使用两两比较法改进公园因子估计
Park factor estimation improvement using pairwise comparison method
摘要：
每个棒球场都有不同的大小。很容易想象，在一个小球场里会有很多本垒打。此外，棒球场的环境，如海拔，湿度，气压和风力，影响击球的轨迹。公园因素（PF）被引入棒球，以量化每个棒球场对结果的影响（例如，本垒打）。在本文中，我假设每个板块的外观可以建模为一个击球手的球队和投手的球队加上一个棒球场之间的比赛。将使用逻辑斯谛回归方法提取每个近似值的影响。数值验证表明，该方法的性能优于传统的PF。验证是基于从2010年至2017年美国职业棒球大联盟（MLB）赛季超过150万板出现的结果。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
