• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.177-185
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• 2020

Recently, the popularity of professional baseball is increasing day by day, and it has data related to professional baseball on various portal sites. If you want to increase the popularity of professional baseball and produce results through analysis using relevant data, you have the advantage of accessing professional baseball. In this paper, three analyzes were conducted using data related to professional baseball. Therefore, in this paper, the trend related to the number of articles retrieved from a specific site of a professional baseball team was examined, and the correlation between professional baseball scores and the number of spectators was analyzed. Finally, we analyzed the current status of professional baseball batting average and on base percentage in 2016 and 2017.

• Korean Journal of Artificial Intelligence
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• v.7 no.2
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• pp.13-17
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• 2019

Currently, the sports market continues to grow every year, and among them, professional baseball's entry income is larger than the rest of the professional league. In sports, strategies are used differently in different situations, and the analysis is based on data to decide which direction to implement. There is a part that a person misses in an analysis, and there is a possibility of a false analysis by subjective judgment. So, if this data analysis is done through artificial intelligence, the objective analysis is possible, and the strategy can be more rationalized, which helps to win the game. The most popular baseball to be applied to artificial intelligence to analyze athletes' strengths and weaknesses and then efficiently establish strategies to ease the competition. The data applied to the experiment were provided on the KBO official website, and the algorithms for forecasting applied linear regression. The results showed that the accuracy was 87%, and the standard error was ±5. Although the results of the experiment were not enough data, it would be possible to effectively use baseball strategies and predict the results of the game if the amount of data and regular data can be applied in the future.

• Korean Journal of Applied Biomechanics
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• v.30 no.2
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• pp.165-172
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• 2020

Objective: The purpose of this study was to provide quantitative and objective data of throwing movement in baseball catcher through biomechanical analysis. Method: Eight high school baseball catchers (age: 17.3±0.7 yrs, height: 175.3±4.5 cm, weight: 82.5±9.0 kg, Career: 7.4±2.1 yrs) participated and 3-dimentional motion capture system and electromyography (EMG) were used in this study. Results: The maximum center of mass position displacement was observed in forward direction. The linear velocity magnitude of the upper extremity segments were showed as "wrist>elbow>shoulder" which is indicative of kinematic chain. For kinetic EMG data, we also observed the greater muscle activation in the left brachioradial and erector spine muscles muscle that during throwing movement. Conclusion: We expect that biomechanical data from this study will provide important training implications to baseball coaches and trainers in order to effectively train their baseball catchers.

• Korean Journal of Applied Biomechanics
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• v.26 no.2
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• pp.205-211
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• 2016

Purpose: The aim of this study was to analyze biomechanical factors and PMT (premotor time) of body muscles between elite college and amateur baseball players during the baseball batting motion. Method: Kinematic and electromyographic data were obtained for 10 elite college baseball players and 10 amateur baseball players who participated in this study. All motion capture data were collected at 200 Hz using 8 VICON cameras and the PMT of muscles was recorded using a Delsys Trigno wireless system. The peak mean bat speed and the peak mean angular velocities of trunk, pelvis, and bat with PMT of 16 body muscles were computed. These kinematic and PMT data of both groups were compared by independent t-tests (p < .05). Results: The pelvis, trunk, and bat showed a sequence of angular velocity value during baseball batting. The PMTs of right tibialis anterior, left gastrocnemius, external oblique, and erector spinae were significantly different between the two groups. Conclusion: The PMT of body muscles was related to the shifting of body and rotation of the pelvis and the trunk segment, and this action can be considered the coordinated muscle activity of the lower and upper body.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1477-1485
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• 2016

The Pythagorean theorem for baseball based on the number of runs they scored and allowed has been noted that in many baseball leagues a good predictor of a team's end of season won-loss percentage. We study the convergence characteristics of the Pythagorean expectation formula during the baseball game season. The three way ANOVA based on main effects for year, rank, and baseball processing rate is conducted on the basis of using the historical data of Korean professional baseball clubs from season 2005 to 2014. We perform a regression analysis in order to predict the difference in winning percentage between teams. In conclusion, a difference in winning percentage is mainly associated with the ranking of teams and baseball processing rate.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.17-24
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• 2019

In this paper, we propose a new model for predicting effective Win/Loss in professional baseball game in Korea using machine learning technique. we used basic baseball data and Sabermetrics data, which are highly correlated with score to predict and we used the deep learning technique to learn based on supervised learning. The Drop-Out algorithm and the ReLu activation function In the trained neural network, the expected odds was calculated using the predictions of the team's expected scores and expected loss. The team with the higher expected rate of victory was predicted as the winning team. In order to verify the effectiveness of the proposed model, we compared the actual percentage of win, pythagorean expectation, and win percentage of the proposed model.

• IE interfaces
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• v.17 no.4
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• pp.440-449
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• 2004

The OERA(Offensive Earned-Run Average) is a methodology for the performance evaluation of baseball players, which is based on a well- known Markov chain model. The DEA(Data Envelopment Analysis) is an LP-based evaluation technique for performance analysis of DMUs (Decision Making Units), whose production activities are characterized by multiple inputs and outputs. In this paper, the performances of Korean professional baseball players are analytically evaluated using both OERA and DEA methods. We discuss methodological strengths and drawbacks of two kinds of baseball evaluation techniques, by comparing both results. Finally to overcome the shortcomings of both methods, we develop a new analytical approach for baseball evaluation by combining OERA with DEA.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.119-126
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• 2023

In this paper, a new model was presented to objectively evaluate the defense ability of defenders in Korean professional baseball. In the proposed model, using Korean professional baseball game data from 2016 to 2019, a representative defender was selected for each team and defensive position to evaluate defensive ability. In order to evaluate the defense ability, a method of calculating the defense range for each position and dividing the calculated defense area was proposed. The defensive range for each position was calculated using the Convex Hull algorithm based on the point at which the defenders in the same position threw out the ball. The out conversion score and victory contribution score for both infielders and outfielders were calculated as basic scores using the defensive range for each position. In addition, double kill points for infielders and extra base points for outfielders were calculated separately and added together.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.165-172
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• 2014

The purpose of this paper is to identify whether the national baseball squad made up of the best players may get the outstanding results in the international competitions or not. Using Data Envelopment Analysis, the relative efficiency of players in Korean Baseball Organization is estimated as performance measure, and compared with the efficiency scores of national squad members. The paper focuses on the proper choice of DEA model in a baseball setting, thereby selecting the BCC model with non-discretionary variable. Two input variables(plate appearances and stolen bases to enforce) and three output variables(runs, on-base plus slugging and stolen base percentage) are used to evaluate the efficiency of the baseball players. Results showed that 22 players among 97 players were classified as efficient and 8 players among 12 national squad members were as efficient. These findings indicate a potential for DEA to be a major part of the analytical approaches in evaluating the relative efficiency of players.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.455-468
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• 2008

Based on the huge baseball game records, the steal plays an important role to affect the result of games. For the research about success or failure of the steal in baseball games, logistic regression models are developed based on 2007 Korean professional baseball games. The analyses of logistic regression models are compared of those of the discriminant models. It is found that the performance of the logistic regression analysis is more efficient than that of the discriminant analysis. Also, we consider an alternative logistic regression model based on categorical data which are transformed from uneasy obtainable continuous data.