Research Center in Sports Sciences, Health Sciences and Human Development, Vila Real, Portugal.
Department of Sport Sciences and Physical Education, Instituto Politécnico de Bragança, Bragança, Portugal.
PeerJ. 2022 Nov 14;10:e14381. doi: 10.7717/peerj.14381. eCollection 2022.
Positional data have been used to capture physical and tactical factors in football, however current research is now looking to apply spatiotemporal parameters from an integrative perspective. Thus, the aim of this article was to systematically review the published articles that integrate physical and tactical variables in football using positional data.
Following the Preferred Reporting Item for Systematic Reviews and Meta-analyses (PRISMA), a systematic search of relevant English-language articles was performed from earliest record to August 2021. The methodological quality of the studies was evaluated using the modified Downs and Black Quality Index (observational and cross-sectional studies) and the Physiotherapy Evidence Database (PEDro) scale (intervention studies).
The literature search returned 982 articles (WoS = 495; PubMed = 232 and SportDiscus = 255). After screening, 26 full-text articles met the inclusion criteria and data extraction was conducted. All studies considered the integration of physical and tactical variables in football using positional data ( = 26). Other dimensions were also reported, such as psychophysiological and technical factors, however the results of these approaches were not the focus of the analysis ( = 5). Quasi-experimental approaches considered training sets ( = 20) and match contexts ( = 6). One study analysed both training and play insights. Small sided-games (SSG) were the most common training task formats in the reviewed studies, with only three articles addressing medium-sided (MSG) ( = 1) and large-sided games (LSG) ( = 2), respectively.
Among the current systematic review, the physical data can be integrated by player's movement speed. Positional datasets can be computed by spatial movement, complex indexes, playing areas, intra-team and inter-team dyads. Futures researches should consider applying positional data in women's football environments and explore the representativeness of the MSG and LSG.
位置数据已被用于捕捉足球中的身体和战术因素，但目前的研究现在正试图从综合的角度应用时空参数。因此，本文的目的是系统地回顾那些使用位置数据整合足球中身体和战术变量的已发表文章。
按照系统评价和荟萃分析的首选报告项目（PRISMA），从最早的记录到 2021 年 8 月，对相关的英文文章进行了系统搜索。使用改良的唐斯和布莱克质量指数（观察性和横断面研究）和物理治疗证据数据库（PEDro）量表（干预性研究）评估了研究的方法学质量。
文献检索返回了 982 篇文章（WoS = 495；PubMed = 232，SportDiscus = 255）。经过筛选，26 篇全文文章符合纳入标准并进行了数据提取。所有研究都考虑了使用位置数据整合足球中的身体和战术变量（=26）。其他维度也有报道，如心理生理和技术因素，但这些方法的结果不是分析的重点（=5）。准实验方法考虑了训练集（=20）和比赛环境（=6）。一项研究分析了训练和比赛的见解。小场比赛（SSG）是综述中最常见的训练任务格式，只有三篇文章分别涉及到中场（MSG）（=1）和大场比赛（LSG）（=2）。
在目前的系统综述中，可以通过球员的移动速度来整合物理数据。位置数据集可以通过空间移动、复杂指标、比赛区域、队内和队间的二元关系来计算。未来的研究应该考虑将位置数据应用于女子足球环境，并探索 MSG 和 LSG 的代表性。
