Applying Different Strategies of Task Constraint Manipulation in Small-Sided and Conditioned Games: How Do They Impact Physical and Tactical Demands?

Higher final speed in 30-15 intermittent fitness tests correlates with soccer's locomotor demands, not heart rate responses in small-sided soccer games

This study aimed to achieve two objectives: firstly, to analyze the relationships between aerobic fitness, as represented by the VIFT, and the heart rate and locomotor responses of youth male soccer players across various teams; and secondly, to compare players with lower and higher VIFT in terms of performance outcomes extracted during small-sided games (SSGs). A total of twenty-six youth male soccer players, aged 16.5 ± 0.32 years, with 3.4 ± 1.1 years of experience, voluntarily participated in the study. These players belonged to two regional-level tier 2 teams (trained/developmental). In the initial week of observation, the 30-15 Intermittent Fitness Test was implemented to measure the final velocity (VIFT) achieved by the players. Subsequently, the 5v5 format of play was conducted twice a week over two consecutive weeks, during which heart rate responses and locomotor demands were measured. The Pearson product-moment correlation test revealed a significant correlation between VIFT and the total distance covered during the 5v5 format (r = 0.471 [95% CI: 0.093; 0.721], p = 0.015). Conversely, small and non-significant correlations were identified between VIFT and mean heart rate (r = 0.280 [95% CI: - 0.126; 0.598]; p = 0.166), VIFT and peak heart rate (r = 0.237 [95% CI: - 0.170; 0.569]; p = 0.243), as well as VIFT and high-speed running (r = 0.254 [95% CI: - 0.153; 0.580]; p = 0.211). Players with higher VIFT demonstrated a significantly greater total distance, with a large effect size (+ 6.64%; p = 0.015; d = 1.033), compared to those with lower VIFT. Our findings suggest that improved performance in VIFT may lead to covering more distance in 5v5 matches. However, the lack of significant associations between VIFT and heart rate levels during SSGs suggests that they are not strongly correlated, possibly because VIFT is more closely linked to locomotor profile. As a practical implication, coaches may consider organizing players during SSGs based on their VIFT if the goal is to standardize locomotor demands.

Integrating physical and tactical factors in football using positional data: a systematic review

Background

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.

Methods and Materials

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).

Results

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 (n = 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 (n = 5). Quasi-experimental approaches considered training sets (n = 20) and match contexts (n = 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) (n = 1) and large-sided games (LSG) (n = 2), respectively.

Conclusions

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.