The majority of COD execution assessments employ the use of total time as the metric by which COD performance is judged. This study investigated the relationships between CODD time, sprint time, 5-10-5 and jump performance. Performance data of 328 participants of the 2021 NFL Combine (age: 22.35 ± 1.00 years; height: 1.87 ± 0.07m; weight: 108.51 ± 21.61kg) was collected and used for the analysis. CODD correlated to the 5- 10-5 pro-agility (r= 0.69 - 0.71) test but not sprint time (r= 0.15 - 0.27) for both the drafted and undrafted groups. Meanwhile, there was a large to very large association between 5-10-5 proagility time and the sprint variables (r = 0.62 - 0.82) for both drafted and undrafted groups. The correlation between CODD time and momentum was minor (r= 0.26 – 0.28) for both drafted and undrafted groups, but the 5-10-5 pro-agility reported a strong to a very strong association with momentum (r= 0.57 – 0.75). There was an inversely small correlation between CODD time and VJh (r= – 0.27) and BJ (r= -0.25– -0.28) for both drafted and undrafted groups whereas the 5-10-5 pro-agility time reported an inversely large to very large correlation with VJH (r= -0.51 – -0.68) and BJ (r= -0.57 – -0.71) on both groups. The magnitude and impact of the momentum, horizontal jump, and vertical jump of participants on their CODD time indicate that coaches and fitness experts should focus on improving the technical aspects of the COD execution when attempting to improve their CODS.

Participation in sports requires using Personal Protective Equipment (PPE) to preserve athletes’ well-being. Although equipment may negatively impact performance, governing bodies often impose standards on participants subject to their jurisdiction. Although the vast majority of new products are incremental innovations, radical innovation still attracts design researchers' and professionals' attention. The design of complex systems needs the expertise of various kinds: designers are fundamental in conceiving innovations in response to developing ways of product use and customer needs, despite they must face product standards, which often act against product innovation. Despite product innovations benefiting consumers in many markets, they do not necessarily benefit consumers in sports PPE markets. In this paper, the author reflects on an ethnographic case study and the importance of the involvement of end and co-dependent users in the design of sports PPE. For this study, the design of the Australian safety vests for jockeys, frequently overlooked, was examined for incremental innovation and its relationship with its standards. This was inspiring to consider an assessment of design values in designing product standards in the sports field. As co-design is increasingly applied across multiple sectors, there is a huge need for practical design guides to support product development and co-designing with users. Further research in this field is highly recommended.

This study represents a comprehensive exploration of the intricate interplay between morphological variables and throwing ability, specifically examining gender-specific variations among athletes in Cape Coast Metropolis, Ghana. In the pursuit of an understanding, data were collected from a diverse sample of 420 athletes, comprising 210 males and 210 females, aged between 16 and 22. The investigation illuminated that athletes within the Cape Coast Metropolis possess not only well-developed body dimensions but also an adequate level of fitness, both integral to overall athletic performance. This insight was substantiated by the statistical analysis, which demonstrated that morphological features accounted for a substantial 64% to 73% of the variance in throwing ability. The study employed predictive equations tailored for male and female athletes, further illustrating the influential role of specific morphological characteristics. For male athletes, the equation TB = -12.53 + .577handspan + .053Body weight + .109Total Arm Length - .055thigh girth + .053Chest Circumference Expiration - .094Tricep Skin Fold encapsulates the predictive model. On the other, the equation TG = -8.11 + .597Handspan + .068Upper Arm Length + .013Body Weight + .021Thigh Girth encapsulates the model for female athletes. These equations provide practical tools for forecasting throwing proficiency within the local athletic community in Cape Coast Metropolis. This research contributes significantly to the field, emphasizing the pivotal role of morphological variables in shaping athletic performance. The findings underscore the importance of training programs and talent identification processes based on an individual's morphological characteristics, with the potential to enhance overall athletic development in the Cape Coast Metropolis region.