Prediction of Distance Running Performances of Female Runners Using Nomograms - Lerebourg, Lucie; Guignard, Brice; Racil, Ghazi; Jlid, Mohamed Chedly; Held, Eric; Coquart, Jeremy Bernard (International Journal of Sports Medicine, 2022)
This study examined the validity, precision and accuracy of the predictions of distance running performances in female runners from three nomograms. Official rankings of French women for the 3000-m, 5000-m, and 10 000-m track-running events from 2005 to 2019 were examined. Only female runners who performed in the three distance events within the same year were included (n=158). Each performance over any distance was predicted using the three nomograms from the two other performances. The 3000-m, 5000-m and 10 000-m performances were 11min17 s±1min20 s, 19min29 s±2min20 s, 41min18 s±5min7 s, respectively. No difference was found between the actual and predicted running performances regardless of the nomogram (p>0.05). All predicted running performances were significantly correlated with the actual ones, with a very high correlation coefficient (p<0.001; r>0.90). Bias and 95% limits of agreement were acceptable because, whatever the nomogram, they were less than or equal to − 0.0±6.2% on the 3000-m, 0.0±3.7% on the 5000-m, and 0.1±9.3% on the 10 000-m. The study confirms the validity of the three nomograms to predict track-running performance with a high level of accuracy. The predictions from these nomograms are similar and may be used in training programs and competitions.
Keywords: estimation; modeling; time to exhaustion; validity; female athletes