Department of Sport, Health and Exercise Science, University of Hull, Hull, United Kingdom.
Playermaker, London, United Kingdom.
PLoS One. 2021 Dec 16;16(12):e0260867. doi: 10.1371/journal.pone.0260867. eCollection 2021.
The primary aims of this study were to examine the effects of bio-banding players on passing networks created during 4v4 small-sided games (SSGs), while also examining the interaction of pitch size using passing network analysis compared to a coach-based scoring system of player performance. Using a repeated measures design, 32 players from two English Championship soccer clubs contested mixed maturity and bio-banded SSGs. Each week, a different pitch size was used: Week 1) small (36.1 m2 per player); week 2) medium (72.0 m2 per player); week 3) large (108.8 m2 per player); and week 4) expansive (144.50 m2 per player). All players contested 12 maturity (mis)matched and 12 mixed maturity SSGs. Technical-tactical outcome measures were collected automatically using a foot-mounted device containing an inertial measurement unit (IMU) and the Game Technical Scoring Chart (GTSC) was used to subjectively quantify the technical performance of players. Passing data collected from the IMUs were used to construct passing networks. Mixed effect models were used with statistical inferences made using generalized likelihood ratio tests, accompanied by Cohen's local f2 to quantify the effect magnitude of each independent variable (game type, pitch size and maturation). Consistent trends were identified with mean values for all passing network and coach-based scoring metrics indicating better performance and more effective collective behaviours for early compared with late maturation players. Network metrics established differences (f2 = 0.00 to 0.05) primarily for early maturation players indicating that they became more integral to passing and team dynamics when playing in a mixed-maturation team. However, coach-based scoring was unable to identify differences across bio-banding game types (f2 = 0.00 to 0.02). Pitch size had the largest effect on metrics captured at the team level (f2 = 0.24 to 0.27) with smaller pitch areas leading to increased technical actions. The results of this study suggest that the use of passing networks may provide additional insight into the effects of interventions such as bio-banding and that the number of early-maturing players should be considered when using mixed-maturity playing formats to help to minimize late-maturing players over-relying on their early-maturing counterparts during match-play.
本研究的主要目的是考察生物分组对 4v4 小场比赛（SSG）中传球网络的影响，同时使用传球网络分析对比基于教练的球员表现评分系统来考察场地大小的相互作用。采用重复测量设计，来自两个英格兰足球冠军联赛俱乐部的 32 名球员参加了混合成熟度和生物分组的 SSG。每周使用不同的场地大小：第 1 周）小（每名球员 36.1 平方米）；第 2 周）中（每名球员 72.0 平方米）；第 3 周）大（每名球员 108.8 平方米）；第 4 周）广阔（每名球员 144.50 平方米）。所有球员都参加了 12 场成熟度（不）匹配和 12 场混合成熟度的 SSG。使用包含惯性测量单元（IMU）的脚部安装设备自动收集技术战术结果指标，并使用比赛技术评分表（GTSC）主观量化球员的技术表现。从 IMU 收集的传球数据用于构建传球网络。使用混合效应模型进行统计推断，使用广义似然比检验，并辅以科恩的局部 f2 来量化每个自变量（比赛类型、场地大小和成熟度）的效应大小。所有传球网络和基于教练的评分指标的平均值都显示出一致的趋势，表明早期成熟的球员表现更好，集体行为更有效，而晚期成熟的球员则表现更差。网络指标确定了差异（f2 = 0.00 到 0.05），主要针对早期成熟的球员，表明他们在混合成熟的球队中打球时，对传球和团队动态变得更加不可或缺。然而，基于教练的评分无法识别生物分组比赛类型之间的差异（f2 = 0.00 到 0.02）。场地大小对团队层面上捕获的指标影响最大（f2 = 0.24 到 0.27），较小的场地面积导致技术动作增加。这项研究的结果表明，使用传球网络可能会为生物分组等干预措施的效果提供额外的见解，并且在使用混合成熟度比赛格式时，应该考虑到早期成熟球员的数量，以帮助在比赛中尽量减少晚期成熟球员过度依赖早期成熟球员。
