A left-handed pitcher for a left-handed hitter? Statistically not correct

Professor Jang, whom we met at Seoul National University on the 12th, emphasized, “Thanks to statistics taking root in baseball, baseball has become more diverse, and players have been able to seize new opportunities.” Professor Jang is a well-known baseball fanatic. He is from Busan and said, “I really enjoyed reading the baseball magazine ‘Weekly Baseball’ during my school days. “There was Gudeok Stadium (Lotte’s old stadium) near my high school (Dong-A High School), so I left school while hearing cheers,” he said. “For my hometown team (Lotte) to come to me, the word ‘Seongdeok (successful nerd)’ is perfect.” In 2011, he participated in the ‘Baek In-cheon Project’ initiated by KAIST Professor Jaeseung Jeong. The purpose was to bring together academia and the baseball world to analyze using big data the reason why .400 hitters disappeared after Baek In-cheon in the first year of professional baseball. This project led to the 'Korea Baseball Society' in 2013, and Professor Jang, a founding member, served as the second president. At this time, he was invited to the advisory committee at the suggestion of Park Hyun-woo, the current vice president of Lotte, with whom he had a relationship. He said, “Baseball is a game of numbers, so (as a statistician) I can’t help but like it.”

He believes that modern baseball is dominated by statistics. In the United States, a statistical approach called 'Saber Matrix' has become the main tool in all aspects of player selection, recruitment, evaluation, and employment. Although it is not at the level of the United States, 'data baseball' is taking root in Korean baseball with the introduction of the pitch tracking system 'Trackman'.

Professor Jang said, “Before, we always put a fast hitter at number 1 and a home run hitter at number 4, but now each team tries various batting order combinations. He pointed out, “Using left-handed pitchers against left-handed batters and right-handed pitchers against right-handed batters can no longer be said to be the right answer.” Referring to the cases of U.S. Major League sluggers Justin Turner (Boston Red Sox) and JD Martinez (LA Dodgers), he said, “After finding out through data analysis at what angle the ball needs to be hit to make the ball travel farther, we focused on training to increase the launch angle.” “These are players who have achieved a career jump,” he said.

He said that Lotte wants to create personalized evaluation indicators for each player. For example, rather than changing it just because a starting pitcher throws 100 balls, different criteria should be applied to each player through statistical analysis, such as when the ball rotation rate decreases for some pitchers and when the arm angle falls below a certain number for other pitchers. . The explanation is that this is possible by calculating ‘expected goals conceded’ using data for each player. However, he added, “Communication with the field is as important as data analysis.” No matter how great an analysis technique you develop and how much data you present, it is of no use if you cannot convey it in field language and convince people. Professor Jang said, “We must be able to intuitively explain to field leaders, ‘In this case, do this,’ without using difficult statistical terms,” and added, “Whether to follow that advice should be left to the judgment of the field.”

He said this while introducing two famous baseball movies, ‘Moneyball’ and ‘Trouble with Curve.’ “Moneyball is a movie that represents ‘data baseball,’ and ‘The Last Curve Ball of My Life’ is a movie that shows that baseball is not a sport played only with numbers. “Finding the right balance between the lessons of the two movies is the way to create a successful baseball team.”

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