考虑协同效应的团队绩效预测方法研究--以篮球团队成员组合为例

Incorporating synergistic effects in team performance prediction--The case of basketball squad management

产生良好的协同效应是团队高效运作的基础.在大数据背景下,利用数据分析手段实现协同效应以团队绩效成为了重要的研究课题.由于协同效应的测量较为困难,现有研究中往往主要考虑团队成员的个体信息,将协同效应作为研究结果的解释因素,而未将其纳入整体研究框架中.本文选择NBA(美国职业篮球联赛)作为研究情境,对篮球团队的协同效应进行定义;并提出三种算法,从团队成员之间的合作历史角度出发量化估计团队的协同效应;基于此提出考虑协同效应的团队绩效预测方法,从而指导团队构建.实验表明,考虑协同效应的团队绩效预测方法能够解决传统方法对团队阵容构建支持不够的问题,并实现较高的团队绩效预测准确率.

Synergistic effects are critical to team performance.In the big data era,data analytic tools have provided us with a new approach to evaluating the synergistic effects among team members and improve team performance.However,due to the difficulty in the measurement of synergistic effects,previous studies have only considered the information of individual team members in their frameworks and ignored the roles of synergistic effects.In this paper,we take the USA National Basketball Association(NBA)as an exemplar scenario and investigate the measurement of the synergistic effects among basketball players.We propose three algorithms to quantify the synergistic effects based on team members'cooperation history and to predict team performance'incorporating the evaluated values of synergistic effects.Experimental results illustrate the effectiveness of the introduction of synergistic effects into the team performance prediction framework.