Running Energy Reserve Index (RERI) as a new model for assessment and prediction of world, elite, sub-elite, and collegiate running performances

Abstract

Abstract The purpose of this study was to utilize the Running Energy Reserve Index (RERI) model and two-trial procedure to predict all-out athletic performances. Twenty-nine trained athletes tested for differences between RERIE and RERIspd (hypothesis 1). Six sprint trained (ST), six middle distance (MD), and six endurance trained (ET) athletes were selected to test for differences in the value of the constant. The prediction of all-out run performances using the RERI model (hypothesis 2) and two treadmill trials procedure (hypothesis 3) were tested on eighteen trained athletes. Lastly, three trained athletes were utilized to predict all-out running performances utilizing two track trials equation (hypothesis 3). RERIE and RERIspd were significantly different between ST, MD, and ET athletes. The RERIE model with a fixed cE value of 0.0185 s−1 predicted all-out running performances to within an average of 2.39 ± 2.04% (R2 = 0.99, nT = 252) for all athletes, with treadmill trials to within an average of 2.26 ± 1.89% (R2 = 0.99, nT = 203) and track trials to within an average of 2.95 ± 2.51% (R2 = 0.99, nT = 49). The two trials equations predicted all-out track performances to within errors of 2.43%. The RERI model may be accurate in determining running performances of 200 m and 5000 m, and treadmill performances ranging between 5 and 1340 s with a high level of accuracy. In addition, the two-trial procedure can be used to determine short and middle distance running performances of athletes and world-class runners.