Detecting tactical patterns in basketball: Comparison of merge self-organising maps and dynamic controlled neural networks
Detecting tactical patterns in basketball: Comparison of merge self-organising maps and dynamic controlled neural networks
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DOI：
10.1080/17461391.2014.933882
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发表时间：
2015-05-19
影响因子：
3.2
通讯作者：
Memmert, Daniel
中科院分区：
文献类型：
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作者：
Kempe, Matthias;Grunz, Andreas;Memmert, Daniel
近年来记录的数据量，特别是时空数据量的激增，需要先进的分析方法。从自组织映射衍生的神经网络将自己确立为分析静态和时间数据的有用工具。在本研究中，我们将合并自组织映射（MSOM）应用于时空数据。为此，我们研究了 MSOM 分析时空数据的能力，并将其性能与用于分析团队运动位置数据的通用动态控制网络 (DyCoN) 方法进行了比较。在一场篮球比赛中，Ubisense 追踪系统记录了 10 名球员的位置数据。此外，还录制了三个不同的预选戏剧进行分类。数据准备完毕后，使用上半场的数据对不同的网络进行训练。两个网络的训练成功通过获得的熵来评估。篮球比赛的下半场被提交给双方网进行自动分类。两种方法都能够非常好地呈现训练数据并正确检测预选的比赛。总之，MSOM 是分析时空数据的有用工具，尤其是在团队运动中。通过直接纳入不同时间长度的战术模式，他们在团队运动中开辟了新的机会。
The soaring amount of data, especially spatial-temporal data, recorded in recent years demands for advanced analysis methods. Neural networks derived from self-organizing maps established themselves as a useful tool to analyse static and temporal data. In this study, we applied the merge self-organising map (MSOM) to spatio-temporal data. To do so, we investigated the ability of MSOM ' s to analyse spatio-temporal data and compared its performance to the common dynamical controlled network (DyCoN) approach to analyse team sport position data. The position data of 10 players were recorded via the Ubisense tracking system during a basketball game. Furthermore, three different pre-selected plays were recorded for classification. Following data preparation, the different nets were trained with the data of the first half. The training success of both networks was evaluated by achieved entropy. The second half of the basketball game was presented to both nets for automatic classification. Both approaches were able to present the trained data extremely well and to detect the pre-selected plays correctly. In conclusion, MSOMs are a useful tool to analyse spatial-temporal data, especially in team sports. By their direct inclusion of different time length of tactical patterns, they open up new opportunities within team sports.