Predicting sprinting speed using agility and power tests in collegiate male soccer players - Rossi, S.; Eisenman, M.; DeJohn, D.; Phillips, D.; Ryan, G. (The Journal of Strength and Conditioning Research, 2021)
Preseason and in-season testing and evaluation of an athlete's physical abilities and readiness to train and compete may be limited either by time, administrator error, or finances. This is particularly true of determining maximum sprint speed, which can either be calculated from time to completion, which has been shown to introduce a fair amount of error, or more accurately measured via GPS devices, which may be outside the financial means of many coaches and staffs. One solution to this problem may be the use of accurate predictors and regression equations to estimate sprint speed from other sport specific tests. Purpose: The intent of this study was to determine potential predictors of maximum sprint speed from select measures of agility and power in collegiate soccer players. Methods: Fourteen Division I collegiate male soccer players (Age: 19.8 ± 1.3 years, Height: 1.78 ± 0.07 m, Weight: 72.6 ± 5.7 kg) participated in the study. All athletes completed a test battery that included: Pro Agility Shuttle (PAS), L-Drill (L-D), T-Drill (T-D), akimbo countermovement jump (CMJ), and 30 m maximum effort sprint (Smax). All athletes were allowed to complete each trial twice, and the best effort was included for analyses. Performance on the PAS and L-D were measured via stopwatches, CMJ on a switch mat, and Smax using GPS bio-harnesses. Pearson correlations were run on all variables to determine their relationship to Smax. Additionally, a forward multiple linear regression was calculated to predict maximum sprint speed based on all other variables of interest. Significance of relationships was calculated at p = 0.05. Results: A significant, positive, moderate correlation was found between BJ (248.1 ± 17.7 cm) and Smax (7.92 ± 0.31 m/s, r = 0.64; p = 0.02). No significant correlations were found between PAS (r = 0.64; p = 0.02), L-D (r = -0.42; p = 0.14), T-D (r = -0.40; p = 0.16), or CMJ (r = 0.49; p = 0.08) and Smax. A significant regression equation was found (F (1, 12) = 8.094, p = 0.02) with an adjusted R2 of 0.353. BJ was the only significant predictor of Smax. The prediction equation was Smax = 11.602 + 0.062(BJ). 95% CIs were [3.094, 7.279] and [0.003, 0.019] respectively. PAS (p = 0.94), L-D (p = 0.78), T-D (p = 0.86), and CMJ (p = 0.36) were not significant predictors of Smax in the tested population. Conclusions: BJ helped explain ~35% of the variance in Smax among Division I collegiate soccer players. BJ may be the best predictor of Smax due to the similar nature of horizontal plane explosion required for both tests. Practical Applications: Monitoring athlete ability and providing this information to coaches and training staffs is important to maximize performance during different phases of training when time is limited due to other requirements of sport. Strength and conditioning professionals should implement horizontal plane power development to potentially improve Smax in collegiate soccer players. Lastly, the ability to predict Smax based on BJ performance is key for managing time spent testing to allow adequate time for training other requirements of sport as well as providing a low cost alternative to estimating Smax compared to GPS bio-harnesses.