Int J Sports Med 2022; 43(11): 949-957
DOI: 10.1055/a-1821-6179
Training and Testing

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

Authors

  • Lucie Lerebourg

    1   CETAPS EA3832, Université de Rouen UFR Sciences et Techniques des Activités Physiques et Sportives, Mont-Saint-Aignan, France
  • Brice Guignard

    1   CETAPS EA3832, Université de Rouen UFR Sciences et Techniques des Activités Physiques et Sportives, Mont-Saint-Aignan, France
  • Maxime L’Hermette

    1   CETAPS EA3832, Université de Rouen UFR Sciences et Techniques des Activités Physiques et Sportives, Mont-Saint-Aignan, France
  • Eric Held

    2   Clinique Mathilde 2, Orthodynamica, Rouen, France
  • Jérémy Bernard Coquart

    1   CETAPS EA3832, Université de Rouen UFR Sciences et Techniques des Activités Physiques et Sportives, Mont-Saint-Aignan, France
    3   Univ. Lille, Univ. Artois, Univ. Littoral Côte d'Opale, ULR 7369 - URePSSS - Unité de Recherche Pluridisciplinaire Sport Santé Société, Lille, France

Funding The authors are grateful to the French Athletics Federation (Fédération Française d’Athlétisme) for data diffusion, and the Orthodynamica Center at Mathilde Hospital 2 for funding.
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Abstract

This study examined the validity and compared the precision and accuracy of a distance-time linear model (DTLM), a power law and a nomogram to predict the distance running performances of female runners. Official rankings of French women (“senior” category: between 23 and 39 years old) for the 3000-m, 5000-m, and 10,000-m track-running events from 2005 to 2019 were examined. Performances of runners who competed in the three distances during the same year were noted (n=158). Mean values and standard deviation (SD) of actual performances were 11.28±1.33, 19.49±2.34 and 41.03±5.12 for the 3000-m, 5000-m, and 10,000-m respectively. Each performance was predicted from two other performances. Between the actual and predicted performances, only DTLM showed a difference (p<0.05). The magnitude of the differences in these predicted performances was small if not trivial. All predicted performances were significantly correlated with the actual ones, with a very high correlation coefficient (p<0.001; r>0.90), except for DTLM in the 3000-m, which showed a high correlation coefficient (p<0.001; r>0.895). Bias and 95% limits of agreement were acceptable because, whatever the method, they were≤–3.7±10.8% on the 3000-m, 1.4±4.3% on the 5000-m, and -2.5±7.4% on the 10,000-m. The study confirms the validity of the three methods to predict track-running performance and suggests that the most accurate and precise model was the nomogram followed by the power law, with the DTLM being the least accurate.



Publication History

Received: 23 October 2021

Accepted: 05 April 2022

Accepted Manuscript online:
08 April 2022

Article published online:
27 June 2022

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