(22) POSITIONAL COMPARISON OF JUMP MOMENTUM IN AMERICAN FOOTBALL

PURPOSE: As many sports require multiple physical performance qualities it is important to understand which of those qualities differ between playing positions. As such, the countermovement jump (CMJ) is commonly used as a method for determining positional differences. The CMJ also provides reliable data that does not induce high levels of fatigue; thus it is easily implemented into testing protocols. Collison based sports have seen an increase in the reporting of sprint momentum (body mass x sprint velocity) as momentum is a critical component to the outcome of the collision. Sprint momentum and jump momentum (JM) has been shown to have high to near-perfect correlation coefficients in rugby athletes. It has been reported that positional differences in JM have been seen in rugby athletes, and that body mass was a critical factor in the differences seen between groups. Thus, the purpose of this investigation was to examine positional differences of JM between positional groups in American football athletes. 

Methods:  95 Division I collegiate football athletes (age 20.18 ± 0.76 years, height 183.94 ± 5.63 cm, body mass 105.98 ± 24.68 kg) were tested at the beginning of the summer training block as a part of their routine athlete monitoring program. Participants were placed into one of three groups (Lineman = 32, Midskill = 29, Skill = 24). Participants performed three CMJ trials using a portable force platform with their arm swing restricted using a dowel placed across their upper back. Each participant was instructed to go to a self-selected countermovement depth and stance. Ground reaction force data was sampled at 1000 Hz. Data was then exported and processed using a customized Excel spreadsheet. Force-time data was then integrated to determine take-off velocity using the impulse-momentum theorem. JM was calculated using take-off velocity and body mass. Variables of interest for this investigation were JM, body mass, and take-off velocity. A one-way analysis of variance was performed on all variables of interest. If a significant effect was found a Fisher’s least significant difference post hoc analysis was performed. Additionally, Pearson product-moment correlation coefficients were calculated between JM, body mass, and take-off velocity. An apriori alpha level of 0.05 was used for all analyses. 

Results:  Each variable of interest displayed significant differences between positional groups (p≤0.001). JM was greatest in the lineman group and lowest in the skill group, with significant differences between each group (p≤0.001). A similar pattern was seen with body mass as the greatest values were seen in the lineman group and the smallest in the skill (p≤0.001). Take-off velocity was greatest in the skill group and lowest in the lineman group with significant differences seen between each group (p ≤ 0.001). Statistically significant (p< 0.05) relationships were present between JM and body mass (r=0.83) as well as JM and take-off velocity (r=-0.22). CONCLUSION: The results of this study support previous findings in which positional groups with the greatest body mass create the greatest JM. This data points to body mass being an important factor to JM with a high positive correlation value. PRACTICAL APPLICATION: The use of JM in the evaluation of training outcomes in football athletes would provide a metric that could potentially translate well based on the nature of the sport. 

Acknowledgements: None