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Updated: Jun 11, 2025

Determining the Contribution of the Energy Systems During Exercise
Published on: March 20, 2012
Highest oxygen consumption prediction: introducing variable theoretical proportional factors for different sports
Irma Lorenzo-Capellá1, Juan José Ramos-Álvarez2, Maria Elena Jiménez-Herranz2
1Faculty of Education and Health, Camilo José Cela University, Madrid, Spain.
Purpose:
The use of a fixed theoretical-proportional-factor (TPF15) is one of the indirect highest-oxygen-consumptions (HOC) assessment methods, but it may not accurately reflect the physiological differences across various sports (cycling-triathlon-running-football-multisport). The aim of this study is to evaluate the variability of TPF across different sports, proposing a series of sport-specific new TPF values for more accurate HOC estimation.
Methods:
A sample of 340 adults (26.01 ± 7.18 years) performed a maximal-incremental-test using sport-specific-ergometers. HOC was considered for cycling , whereas for the other investigated sports it was considered . HOC was directly measured using a gas-analyzer, and TPF values were calculated using heart rate (HR): the ratio of HRmax/HRrest multiplied for the measured values of HOC. A one-way ANOVA was used to measure differences and Bland-Altman plots were constructed to compare predicted and actual / .
Results:
Actual HOC was significantly greater than those predicted by the fixed TPF15 (P < 0.001). Sport-specific new TPF values ranged from 16.55 in multisport to 20.15 in cycling, consistently exceeding the old fixed TPF15, and predicting therefore better HOC. The new TPF exhibited a closer agreement with the directly measured / compared to the TPF15. Furthermore, the new TPF reduced the typical-measurement-error (14.94-17.78%) compared to TPF15 (15.63-24.13%).
Conclusion:
This study suggests that new TPF values predict / with higher accuracy compared to the traditional method. The use of HRmax and HRrest values allows to customize training programs for different athletes. Future research should focus on validating these findings across larger populations of athletes.
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