Author(s): BARBRY, A., LEREBOURG, L., RACIL, G., CJLID, M., COQUART, J., Institution: UNIV. LILLE, UNIV. ARTOIS, UNIV. LITTORAL CÔTE D'OPALE, ULR 7369 - UREPSSS - UNI, Country: FRANCE, Abstract-ID: 318

INTRODUCTION:
The purpose of the current study was to develop and test the validity and accuracy of a simple equation in predicting 3000-m steeplechase performance (PerfSteeple) from individual variables (e.g., age, height, body mass and BMI) in men.
METHODS:
The official rankings of French runners for the 3000-m track-running (Perf3000) and 3000-m steeplechase events were examined. Moreover, age, height and body mass of runners were collected. From 146 included athletes, two groups were randomly composed: one comprising 80% of the sample (n = 117) to develop a simple equation to predict PerfSteeple (i.e., development group) and the other comprising the remaining 20% (n = 29) to test the validity and accuracy of the developed prediction equation (i.e., cross-validation group).
RESULTS:
The simple prediction equation included Perf3000 and age: PerfSteeple = -57.165 + 1.147 × Perf3000 + 0.955 × age. No significant difference was noted between the actual and predicted performances. Predicted performances were significantly correlated with the actual ones, with a very high correlation coefficient (p < 0.001; r = 0.929). Bias and 95% limits of agreement were -5 ± 24 s, i.e., -0.8 ± 7.6%.
CONCLUSION:
This equation (PerfSteeple = -89.740 + 1.153 × Perf3000m + 0.952 × age + 14.810 × sex) is a valid tool to predict 3000-m steeplechase performance according to a performance on 3000-m. This tool could be useful for athletes and coaches to predict a 3000-m steeplechase. It can enable them to adapt their training and to select the optimum speed for the athletes performance. This tool can also be useful for national directors in charge of performance in athletics federations to detect talent in the 3000m steeplechase and thus orient young athletes more easily towards this discipline.