用统计价值选择来概括篮球运动员的表现

Alexander Franklyn, Yessica Nataliani
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引用次数: 0

摘要

一个组织需要对个人绩效进行评估,以提高组织绩效,尤其是在篮球队中。萨提亚瓦卡纳圣徒萨拉蒂加是印度尼西亚篮球队,参加印度尼西亚篮球联赛(IBL)。所有球员在篮球比赛中都有统计价值,包括得分、助攻、盖帽、篮板和抢断。这五个特征可以作为教练员判定运动员表现的参考依据,包括表现良好、中等和较差的运动员。功能选择决定了最能影响玩家表现的功能。在本研究中,采用球员统计值的特征选择来评估篮球运动员的表现。该数据来自Satya Wacana圣徒萨拉蒂加队2021赛季的IBL统计数据。采用k-均值和模糊c-均值相结合的特征选择方法。实验结果表明,得分值是影响球员表现的主要因素。将k-means和模糊c-means算法与教练员评价的实际表现进行比较,模糊c-means算法的准确率为1.000,而k-means算法的准确率为0.8000。这意味着对玩家表现的评价可以使用模糊c均值算法从点数值中确定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PENGELOMPOKAN PERFORMA PEMAIN BASKET DENGAN SELEKSI FITUR NILAI STATISTIK MENGGUNAKAN K-MEANS DAN FUZZY C-MEANS
Assessment of individual performance in an organization is needed to improve organizational performance, not least in the basketball team. Satya Wacana Saints Salatiga is a basketball team in Indonesia that competes in the Indonesian Basketball League (IBL). All players have statistical values in a basketball game, including points, assists, blocks, rebounds, and steals. These five features can be used as a reference for coaches in determining the performance of players consisting of players with good, moderate, and poor performance. Feature selection determines the feature(s) that most affects a player's performance. In this study, a feature selection of the statistical value of players was carried out to assess the performance of basketball players. The data was obtained from IBL statistical data for the Satya Wacana Saints Salatiga team for the 2021 season. The method used was k-means and fuzzy c-means with feature selection. The experiment results showed that the point value was the main factor influencing players' performance. The comparison between the k-means and fuzzy c-means with the actual performance of the coaches' assessment shows that the fuzzy c-means algorithm has an accuracy rate of 1.0000, while the k-means algorithm is 0.8000. It means that the evaluation of the player's performance can be determined from the point value using the fuzzy c-means algorithm.
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