• Title/Summary/Keyword: 메이저리그베이스볼

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The Characteristics of Cultural Sustainability in Architectural Design of MLB Ballparks (MLB 구장의 건축 디자인에 나타난 문화적 지속가능성의 특성)

  • Kim, Kwang-Hoe;Lee, Young-Han
    • KIEAE Journal
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    • v.15 no.6
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    • pp.93-100
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    • 2015
  • Purpose: Ballparks of KBO which were built by local governments and operated for baseball game-centered have been required more sustainable development according to going into low growth phase in Korea recently. MLB ballparks with the teams having 100 year old tradition have been sustainable-developed economically, socially, environmentally and culturally. This research is to study the characteristics of cultural sustainability in architectural design of 30 MLB parks. Method: To begin with comparison analysis of usage rate of 10 ballparks of KBO with 30 ballparks of MLB, and architectural designs of facades, fields, accommodations, sculptures, greens, roof gardens, etc. are analyzed in the MLB ballpark. And finally, the characteristics of cultural sustainability in the architectural design are analyzed. Result: MLB ballparks have played role as core-space of urban community, accumulated space of citizens' memory being originated in natural climatic feature of region, historical image of city and tradition of home-ballpark. A basis of these characteristics could is nature of cultural sustainability, that is to say local community, historical restoration, social solidarity.

A Study on the Timing of Starting Pitcher Replacement Using Machine Learning (머신러닝을 활용한 선발 투수 교체시기에 관한 연구)

  • Noh, Seongjin;Noh, Mijin;Han, Mumoungcho;Um, Sunhyun;Kim, Yangsok
    • Smart Media Journal
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    • v.11 no.2
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    • pp.9-17
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    • 2022
  • The purpose of this study is to implement a predictive model to support decision-making to replace a starting pitcher before a crisis situation in a baseball game. To this end, using the Major League Statcast data provided by Baseball Savant, we implement a predictive model that preemptively replaces starting pitchers before a crisis situation. To this end, first, the crisis situation that the starting pitcher faces in the game was derived through data exploration. Second, if the starting pitcher was replaced before the end of the inning, learning was carried out by composing a label with a replacement in the previous inning. As a result of comparing the trained models, the model based on the ensemble method showed the highest predictive performance with an F1-Score of 65%. The practical significance of this study is that the proposed model can contribute to increasing the team's winning probability by replacing the starting pitcher before a crisis situation, and the coach will be able to receive data-based strategic decision-making support during the game.