Each ballpark has a different size in baseball. It could be easily imagined that there would be many home runs in a small ballpark. Moreover, the environment of the ballpark, such as altitude, humidity, air pressure, and wind strength, affects the trajectory of batted balls. Park Factors (PF) are introduced in baseball to quantify the effect of each ballpark on the results (e.g., home runs). In this paper, I assume that each plate appearance can be modeled as a match-up between a batter's team and a pitcher's team plus a ballpark. The effects of each ballpark will be distilled by using a logistic regression method. Numerical verification shows that the proposed method performs better than conventional PF. The verification is based on the results of more than 1.5 million plate appearances from the 2010 to 2017 Major League Baseball (MLB) seasons.
翻译:每个球场在棒球场上都有不同的大小。 可以很容易地想象到在小球场上有许多全垒打。 此外,球场的环境,如高度、湿度、气压和风力,会影响球体的轨迹。球场因素(PF)被引入棒球中,以量化每个球场对比赛结果的影响(例如,全垒打)。在本文中,我假设每个板块的外观可以模拟成打球队和投球队之间的匹配。每个球场的效果将通过使用逻辑回归法来提炼。数字核查表明,拟议的方法比常规PF效果更好。核查基于2010至2017年主要棒球联盟棒球赛季超过150万张牌面的结果。