• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1271-1281
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• 2016

Wins above replacement (WAR) is one of the most widely used statistic among sabermatrics statistics that measure the ability of a batter in baseball. WAR has a great advantage that is to represent the attack power of the player and the base running ability, defensive ability as a single value. In this study, we proposed a hitter ability index using the sabermetrics statistics that can replace WAR based on Korea Baseball Record Data of the last three years (2013-2015). First, we calculated Batter ability index through the arithmetic mean method, the weighted average method, principal component regression and selected the method that had high correlation with WAR.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1191-1199
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• 2010

Knowing what factors into a player's ability to affect the outcome of a sports game is crucial. This knowledge helps determine the relative degree of contribution by each team member as well as sets appropriate annual salaries. This study uses statistical analysis to investigate how much the outcome of a professional baseball game is influenced by the records of individual players. We used the Lotte Giants' data on 252 games played between 2007 and 2008 that included environmental data(home or away games and opponents) as well as pitchers' and batters' data. Using a SAS Enterprise Miner, we performed a logistic regression analysis and decision tree analysis on the data. The results obtained through the two analytic methods are compared and discussed.

• Korean Journal of Applied Biomechanics
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• v.23 no.1
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• pp.25-35
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• 2013

This study examined 24 right-handed amateur baseball players. Twelve who had played baseball for more than 6 years were grouped as skilled players, while 12 who had played for 1-3 years were the unskilled player group. The swing motion was divided into four event phases: stance, backswing, impact, and follow-through. The mean and maximum plantar pressure, center of pressure, and ground reaction force were measured during each event phase. The mean and standard deviations for each variables were calculated and differences were validated with the independent sample t-test. A p-value <0.05 was considered statistically significant. The results were as follows. 1)The ideal stance is a stable, balanced position with more than 65% of weight on the right foot. There was significant difference in mean left plantar pressure, while the maximal plantar pressure and mean right plantar pressure did not differ significant. 2)The effective backswing of a skilled player is comprised a rightward shift in weight to build maximum energy. More than 90% of the weight was on the right foot. There was a significant difference in the mean left plantar pressure, while the maximal plantar pressure and mean right plantar pressure did not differ significantly. 3) For an effective impact, a rapid shift in weight to the left foot is essential, so that a power hit is obtained. Significant difference in the mean and maximum plantar pressures of both feet were observed. 4)Follow-through requires wight balance, more on the right than the left, without leaning leftward. There was no significant difference in the mean or maximum plantar pressure. 5)The center of plantar pressure should move from the center of the foot to the toe. 6)The analyses of the ground reaction force suggest that a good swing involves a gradual shift in weight to the right side and a rapid leftward shift at impact. Good balance, with the center of gravity on the right side at follow-through, is also required.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.285-298
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• 2012

This research deals with a relationship between the performance of Korean professional baseball players and their annual salaries. It is based on the sabermetrics, which measures the performance of baseball batters in a refined way. We collect the records of batters of eight professional baseball clubs during the season 2009 and 2010. Then, we calculate every index of the sabermetrics. Principal component analysis is used for examining the relationship between those indexes of sabermetrics and annual salary for the next year. In general, batters who show higher performance get more salary. The result of this research can be useful in order to reach an agreement on salary between a player and his club partner.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.79-90
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• 2008

This paper introduces how we have designed and implemented an efficient starting line-up system of professional baseball players, using the forward chaining technology which is an expert system technology. The knowledge base adopted holds 286 players and 148 evaluation Items. Each player's competitiveness is measured as a numerical value in points through 2 different phases. The 1st phase point represents the static information of the target player and the 2nd his dynamic information. This paper gets a representative value of the player, which is used as the basis on which an efficient line-up system in views of both game environments and counterparts is constructed.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.134-141
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• 2023

Objectives : The purpose of this study was investigating the differences in temperament, personality, and cognitive function among athletes and non-athletes, as well as differences within athlete groups participating in different-paced sports like baseball and basketball. Methods : A total of 57 professional basketball players, 51 professional baseball players, and 44 non-athletes subjected to temperament and characteristics inventory assessments and computerized neurocognitive function test. One-way analysis of variance (ANOVA) was employed to analyze the average differences in demographic characteristics, temperament, personality traits, and cognitive functions among the three groups, followed by Bonferroni post hoc tests. Comparisons between starters and non-starters within the athlete groups were conducted using the Mann-Whitney U test. Results : In the analysis of temperament, the basketball and baseball player groups exhibited higher reward dependence and persistence compared to the control group. Additionally, in the assessment of personality traits, both basketball and baseball player groups scored higher in self-directedness and cooperativeness compared to the control group, whereas self-transcendence scores were lower. In cognitive ability assessments, baseball and basketball players outperformed the control group in emotional perception tests. Both baseball and basketball players showed lower card movement counts compared to the control group. Conclusions : This study compared the differences in temperament, personality, and cognitive abilities between professional basketball and baseball players and non-athletes. These results provide valuable insights into the temperament, personality, and cognitive abilities of professional athletes, contributing important information for athlete development and coaching goals in the future.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.357-363
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• 2014

OPS is a sabermetric baseball statistic calculated as the sum of a player's on base percentage (OBP) and slugging percentage (SLG). One of the frequently cited problem with OPS is that OPS gives equal weight to its two components, OBP and SLG. In fact, OBP contributes significantly more to scoring runs than SLG does. This paper provides some exploration into the correct weighting of OBP to SLG when adding the two together. By correlating different coefficients of OBP to runs scored per game, the weighted OPS that weighting OBP 56% in two place more than SLG produced the highest correlation. We found that the weight of OBP increases as RPG increases. Also we suggest the linear regression equation of the best OBP coefficient against RPG.

• Archives of Hand and Microsurgery
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• v.23 no.4
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• pp.262-266
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• 2018

Flexor digitorum profundus (FDP) tears in adolescents appear as avulsion tears in the FDP tendon, whereas longitudinal tears are very rare. Moreover, there has been only one reported case of intratendinous fibroma occurring in the flexor tendon of a finger. A longitudinal tear of the flexor profundus tendon associated with an intratendinous fibroma has not been previously reported. We report one case of a longitudinal partial tear accompanied by an intratendinous fibroma at the FDP tendon of the left middle finger after a hyperextension injury caused by the impact of a baseball. Given the rarity of longitudinal flexor tendon tears in adolescents, in such cases, the possibility of an underlying pathology should be considered.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.978-984
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• 2020

In this study, the correlation between sports records and weather data was analyzed using the big data analysis method. To this end, data was collected by API and crawling, data was processed, statistics were performed, and data visualization was performed. The subject of this study was a player who entered the regular at-bat among outfielders in the 2019 KBO League. In addition, meteorological data were analyzed by using the unpleasant index and above 70 and below 70. As a result of the study, in the various hitting indicators, which are the records that pitchers intervene, the higher the unpleasant index, the better the outfielder's record, but pitchers, walks, pitches, pitching success rates, pitches per turn, pitches per game From the records of the back, it was found that the outfielder made the pitcher difficult. It is expected that this study will help the development of the sports data industry and the performance of baseball players, baseball teams, and coaching staff.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.48-56
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• 2022

The importance of data analysis in baseball has been increasing after the success of MLB's Oakland which applied Billy Beane's money ball theory, and the 2020 KBO winner NC Dinos. Various studies using data in baseball has been conducted not only in the United States but also in Korea, In particular, the models using deep learning and machine learning has been suggested. However, in the previous studies using deep learning and machine learning, the focus is only on predicting the win or loss of the game, and there is a limitation in that it is difficult to interpret the results of which factors have an important influence on the game. In this paper, to investigate which factors is important by position, the prediction model for the Golden Glove award which is given for the best player by position is developed. To develop the prediction model, XGBoost which is one of boosting method is used, which also provide the feature importance which can be used to interpret the factors for prediction results. From the analysis, the important factors by position are identified.