This study aimed to assess the associations between sprint force–velocity profile variables with change of direction (COD) performance and to investigate the impact of these variables on asymmetries in COD speed performance. Ninety-nine participants (volleyball players: n = 44, basketball players: n = 55) performed 40 m sprints for Fv relationship calculation, two COD tests (Modified Agility T-test and 505 test). A partial least squares (PLS) regression analysis was conducted to determine the relationships between the variables. The V₀ was the most influential variable; it was negatively associated with COD performance variables (β = −0.260, −0.263 and −0.244 for MAT, 505-D and 505-ND, respectively), and F₀ (β = 0.169, 0.163) was associated with the COD performance variables (COD deficit D and COD deficit ND, respectively), slightly larger than the effects of Fv_slope (β = −0.162, −0.146), D_RF (β = −0.159, −0.142) and P_max (β = −0.162, −0.146). For COD deficit imbalance, the D_RF (β = −0.070) was the most influential variable followed by Fv_slope (β = −0.068), F₀ (β = 0.046) and gender (β = 0.031). V₀ and RF_max were the critical variables for improving COD performance that includes linear sprints, while D_RF, Fv_slope, F₀ and P_max collectively influence 180° COD performance. Meanwhile, D_RF and Fv_slope were important factors for asymmetries in COD speed performance. It is recommended to use the Fv profile to diagnose different COD movement patterns and then develop training plans accordingly for team sports played on smaller courts, such as basketball and volleyball.

Background: Exercise training is known to improve metabolic health in individuals with obesity; however, its role in facilitating transitions between metabolically unhealthy obesity (MUO) and metabolically healthy obesity (MHO), as well as the associated metabolic adaptations, remains incompletely understood. Methods: A total of 84 young adults with obesity were enrolled and classified MUO (n = 55) or MHO (n = 29) based on baseline metabolic profiles. All participants completed an 8-week supervised exercise intervention. Anthropometric parameters, body composition, cardiometabolic markers, and VO₂max were assessed before and after the intervention. Targeted metabolomics of 30 amino acid-related metabolites was performed in the MHO-R (remained MHO) and MUO-C (conversion from MUO to MHO) groups to explore exercise-associated metabolic adaptations following intervention. Results: Exercise training improved cardiometabolic risk profiles, including reductions in adiposity and improvements in insulin resistance-related markers. A proportion of participants transitioned from metabolically unhealthy to metabolically healthy obesity following the intervention. No significant between-group differences in amino acid metabolite changes were observed between MHO-R and MUO-C groups. Exploratory metabolomic analyses identified exercise-responsive alterations in amino acid-related metabolites, particularly involving arginine biosynthesis and histidine metabolism. Conclusions: Combined aerobic and resistance training is associated with improvements in metabolic health and phenotype transition in young adults with obesity. Observed alterations in arginine and histidine metabolism may reflect metabolic adaptations to exercise rather than transition-specific or causal mechanisms underlying phenotype conversion.