Classification of Male Athletes Based on Critical Power

Abstract

This study aimed to classify male athletes based on their performance levels derived from running critical power (CP) using the 9/3-minute Stryd CP test, enabling customized training strategies and goal setting. Twenty-four trained athletes underwent the 9/3-minute running CP test on a certified 400-m athletics track. Hierarchical cluster analysis using Ward's method categorized athletes based on CP into distinct performance tiers. Three clusters were identified with centroids of 3.87±0.12, 4.45±0.17, and 5.14±0.29 W/kg. Five performance tiers were defined through ordinary least square linear regression based on power (W/kg): Tier 1: Fair (2.9 to 3.6 W/kg), Tier 2: Tourist (3.6 to 4.2 W/kg), Tier 3: Regional (4.2 to 4.8 W/kg), Tier 4: National (4.8 to 5.5 W/kg), Tier 5: International (5.5 to 6.1 W/kg). Low semi-partial R-squared (SpR ²) values (0.02 to 0.05) indicated minimal homogeneity loss when merging clusters. R-squared (R ²) explained 89% to 96% of CP variance, emphasizing cluster analysis effectiveness. The linear regression model demonstrated a strong fit (r ²+=+0.997) with a significant intercept (3.22 W/kg), slope (0.63 W/kg/tier), and a low standard error of estimate (0.045 W/kg). This classification offers insights into male athlete performance levels based on CP, facilitating targeted training programs for varying performance levels.

Keywords

performance - clustering - linear regression - running - tiers - training

Publikationsverlauf

Eingereicht: 29. November 2023

Angenommen: 06. Februar 2024

Artikel online veröffentlicht:
10. März 2024

• References

• 1 Joyner MJ. Physiological limits to endurance exercise performance: Influence of sex. J Physiol 2017; 595: 2949-2954
• 2 McKay AK, Stellingwerff T, Smith ES. et al. Defining training and performance caliber: A participant classification framework. Int J Sports Physiol Perform 2021; 17: 317-331
• 3 Olaya-Cuartero J, Cejuela R. Contextualisation of running power: A systematic review. J Phys Educ Sport 2020; 20: 2044-2051
• 4 Cerezuela-Espejo V, Hernández-Belmonte A, Courel-Ibáñez J. et al. Are we ready to measure running power? Repeatability and concurrent validity of five commercial technologies. Eur J Sport Sci 2021; 21: 341-350
• 5 Pringle JS, Jones AM. Maximal lactate steady state, critical power and EMG during cycling. Eur J Appl Physiol. 2002; 88: 214-226
• 6 Hill DW. The critical power concept: a review. Sports Med 1993; 16: 237-254
• 7 Dotan R. A critical review of critical power. Eur J Appl Physiol 2022; 122: 1559-1588
• 8 Olaya-Cuartero J, Pueo B, Penichet-Tomas A. et al. Does Power Output at Critical Power Intensity Interchange between Cycling and Running?. Appl Sci 2023; 13: 5511
• 9 Dearing CG, Paton CD. Is Stryd critical power a meaningful parameter for runners?. Biol Sport 2022; 40: 657-664
• 10 Ruiz-Alias SA, Olaya-Cuartero J, Ñancupil-Andrade AA. et al. 9/3-Minute Running Critical Power Test: Mechanical Threshold Location With Respect to Ventilatory Thresholds and Maximum Oxygen Uptake. Int J Sports Physiol Perform 2022; 1: 1-8
• 11 Olaya-Cuartero J, Pueo B, Villalon-Gasch L. et al. Prediction of Half-Marathon Power Target using the 9/3-Minute Running Critical Power Test. J Sports Sci Med 2023; 22: 526-530
• 12 Ruiz-Alias SA, Ñancupil-Andrade AA, Pérez-Castilla A. et al. Can we predict long-duration running power output? A matter of selecting the appropriate predicting trials and empirical model. Eur J Appl Physiol 2023; 10: 2283-2294
• 13 Olaya-Cuartero J, Sellés-Pérez S, Ferriz-Valero A. et al. A comparison between different tests for functional threshold power determination in running. J Phys Educ Hum Mov 2019; 1: 4-15
• 14 Passfield L, Hopker JG, Jobson S. et al. Knowledge is power: Issues of measuring training and performance in cycling. J Sports Sci 2017; 35: 1426-1434
• 15 Gorostiaga EM, Sánchez-Medina L, Garcia-Tabar I. Over 55 years of critical power: Fact or artifact?. Scand J Med Sci Sports 2022; 32: 116-124
• 16 Jones AM, Vanhatalo A. The ‘critical power’ concept: applications to sports performance with a focus on intermittent high-intensity exercise. Sports Med 2017; 47: 65-78
• 17 Pinot J, Grappe F. The record power profile to assess performance in elite cyclists. Int J Sports Med 2011; 32: 839-844
• 18 Van Dijk H, Van Megen R. The secret of running: Maximum performance gains through effective power metering and training analysis. Meyer & Meyer Sport (UK) Ltd.,. 2017 ISBN 978-1-78255-109-6
• 19 Ross WD. , Marfell-Jones Physiological Testing of the High-Performance Athlete. Kinanthropometry. Champaign IL: Human Kinetics Books. 1991
• 20 Lee JB, Sutter KJ, Askew CD. et al. Identifying symmetry in running gait using a single inertial sensor. J Sci Med Sport 2010; 13: 559-563
• 21 Withers RT, Craig NP, Bourdon PC. et al. Relative body fat and anthropometric prediction of body density of male athletes. Eur J Appl Physiol Occup Physiol 1987; 56: 191-200
• 22 Rocha M. Bone Weight of Brazilians of Both Sexes Aged 17 to 25 Years [Peso ósseo do brasileiro de ambos os sexos de 17 a 25 años]. Arq Anat Antropol 1975; 1: 445-451
• 23 Carter J. Carter J. Part 1: The Heath-Carter anthropometric somatotype-instruction manual. Tep and Rosscraft. Surrey: Canada. 2002
• 24 Flamme GA, Williams N. Sports officials’ hearing status: Whistle use as a factor contributing to hearing trouble. J Occup Environ Hyg 2013; 10: 1-10
• 25 Galbraith S, Daniel JA, Vissel B. A study of clustered data and approaches to its analysis. J Neurosci 2010; 30: 10601-10608
• 26 Kim H-Y. Statistical notes for clinical researchers: Simple linear regression 2-evaluation of regression line. Restor Dent Endod 2018; 43: e34