Purpose: Predicting performance in sports competitions is a popular topic in research. However, only a few studies exist in rowing sports, which suggest that some anthropometric and performance indices might predict performance in various situations. Methods: This work expands past research by examining the effects of five anthropometric measures, such as body mass index (BMI), height, weight, fat, and muscle, and three performance indicators, such as aerobic capacity, maximum speed, and force, while also considering the training history of 38 elite rowers (Mage = 16.89 ± 1.85, range 14.7 to 22.6 years, 61% males) participating in a national championship. Results: Apart from BMI, all measures correlated statistically significantly with the 2000m rowing time. A bootstrapped forward multiple regression yielded the best model with only two predictors (R² =.995), aerobic capacity and body mass, accounting for 99.5% variance in the 2000m rowing time. Conclusions: While the results support previous findings, such robust prediction has not been reported in the literature. We conjecture that the differences from other past works rest with the high-pressure 2000m performance preceding a national championship. If these findings could be replicated, their practical implication is substantial in preparatory training for rowing contests.

Introduction: Although the relationship between functionality, as reflected in physical performance (PHP), and mental health in older adults has been researched, its strength remains unclear. Methods: This field study aimed to determine the strength of this relationship in adults aged 60 and above using seven PHP indices and six psychological measures. We individually tested 114 older adults. Objective measures included six PHP indices consisting of the Senior Test and handgrip strength. Subjective measures included resilience, wellbeing, happiness, perceived stress, hopelessness, and life satisfaction. Results: Structural equation modeling (SEM) revealed two latent constructs: PHP and mental wellbeing (MWB): robust fit (MLR): X² (75) = 136.28, p < 0.001; CFI = 0.967; TLI = 0.960; RMSEA = 0.066 (90% CI [0.000, 0.128]); SRMR = 0.088. The latent partial correlation between PHP and MWB (adjusted for Age) was φ = 0.46, indicating ∼21% shared variance. The correlation between the two latent factors was moderate (r = 0.46), suggesting that other unassessed factors might account for the relationship. Discussion: Based on objective PHP and subjective MWB measures, these results suggest a modest connection, with the two latent constructs sharing ∼1/5 of their variances. Consequently, further research is needed to identify other factors affecting the studied relationship in older adults. These cross-sectional findings, suggesting a moderate association, should be interpreted with caution. Still, they support recommending physical activity as one component of broader, multi-domain strategies to support the wellbeing of older adults.