利用深度学习优化篮球的最佳发挥

Pub Date : 2022-02-15 DOI:10.3233/jsa-200524
L. Javadpour, Jessica Blakeslee, Mehdi A. Khazaeli, Pete Schroeder
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引用次数: 3

摘要

在势均力敌的篮球比赛中,胜负取决于一次投篮。能够为特定对手的防守确定最佳球员和比赛场景可以增加获胜的可能性。在过去的二十年里,技术的进步导致体育分析越来越受欢迎,团队和个人可以利用这些数据为自己谋利。体育运动中一种流行的数据分析技术是深度学习。深度学习是机器学习的一个分支,它可以在大数据中找到模式,并预测未来的决策。该过程依赖于用于训练目的的原始数据集。它可以在体育运动中使用,通过使用深度学习来读取数据,并更好地了解球员在哪里最成功。在这项研究中,使用的数据是一所私立大学第一赛区女子篮球比赛的数据,该比赛由排名前25的球队参加。深度学习被应用于针对给定的一组特征优化游戏场景中的最佳进攻。该系统用于预测将导致投篮命中率最高的比赛。
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Optimizing the best play in basketball using deep learning
In a close game of basketball, victory or defeat can depend on a single shot. Being able to identify the best player and play scenario for a given opponent’s defense can increase the likelihood of victory. Progress in technology has resulted in an increase in the popularity of sports analytics over the last two decades, where data can be used by teams and individuals to their advantage. A popular data analytic technique in sports is deep learning. Deep learning is a branch of machine learning that finds patterns within big data and can predict future decisions. The process relies on a raw dataset for training purposes. It can be utilized in sports by using deep learning to read the data and provide a better understanding of where players can be the most successful. In this study the data used were on division I women’s basketball games of a private university in a conference featuring top 25 teams. Deep learning was applied to optimize the best offensive play in a game scenario for a given set of features. The system is used to predict the play that would lead to the highest probability of a made shot.
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