论文标题
篮球运动员通过基于网络的变体参数隐藏马尔可夫模型评估的价值评估
Basketball Player's Value Evaluation by a Networks-based Variant Parameter Hidden Markov Model
论文作者
论文摘要
通过分析球员的行为来确定篮球运动员的价值对现代篮球队的经理很重要。但是，常规方法始终使用孤立的统计数据，从而导致无效和不准确的评估。基于动态网络理论的现有模型可以对此类评估的结果进行重大改进，但表示模型仍然不精确，因为它们仅专注于评估单个参与者的价值，而不是在当前的团队中考虑它们。为了解决这个问题，我们提出了一个基于网络和隐藏的马尔可夫模型的分析和评估模型。据我们所知，我们是第一个组合网络形式的人，代表使用隐藏的马尔可夫模型来开采网络并生成所需结果的玩家。将我们的方法应用于从国家篮球协会收集的SportVU数据中，表明该分析和评估模型可以有效地分析游戏中每个玩家的性能，并为团队经理提供辅助工具。
Determining the value of basketball players through analyzing the players' behavior is important for the managers of modern basketball teams. However, conventional methods always utilize isolated statistical data, leading to ineffective and inaccurate evaluations. Existing models based on dynamic network theory offer major improvements to the results of such evaluations, but said models remain imprecise because they focus merely on evaluating the values of individual players rather than considering them within their current teams. To solve this problem, we propose an analysis and evaluation model based on networks and a hidden Markov model. To the best of our knowledge, we are the first to combine a network form representing the players who are playing with the use of a hidden Markov model to mine the network and generate the desired results. Applying our approach to SportVU data collected from the National Basketball Association shows that this analysis and evaluation model can effectively analyze the performance of each player in a game and provides an assistive tool for team managers.
