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John L Grace, Meghan E Hancock, Madison L Malone, Bahman Adlou, Jerad J Kosek, Hannah R Houde, Christopher M Wilburn, Wendi H Weimar School of Kinesiology, Auburn University, Auburn, AL, USACorrespondence: John L Grace, School of Kinesiology, Auburn University, 301 Wire Road, Auburn, AL, 36849, USA, Tel +1 (334) 844-1468, Fax +1 (334) 844-1469, Email jlg0068@auburn.eduIntroduction: The National Football League (NFL) combine tests the athleticism of prospects competing for the draft. The vertical jump is included to test lower extremity power, yet the components which lead to the greatest performance remain elusive. Therefore, this study aimed to utilize a sample of elite athletes to analyze vertical jump components associated with increased performance and the relationship between vertical jump performance and rookie-year success.Methods: Videos of 50 NFL prospects performing the vertical jump task were analyzed for various countermovement jump components. Regression analyses examined the components in relation to normalized jump height and rookie Approximate Value (AV) using an alpha level of 0.05.Results: After analysis, only the overall model for normalized jump height was statistically significant (R^2^ = 0.69, p = 0.002).Discussion: While no single variable predicted jump height, distinct strategies were evident between the top and bottom 25% performers based on component correlations. The regression model approached significance in predicting rookie AV (R^2^ = 0.94, p = 0.052), with notable components like heel pauses for skilled positions and greater knee flexion for linemen. By creating models that can predict jump height or AV, variables can be identified that can be used to improve one’s jump height or, in the case of AV, that can be used to predict which draft prospects will perform better in the NFL.Keywords: athletes, technique, biomechanics, sport, video analysis