Statistical Analysis of Cricket Leagues Using Principal Component Analysis

Q4 Environmental Science
Sheharyar Khan
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引用次数: 0

Abstract

Any sport has statistics and cricket is one of the sports where statistics are significantly important because, on the based on these statistics, players are ranked. These statistics include individual runs, wickets, and highest scores, etc. Based on statistics, players are selected for any tournament around the world. This research uses Principal Component Analysis by evaluating cricket facts and figures. This analysis tests the precise co-variation among different measurements relating to the batting and bowling abilities of players in the Pakistan Super League PSL T-20 (2016-2019) and IPL T-20 (2016-2019) utilizing the progressed factual system Principal Component Analysis. In the current investigation, PCA was utilized to rank the top ten best-performing batsmen and bowlers of the PSL and IPL. Principal Component Analysis is a dimension reduction technique that is used to reduce dataset dimensions into smaller variables. We can presume that batting ability rules over bowling capacity. This exploration is the first report in Pakistan that features the highlights of the PSL and IPL.
用主成分分析法对板球联赛进行统计分析
任何运动都有统计数据,板球是统计数据非常重要的运动之一,因为根据这些统计数据,球员排名。这些统计数据包括个人跑动、三柱球和最高得分等。根据统计数据,球员被挑选参加世界各地的任何比赛。本研究使用主成分分析,评估板球事实和数据。本分析利用进展事实系统主成分分析测试了巴基斯坦超级联赛PSL T-20(2016-2019)和IPL T-20(2016-2019)球员击球和保龄球能力的不同测量之间的精确共变。在目前的调查中,PCA被用来排名前十位表现最好的击球手和投球手的PSL和IPL。主成分分析是一种降维技术,用于将数据集的维度降为更小的变量。我们可以假设击球能力高于保龄球能力。这一探索是巴基斯坦第一份以PSL和IPL为特色的报告。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Iranian Journal of Botany
Iranian Journal of Botany Environmental Science-Ecology
CiteScore
0.80
自引率
0.00%
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0
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