Predictive Performance Models in Long-Distance Runners: A Narrative Review Physiological variables such as maximum oxygen uptake (VO2max), the speed at maximum oxygen uptake (VVO2max), the running economy and changes in the lactate level are considered as main factors for the performance for long-distance races. The aim of this review was to introduce the mathematical models available in the literature to estimate performance at the competitions 5'000 m, 10,000 m, half marathon and marathon. Eighty-eight articles have been identified, selections based on the inclusion criteria and the full text of the articles received. The articles were reviewed and categorized according to demographic, anthropometric, exercise physiology and field test variables. From 1983 to this day, a total of 58 studies were included, which were divided into the following categories: 12 to 5'000 m, 13 to 10'000 m, 12 on half marathon and 21 on Marathon. A total of 136 independent variables in connection with the performance in long-distance races were taken into account, of which 43.4% of variables derived from the evaluation of the aerobic metabolism, 26.5% variables associated with the training load, and 20.6% anthropometric variables, body composition and somatotypic components. The narrowest-associated variables in the predictive models for semi- and full marathon specialties were the variables obtained from the laboratory tests (Vo2max, VVO2max), training variables (training pace, training load) and anthropometric variables (fatty mass, skin folds). In predicting the time for long-distance races on the basis of field tests, there is a big gap.Physiological performance assessments are almost exclusively for shorter specialties (5'000 m and 10,000 m). The predictor variables of the half-marathon are mainly anthropometric, but with moderate determination coefficients.
The remarkable variables in the marathon category are essentially those associated with training, and those derived from physiological evaluations and anthropometric parameters. The work can be found under https://www.mdpi.com/1660-4601/17/21/8289