Predicting power outputs between 15s and 3600s

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitrag - Abstract in KonferenzbandForschungBegutachtung

Abstract

Einleitung/Introduction
Various models are available to model the power-duration relationship, however, most models only cover a specific section of the power-duration relationship. The anaerobic power reserve (APR) has been shown to be capable of predicting short duration (≤ 5 min) power outputs within the extreme/severe exercise intensity domain1. However, the best model to predict power outputs of up to 60 min is still discussed. Therefore, this study aimed to test, if the maximal aerobic power (MAP) and power at lactate threshold 2 (PLT2) can be used to predict power output between 5 min and 60 min.
Methode/Methods
32 well-trained male cyclists (age: 28.9 ± 9.8 yrs; VO2max: 67.6 ± 5.3 mL·min-1·kg-1) participated in this study. MAP was set as the peak power output during an incremental ramp test (160W, +20W/min). PLT2 was determined using a modified Lactate-Minimum Test (LMT). Furthermore, subjects performed all-out time trials over 300, 600, 1200, 2400, and 3600s.
Using the time trial data, an iterative best-fit approach was performed using a nonlinear least-squares analysis to determine an optimal time decay constant (k) for each individual. This was achieved by minimizing the sum of squared differences between the predicted and measured power. Based on the optimal individual exponential decay constants, a general time decay constant was established by taking the mean of the individual constants. Afterwards, the constant (k), MAP, and LT2 were used to predict power outputs over the mentioned durations using the following formula: P(t≥300s) = PLT2 + (MAP – PLT2) · e(-k·t). Predicted power was then compared with real power outputs, also from a “validation” study in another cohort (20 trained triathletes and cyclists; age: 31.1 ± 8.8 yrs; VO2max: 57.6 ± 7.1 mL·min-1·kg-1).
Ergebnisse/Results
The constant (k) calculated using our approach was k = -0.0012 ± 0.00038. Using the above-mentioned formula, the model showed very high correlations (r=0,91 (300 s); r=0,99 (600 s); r=0,98 (1200 s); r=0,95 (2400s); r=0,91 (3600s)), as well as absolute agreement (25 ± 27 W (300 s); -5 ± 11 W (600 s); -6 ± 7 W (1200 s); -8 ± 18 W (2400 s); -14 ± 25 W (3600 s)) with real power outputs. Further, it showed a very high correlation (r= 0,94) and absolute agreement (-7 ± 28 W) with power data from the validation study.
Diskussion/Discussion
The outcome parameters of our previously published diagnostic protocol2, consisting of a 15 s sprint test, a ramp test followed by a LMT, can be used to precisely predict performance up to 60 min.
Literatur/References

1. Sanders D, Heijboer M, Akubat I, Meijer K, Hesselink MK. Predicting High-Power Performance in Professional Cyclists. Int J Sports Physiol Perform. 2017 Mar;12(3):410-413.
2. Wahl P, Manunzio C, Vogt F, Strütt S, Volmary P, Bloch W, Mester J. Accuracy of a Modified Lactate Minimum Test and Reverse Lactate Threshold Test to Determine Maximal Lactate Steady State. J Strength Cond Res. 2017 Dec;31(12):3489-3496.
OriginalspracheEnglisch
TitelAbstractband
Erscheinungsdatum2023
PublikationsstatusVeröffentlicht - 2023
VeranstaltungJahrestagung dvs-Sektion Trainingswissenschaft: Optimizing Training in Sports, Exercise and Health - Deutsche Sporthochschule Köln, Köln, Deutschland
Dauer: 09.11.202310.11.2023

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