• The Korean Journal of Applied Statistics
• /
• v.27 no.5
• /
• pp.731-741
• /
• 2014

We suggested an adjusted OPS and weighted adjusted OPS as indices to explain run productivity of teams using the slugging average and adjusted OBP from Korean professional baseball. First, we defined adjusted OBP by modifying currently used OBP. Next, we defined adjusted OPS as the sum of adjusted OBP and slugging average. We also defined weighted adjusted OPS as the weighted average of adjusted OBP and slugging average. Analysis of the data from all games in the regular seasons from 1982~2013 shows that adjusted OPS better explains runs than OPS. For 25 seasons out of 32 seasons, adjusted OPS explains runs better than OPS. Further, weighted adjusted OPS consisting of adjusted OBP (with weight 60%) and slugging average (with weight 40%) gives the best explanation of run productivity. Weighted adjusted OPS has been found to explain run productivity better than weighted OPS proposed in Kim (2012).

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

• The Journal of Bigdata
• /
• v.7 no.1
• /
• pp.49-61
• /
• 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 the Korean Data and Information Science Society
• /
• v.26 no.1
• /
• pp.197-207
• /
• 2015

In baseball game, the hitting ability of batter is frequently assessed by a batting average, a run batted in, a home run, a run scored, an on-base percentage, etc. Recently, more comprehensive indicators such as OPS, ISO, SECA, TA, RC and XR are often used. But, these measures generally shows large deviations since they are calculated from the data for a certain period of time, and they are not an estimate of a population parameter, either. In this paper, we will presume the pure hitting ability of the korea professional baseball players as a parameter which is depend upon at bat. We will estimate the parameter by using the Bayesian method.

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

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.1
• /
• pp.1-10
• /
• 2015

This paper offers some long term perspective on what has been happening to some baseball statistics for Korean professional baseball. The data used are league summaries by year over the period 1982-2013. For the baseball statistics, statistically significant positive correlations (p < 0.01) were found for doubles (2B), runs batted in (RBI), bases on balls (BB), strike outs (SO), grounded into double play (GIDP), hit by pitch (HBP), on base percentage (OBP), OPS, earned run average (ERA), wild pitches (WP) and walks plus hits divided by innings pitched (WHIP) increased with year. There was a statistically significant decreasing trend in the correlations for triples (3B), caught stealing (CS), errors (E), completed games (CG), shutouts (SHO) and balks (BK) with year (trend p < 0.01). The ARIMA model of Box-Jenkins is applied to find a model to forecast future baseball measures. Univariate time series results suggest that simple lag-1 models fit some baseball measures quite well. In conclusion, the single most important change in Korean professional baseball is the overall incidence of completed games (CG) downward. Also the decrease of strike outs (SO) is very remarkable.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.6
• /
• pp.1065-1074
• /
• 2012

The purpose of this paper is to statistically analyze the effects of on-base and slugging ability on the run productivity in Korean professional baseball. In Section 2, we have investigated the OPS (On-base percentage Plus Slugging average) and introduced new indices of batting ability by modifying the OPS. In Section 3, we have examined the correlation which the batting average, on-base percentage, slugging average, IsoP (Isolated Power), OPS and the indices introduced in Section 2 have with the average runs per game, using the data from all the games of the regular seasons in 2007~2011. In addition, by generalizing the OPS and the indices introduced in Section 2, we have analyzed the correlation of the indices with various weights between the average runs per game. As a result, the weighted OPS consisting of on-base percentage (with weight 57%) and slugging average (with weight 43%) has been found to give the best explanation of the run productivity.

• The Journal of the Korea Contents Association
• /
• v.18 no.10
• /
• pp.78-98
• /
• 2018

On the 855 pure Korean commercial fictional movies, excluding diversity films, released in Korea from 2004 to August 2017, I conducted deciles distribution analysis of box office performance of those movies and average box office performance of directors, producers and lead actors who involved in making them. Deciles distribution analysis of average box office performance might be helpful to predict their next box office performance of newly produced Korean movies and to evaluate their contribution to box office performance. In baseball, the various index such as winning rate, on-base percentage, slugging percentage, stolen base percentage, battling average, earned run average is used for predicting and reviewing of professional players. In this study, I evaluate the script's narrative quality by the indirect method of insight and judgment of creative manpower involved in making the movies. For the more productive prediction, direct statistical analysis method on the narrative of the script needs to develop. Time series analysis is required to evaluate the rise and fall of creative manpower and network analysis is also necessary to see the interaction among creative people.