The aims of this study were to analyze the within-group weekly metabolic power average (wMPA), weekly acceleration zones (wAcZ), and weekly deceleration zones (wDcZ), in starter and non-starter professional soccer players, based on different periods of the full season (pre-, early-, mid-, and end-season). Twenty-one professional soccer players (age, 28.3 ± 3.8 years; height, 181.2 ± 7.1 cm; body mass, 74.5 ± 7.7 kg; BMI, 22.6 ± 1.0 kg·m2) were monitored during the full season in the highest level of the Iranian Premier League. WMPA, wAcZ, and wDcZ at three different zones (wAcZ1, wAcZ2, wAcZ3, wDcZ1, wDcZ2, wDcZ3) were collected using Global Positioning System. ANOVA was applied to analyze within-group changes across the different periods of the full season. In general, starters presented higher values in the beginning of the season (pre- and early-season) and lower values at mid- and end-season. Specifically, starters showed significant differences in early- vs. mid-season for wMPA, wAcZ1, and wDcZ1 (p < 0.05), plus early- vs. end-season for wMPA and wAcZ1 (p < 0.01). In addition, non-starters showed higher values in the pre-season that decreased until the end-season for wMPA, wAcZ1, and wDcZ1. Regarding wAcZ2, wDcZ2, wAcZ3, and wDcZ3, non-starters presented higher values in early-season that decreased until the end-season. Specifically, non-starters showed significant differences in pre- vs. mid-season for wMPA, wAcZ1, and wDcZ1; pre- vs. end-season for wMPA, wDcZ1, wDccZ2, and wDcZ3; early- vs. mid-season for wMPA, wAcZ1, wDcZ1, wAcZ2, and wDccZ2; early- vs. end-season for wMPA, wAcZ1, wDcZ1, wAcZ2 wDccZ2, wAcZ3, and wDcZ3; and mid- vs. end-season for wMPA, wAcZ1, and wAcZ3 (p < 0.05). In conclusion, starters were revealed to have higher values in pre- and early-season, and lower values in mid- to end-season, while non-starters were revealed to have lower load values in pre- and end-season and higher load values in early- and mid-season. This study provides extra insights over the season for starters and non-starters, respectively. Data can be used by coaches to better training periodization across soccer season.