Prediction of Distance Running Performances of Female Runners Using Nomograms

Abstract

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.

Predictions of the Distance Running Performances of Female Runners Using Different Tools

“…These performances in the 3000-m, 5000-m and 10,000-m represented, respectively, 60±17%, 62±17% and 59±18% of the current outdoor world records. These performances were used in another recently published work 13 , which was focused on the prediction of distance running performances of female runners using nomograms ( i. e., nomogram of Mercier et al 24 and the two nomograms of Vandewalle 12 ).…”

“…of the three methods [1,2,4,5,7,13] and the lowest accuracy of the DTLM to predict the distance track-running performances of women. Indeed, although no study has compared the power law vs the nomogram, previous studies have shown that the power law was more accurate than the DTLM in predicting performance [5,11], and the nomogram was better than the DTLM, as well [4].…”

“…Indeed, it does not seem common to run slower over a shorter distance even though some evidence that runners, notably in long-distance like marathon, hit sometimes the wall suffer a relative slowdown [29]. This outlier removal procedure has been notably used in previous works [1,2,13,30].…”

“…Finally, to predict performance with the nomogram of Mercier et al [24], a numerical process was implemented using another custom-made MATLAB code to avoid human errors [13].…”

“…Finally, to predict performance with the nomogram of Mercier et al [24], a numerical process was implemented using another custom-made MATLAB code to avoid human errors [13]. Automatization avoids the errors that are possible during the manual process, as reported in Coquart et al [1].…”