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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Factor Analysis of the Batting Average
verfasst von : Hiroki Yamato, Yumi Asahi
Erschienen in: Human Interface and the Management of Information. Interaction, Visualization, and Analytics
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Abstract
This study is factor analysis of the batting average in the professional baseball in Japan. We analyze the factor influencing the batting average using the Japanese professional baseball data. There is no established method to ensure a good shot at Japanese baseball. Based on the results, clarify factors that prevent pitchers from hitting hits and factors that batters increase hits. And establish baseball teaching methods based on the clarified factor. Finally, we aim to improve the level of the professional baseball world of Japan.
The data used are the one-ball data in the regular season of Japanese professional baseball in 2015 and 2016. One-ball data is data every time a pitcher throws one ball to a batter. This time, we used only the data of the battle of right-handed pitcher and right-handed batter. The reason for limiting the data is that it is judged that it is easier to extract the characteristics of the factor when narrowing down the conditions.
In this research, factor analysis is performed first, and covariance structure analysis is performed based on extracted factors. Factor analysis extracts pitcher and batters how to approach the ball. In the covariance structure analysis, we analyze how the extracted factor affects variables.
The result of the factor analysis is that the pitcher can extract four factors, the batter can extract two factors. We named the extracted pitcher’s factors “throw down low”, “throw falling balls”, “throw balls to escape outside”, “attack in-course”. We named the extracted batter’s factors “upper swing”, “down swing”. When covariance structure analysis was performed using the result of the factor analysis, three models could be created. The three models can know how each factor influences hits, outs, batting average. From the results of these models, upper swing had a positive influence on hits, and it turned out that it had a bad influence on outs. It also proved to have a positive effect on latent variable batting time consisting of hits and outs. In summary, it turns out that doing an upper swing has a good influence on increasing the batting average.
From the analysis result, it turned out that the upper swing is important for improving the batting average. The future task can be to analyze also combinations other than right-handed pitcher versus right-handed batter who could not be done this time. In addition, we clarify the explanatory variable which has the most influence on improving batting average among latent variable upper swing.