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Basketball Players Performance Analytic as Experiential Learning Approach in Teaching Undergraduate Data Science Course

机译:篮球运动员表现分析作为教学本科数据科学课程的经验学习方法

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Sports analytic is an informative and beneficial tool especially for a coaching team who closely follow the development of their team. For a sports coach, deciding the best team composition is crucial to ensure winning. This requires understanding the dynamics of the players and the game parameters. However, small sports communities do not usually have the chance to benefit from this advanced technology. In a Data Mining course at Universiti Putra Malaysia, a data analytic project of basketball players' performance has been conducted through experiential learning approach. This paper presents the experience and output of shooting performance analytic, attack profiling analysis, team performance analysis, player rating prediction and game outcome prediction. The achievements of the students on the project are high with low marks deviation, plus the students said that the pedagogy encourages them to be highly committed and independent. Engaging lessons have also been happening as students compassionately share about their findings.
机译:体育分析是一种信息性和有益的工具,特别是对于密切关注其团队发展的教练团队。对于体育教练来说,决定最好的团队组成是至关重要的,以确保获胜。这需要了解玩家的动态和游戏参数。然而,小型体育社区通常没有机会从这种先进的技术中受益。在Putra Malaysia大学的数据矿业课程中,通过体验学习方法进行了一项篮球运动员绩效的数据分析项目。本文介绍了拍摄性能分析,攻击分析分析,团队性能分析,球员评级预测和游戏结果预测的经验和产出。该项目的成就率高,偏差低,而学生表示教育学鼓励他们高度承诺和独立。随着学生对他们的发现分享,也会发生从事课程。

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