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Objectives: The purpose of this study was to examine the relationship of velocities in the back squat between one repetition maximum (1RM) and submaximally loaded repetition maximum (RM) conditions, specifically in regard to what has been described as the minimal velocity threshold (MVT). The MVT describes a minimum concentric velocity that an individual must reach or surpass in order to successfully complete a repetition. Design: To test the presence of a MVT, participants were tested for 1RM and RM back squat ability. The mean concentric veloci ties (MCV) of the last successful repetition of each condition were then compared. Methods: Fourteen male participants familiar with the back squat volunteered to participate in the current study (age = 25.0 y ± 2.6, height = 178.9 cm ± 8.1, body mass = 88.2 kg ± 15.8). The mean concentric velocity (MCV) during the last successful repetition from each testing condition was considered for the comparison. Results: Results indicated a non-significant negative relationship of MCV between the 1RM and RM conditions (r = -0.135), no statistical difference between testing conditions (p = 0.266), with a small-to-moderate effect size (d = 0.468). Conclusions: The results of this study suggest that MVT should be further investigated to enhance its use in the practical setting. Additionally, coaches considering using a velocity-based approach for testing athletes should use data from either 1RM or RM conditions, but not both interchangeably. Coaches should be cautious when considering group averages or comparing velocity data between athletes, which may not be appropriate based on our results.

The present article addresses issues within U.S. collegiate sport as it pertains to the physical preparation and health and well-being of intercollegiate athletes. Specifically, the sport coach is often perceived as “all knowing” about every facet of their sport when, in fact, they typically are not formally educated or well-trained in current methods of enhancing sport performance. Often strength and conditioning coaches, who may also be poorly trained, are tied directly (financially and administratively) to the sport coach—a situation which has led to a subservient role heavily influenced by the wishes of the sport coach. This has unfortunately resulted in the multidimensional well-being of the athlete clearly not being a primary objective in many programs.

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The purpose of this study was to explore the interdepartmental integration between athletic trainers and strength and conditioning coaches in relation to relationship, communication, collaboration, and education. Forty participants from the NCAA Division I Southern Conference, twenty-eight athletic trainers and twelve strength and conditioning coaches, completed an electronic survey during a two-week period. Collected data were analyzed by descriptive and thematic coding analyses. The results suggested participated athletic trainers and strength and conditioning coaches were interactive and collaborative. Open-ended responses identified key concepts when athletic trainers and strength and conditioning coaches communicated and collaborated. A high interaction and collaboration model may be ideal to optimize athletes through rehabilitation while considering injury management, athlete monitoring, training program modifications, and athletic movement correction.

We examined a static jump test’s relationship with back squat strength in collegiate athletes. Forty-one (n=41) young (aged 20.8+2.4 years), healthy volunteers reported estimated back squat one-repetition maximums and completed a static jump protocol. The static jump protocol included five loading conditions, and jump height was estimated via flight time from portable contact mats. Loading conditions for males (n=19) included 0 kg (polyvinylchloride pipe), 20.42 kg, 43.10 kg, 61.25 kg, and 83.94 kg whereas females (n=22) used 0 kg, 12.70 kg, 20.42 kg, 29.49 kg, and 43.10 kg. Relationships between back squat one-repetition maximums, jump height, ratio (jump height/system mass) at each loading condition, mean jump height and ratio across loading conditions, change in jump height and ratio per condition (ΔJH, ΔRatio), and performance slope (slope of best fit line for system mass vs. jump height) were evaluated. Amongst all subjects, large (r>0.70), statistically significant correlations were found between back squat one-repetition maximums and jump height for the two lightest loading conditions, mean jump height, and performance slope. However, relationships varied by sex with mean jump height demonstrating the greatest consistency in both males and females. Mean jump height may be the most practical variable from this static jump protocol for monitoring training adaptations, particularly in relatively homogenous female collegiate athlete populations.

The purpose of this study was to assess and determine the current level of knowledge that National Collegiate Athletic Association (NCAA) Strength and Conditioning Coaches (SCCs) possess regarding exertional heat stroke (EHS) prevention and recognition and to determine if SCC certification type had any effect. Major findings of this study support the view that SCCs need more preparation, education and training to increase their competency in preventing and recognizing EHS. Research found that there was no significant difference in scores on the EHS scale based on SCC certification (CSCS vs. SCCC) after accounting for experience, education or division but the CSCS certified professionals scored higher on all the factors as compared to SCCs without the CSCS.. The major key finding was that SCCs lacked essential knowledge to prevent or recognize EHS. Furthermore, the study defines relevant EHS prevention and recognition competencies that an undergraduate curriculum, graduate curriculum and professional certification providers, should include and emphasize in their preparation programs.

Wearable tech has become increasingly popular with elite level sports organizations. The limiting factor to the value of the wearables is the use cases for the data they provide. This study introduces a technique to be used in tandem with this data to better inform training decisions. K-means clustering was used to group athletes from two seasons worth of data from an NCAA Division 1 American Football team. This data provided average game demands of each student-athlete, which was then used to create training groups. The resultant groupings showed results that were similar to traditional groupings used for training in American football, thus validating the results, while also offering insights on individuals that may need to consider training in a non-traditional group. In conclusion, this technique can be brought to athletic training and be useful in any organization that is dealing with training multitudes of athletes.