseball provide data to users by using reward, competition and Self-expression elements of gamification. The analysis methods presented in this study can be a method to analyze screen sports, and are expected to be appropriate methods to make screen sports.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.562-563
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• 2019

본 연구는 한국 프로 야구 선수 개인의 수치화된 데이터를 바탕으로 타석의 결과를 예측하고자 하는데 목적을 두고 있다. 연구의 방법은 2015시즌부터 2018시즌에 활약한 한국 프로 야구 소속의 투수와 타자의 유형을 군집화 하여 지도학습 모델을 만든다. 지도학습 모델과 현재까지 진행된 2019시즌의 결과를 비교·대조한다. 본 연구결과는 한국 프로 야구 10개 구단의 감독의 선수 선발 결정에 기여할 것으로 판단된다.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.615-616
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• 2024

현대 야구에서 타자의 스윙 패턴 분석은 상대 투수가 투구 전략을 수립하는데 상당히 중요하다. 이미지 기반의 인간 포즈 추정(HPE)은 대규모 스윙 패턴 분석을 자동화할 수 있다. 그러나 기존의 HPE 방법은 빠르고 가려진 신체 움직임으로 인해 복잡한 스윙 모션을 정확하게 추정하는 데 어려움이 있다. 이러한 문제를 극복하기 위해 스윙 모션에 대한 사전 정보를 활용하여 야구 선수의 포즈를 보정하는 방법(BPPC)을 제안한다. BPPC는 동작 인식, 오프셋 학습, 3D에서 2D 프로젝션 및 동작 인지 손실 함수를 통해 스윙 모션에 대한 사전 정보를 반영하여 기성 HPE 모델 결과를 보정한다. 실험에 따르면 BPPC는 벤치마크 데이터셋에서 기성 HPE 모델의 2D 키포인트 정확도를 정량적 및 정성적으로 향상시키고, 특히 신뢰도 점수가 낮고 부정확한 키포인트를 크게 보정했다.

• Digital Contents
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• no.5 s.96
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• pp.36-41
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• 2001

데이터웨어하우스(Dataware House)가 자료 창고라고 하면 데이터마이닝(Data mining)은 그 창고에 있는 데이터를 가지고 실제 분석을 하는 것이다. 창고에 있는 데이터 자체는 기업에 부가가치를 줄 수는 없다. 이것을 분석하여 유용한 자료가 나와야지 그것을 가지고 행동에 옮겨 기업은 이익을 얻기 때문이다. 예를 들면 아무리 야구에 대한 지식이 머리 속에 많은 감독이라도 고민을 하여 실제 경기에서 응용할 수 있는 작전이 없다면 그 지식은 의미가 없듯이 데이터가 아무리 훌륭하고 많아도 그것을 분석하는 단계에서 문제가 있다면 아무 소용이 없다는 것이다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.677-687
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• 2016

Among lots of sabermetric statistics for baseball batters' ability, the wins above replacement (WAR) is the most popular statistic in MLB. However, there exists a difficulty applying WAR to KBO, since KBO data do not have position adjustment, league adjustment and park factor which are essential in calculating WAR. In this paper, using five statistics for both KBO and MLB qualified batters, we propose hitting ability index (HAI), an alternative sabermetric indices to represent batters' ability. Comparing HAI with WAR of MLB batters, we evaluate the validity of HAI and then applied HAI to 2015 KBO data in which HAI is analyzed statistically with respect to different teams, ages, and positions. Moreover, the linear relationship between KBO batter's HAI and their annual salary is discussed. Grouping 46 KBO batters based on confidence region of the regression model for annual salary, we also statistically investigate batter's annual salary in these groups with respect to several factors.

• Smart Media Journal
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• v.13 no.4
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• pp.16-22
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• 2024

Pitching is a major part of baseball, so much so that it can be said to be the beginning of baseball. Analysis of accurate pitching motions is very important in terms of performance improvement and injury prevention. When analyzing the correct pitching motion, the currently used motion capture method has several critical environmental drawbacks. In this paper, we propose analysis of pitching motion using the RGB-based Human Pose Estimation (HPE) model to replace motion capture, which has these shortcomings, and use motion capture data and HPE data to verify its reliability. The similarity of the two data was verified by comparing joint coordinates using the Dynamic Time Warping (DTW) algorithm.

• Journal of Korea Entertainment Industry Association
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• v.14 no.6
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• pp.139-150
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• 2020

The data processing of this study focuses on the textom and social media words about three areas: 'Corona 19 and professional baseball', 'Corona 19 and professional baseball', and 'Corona 19 and professional sports' The data was collected and refined in a web environment and then processed in batch, and the Ucinet6 program was used to visualize it. Specifically, the web environment was collected using Naver, Daum, and Google's channels, and was summarized into 30 words through expert meetings among the extracted words and used in the final study. 30 extracted words were visualized through a matrix, and a CONCOR analysis was performed to identify clusters of similarity and commonality of words. As a result of analysis, the clusters related to Corona 19 and Pro Baseball were composed of one central cluster and five peripheral clusters, and it was found that the contents related to the opening of professional baseball according to the corona 19 wave were mainly searched. The cluster related to Corona 19 and unrelated to professional baseball consisted of one central cluster and five peripheral clusters, and it was found that the keyword of the position of professional baseball related to the professional baseball game according to Corona 19 was mainly searched. Corona 19 and the cluster related to professional sports consisted of one central cluster and five peripheral clusters, and it was found that the keywords related to the start of professional sports according to the aftermath of Corona 19 were mainly searched.

• 한국체육학회지인문사회과학편
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• v.55 no.1
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• pp.457-467
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• 2016

Understanding professional baseball fans' expenditure is expected to provide fundamental marketing information that help increase each team's marketing profits and values and produce a better economic impact on its community. In this regard, this study employed a survey method with a total of 372 residents located in Changwon. A questionnaire included factors such as demographics, consumption patterns and perceived socio-psychic effect(PSE), all of which were derived from literature review. A binary logistic regression was modeled with a dichotomous dependent variable, expenditure(30,000 won more or less). The following were input in the model as the independent variables in order to see the relationships; gender, marriage, education, occupation, income, location, age, leisure type, distance, companion, transportation, interest, and PSE. The results of the logistic regression analysis are as follows. Overall, the model was statistically significant, χ²(21, N=372)=59.159, p=.000. Cox and Snell R² was reported as .147 and .200 respectively. So, the model accounted for between 14.7% and 20.0% of the variation in expenditure. Among the independent variables, income, location, companion, and PSE were found to be the significant factors to expenditure. For income, subjects with 2 million won less of income, compared to those with 4 million won more, were .38 times less likely to pay the money of 30,000 won more. For location, subjects in Masan, compared to those in Jinhae, were 3.49 times more likely to pay 30,000 won more. Subjects in Changwon, compared to those in Jinhae, were 3.05 times more likely to pay 30,000 won more. For companion, people visiting the stadium alone, compared to those with friends/colleague, were .36 times less likely to pay 30,000 won more. For PSE, the odds of 30,000 won more paid increased by 1.37 times with one-unit increase in PSE.