The present study aimed to investigate how team’s tactical behavior varies within and between age categories in different Small-Sided and Conditioned Games’ configurations and conditions. Twenty non-elite youth male soccer players (U15, n = 10, mean age = 13.5 ± 1.2 years; U17, n = 10, mean age = 16.3 ± 0.5 years) were selected. Thirty-six Small-Sided and Conditioned Games (SSCG) were played in both categories, namely three Representative SSCG (R-SSCG), three Maintaining Ball Possession Games (MBPG) and three Progression to Target Games (PTG) performed for each configuration (Gk+3vs3+Gk and Gk+4vs4+Gk). Teams’ tactical behavior was analyzed based on simple and composite performance indicators, as well as through Lag Sequential Analysis. Rules manipulation and SSCG configurations influenced teams’ tactical behavior on both categories, but in different ways. Teams composed by younger players presented greater difficulties in MBPG played in smaller games configuration, while Gk+4vs4+Gk configuration can be used to enhance teams’ tactical performance of younger players in R-SSCG and MBPG conditions. Moreover, increasing rules manipulations appeared to negatively impact on teams’ exploratory behavior. Therefore, practitioners should carefully manipulate key constraints to adapt task demands to players’ age category and training session’s goals in order to enhance tactical performance.

This study analyzed the influence of rules manipulation on offensive patterns in different Small-Sided and Conditioned Games (SSCGs). Fourteen young soccer players (13.82 ± 1.94 years) performed two different SSCG formats (6v6+Gk): Maintenance of Ball Possession Game (MPG) and Progression to the Target Game (PTG). Both games were played on a field 52 m long by 32 m wide. We used the Offensive Sequences Characterization System (OSCS) and SoccerEye software to analyze offensive sequences. For statistical analysis, we used the Mann-Whitney test to compare variables that compose the OSCS between the two SSCGs, while the SDIS-GSEQ software allowed us to detect offensive patterns. We concluded that the rule manipulation of SSCGs influenced changes in teams' offensive patterns, in which they self-organized according to manipulation of key task constraints.

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