足球院校决策过程支持预测模型的建立——文献综述

R. Vrban
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引用次数: 0

摘要

足球的人才发展过程被认为是为年轻运动员提供最佳环境,以识别和实现其最大能力的过程。采用多维度的方法分析影响初级球员向高级球员转变的因素,可以为教练和管理层区分优秀球员和非优秀球员提供更好的支持。随着数字技术和人工智能的发展,越来越多的俱乐部能够对他们的青少年发展计划进行详细的分析。在本文中,我们专注于识别将数字技术与体育人才发展过程联系起来的良好实践。基于体育数据挖掘领域专家使用的既定方法和技术,我们希望选择一种合适的方法和方法从博士论文的数据中发现知识。文献综述是识别初级到高级过渡关键属性的整体过程的第一步。研究结果表明,综合分析运动数据的方法可以更好地识别年轻运动员的技能和属性。因此,体育数据挖掘在评估人才发展过程中各个层面的重要特征方面变得越来越重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Prediction Model for Support in Decision-Making Process in Football Academies – Literature Review
Talent development process in football is considered as a process of providing the optimal environment for identifying and realising the maximum ability of young athletes. A multidimensional approach to analysing factors that influence junior to senior transition can produce much better support for coaches and management to distinguish elite and non-elite players. With development of digital technologies and artificial intelligence, more clubs are able to perform detailed analysis of their youth development programme. In this paper, we focus on identfying good practices in connecting digital technologies with talent development process in sports. Based on established methods and techniques used by experts in a field of data mining within sports, we want to select an appropriate methodology and approach in discovering knowledge from the data for the doctoral dissertation. Literature review presents a first step in a hollistic process of identifying key attributes in junior to senior transition. The findings suggest that the comprehensive approach towards analysing data in sports, results in better identification of skills and attributes of young athletes. Consequently, data mining in sports is becoming more and more important in assessing important characteristics on every level within talent development process.
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