Jang Won-chul, 54, a professor of statistics at Seoul National University, was appointed to the Lotte R&D (research and development) advisory board of the Korean baseball team last month. For one year, he will advise Lotte on data collection and utilization. After graduating from Seoul National University’s Department of Computational Statistics (now the Department of Statistics), Prof. Jang did his doctorate in the United States and taught at the University of Georgia and Duke University before joining Seoul National University in 2017. He is a prominent scholar in the field of big data statistics, but suddenly he is advising a professional baseball team.
“Thanks to the integration of statistics into baseball, baseball has become more diverse, and players can seize new opportunities,” said Prof. Jang when we met at Seoul National University on the 12th. Prof. Jang is a well-known baseball “dugout” (mania). “When I was a student, I really enjoyed watching the baseball magazine ‘Weekly Baseball’. There was Guduk Stadium (Lotte’s old stadium) near my high school (Dong-A High School), so I would go to school while listening to the cheers.” “It’s perfect that my hometown team (Lotte) came to visit me,” he said. In 2011, he participated in the “Baek Incheon Project” initiated by KAIST professor Jung Jae-seung. The idea was to bring together academics and the baseball world to analyze the reasons for the disappearance of four-hit hitters after Baek Incheon, the first year of baseball, using big data. The project led to the formation of the Korean Baseball Association in 2013, and Professor Jang served as its second president. He was invited to join the advisory board at the suggestion of Park Hyun-woo, the current Lotte vice president. “Baseball is a game of numbers, so I can’t help but like it (as a statistician),” he said.
In his view, modern baseball is dominated by statistics. In the U.S., a statistical approach called the “sabermetric matrix” has become the main tool in all aspects of player selection, recruitment, evaluation, and playing time. Although not at the same level as the U.S., Korean baseball is also taking root with the introduction of the pitch tracking system Trackman.안전놀이터
Professor Jang explains, “Before, we always put a speedy hitter in the top of the order and a home run hitter in the fourth, but now teams try different batting order combinations. Pitching a lefty against a lefty and a righty against a righty is no longer the right answer,” he said. Referring to Major League Baseball sluggers Justin Turner (Boston Red Sox) and J.D. Martinez (Los Angeles Dodgers), he said, “They have made ‘career jumps’ by focusing on training to increase their launch angles after analyzing data to find out what angle to hit the ball at to make it go far.”
Lotte wants to create personalized evaluation metrics for each player. For example, instead of changing a starting pitcher just because he throws 100 pitches, Lotte wants to apply different criteria for each player through statistical analysis, such as when one pitcher’s spin rate decreases and another’s arm angle drops below a certain number. This can be done by using player-specific data to calculate “expected runs,” he explains. “Communication with the field is as important as data analysis,” he adds. Even if you develop the best analytical techniques and present the data, it’s useless if you can’t communicate and convince them in the language of the field. “You need to be able to intuitively explain to field leaders, without using complicated statistical terms, that ‘this is what you should do in this situation,’ and then leave it up to them to decide if they want to follow that advice,” Zhang said.
He cited two famous baseball movies, Moneyball and Trouble with Curve, as examples. “Moneyball is the movie that epitomizes ‘data baseball,’ and Trouble with Curve is the movie that shows that baseball is not just a numbers game. Finding the right balance between the lessons of both movies is what makes a successful baseball team.”