Running Functional Threshold versus Critical Power: Same Concept but Different Values.

The aims of this study were (i) to estimate the functional threshold power (FTP) and critical power (CP) from single shorter time trials (TTs) (i. e. 10, 20 and 30 minutes) and (ii) to assess their location in the power-duration curve. Fifteen highly trained athletes randomly performed ten TTs (i. e. 1, 2, 3, 4, 5, 10, 20, 30, 50 and 60 minutes). FTP was determined as the mean power output developed in the 60-min TT, while CP was estimated in the running power meter platform according to the manufacturer's recommendations. The linear regression analysis revealed an acceptable FTP estimate for the 10, 20 and 30-min TTs (SEE≤12.27 W) corresponding to a correction factor of 85, 90 and 95%, respectively. An acceptable CP estimate was only observed for the 20-min TT (SEE=6.67 W) corresponding to a correction factor of 95%. The CP was located at the 30-min power output (1.0 [-5.1 to 7.1] W), which was over FTP (14 [7.0 to 21] W). Therefore, athletes and practitioners concerned with determining FTP and CP through a feasible testing protocol are encouraged to perform a 20-min TT and apply a correction factor of 90 and 95%, respectively.

Can We Predict Long-Duration Running Power Output? Validity of the Critical Power, Power Law, and Logarithmic Models.

ABSTRACT: Ruiz-Alias, SA, Ñancupil-Andrade, AA, Pérez-Castilla, A, and García-Pinillos, F. Can we predict long-duration running power output? Validity of the critical power, power law, and logarithmic models. J Strength Cond Res 38(2): 306-310, 2024-Predicting long-distance running performance has always been a challenge for athletes and practitioners. To ease this task, different empirical models have been proposed to model the drop of the running work rate with the increase of time. Therefore, this study aims to determine the validity of different models (i.e., CP, power law, and Peronnet) to predict long-duration running power output (i.e., 30 and 60 minutes). In a 4-week training period, 15 highly trained athletes performed 7-time trials (i.e., 3, 4, 5, 10, 20, 30, and 60 minutes) in a randomized order. Then, their power-duration curves (PDCs) were defined through the work-time critical power model (CP work ), power-1/time (CP 1/time ), 2-parameter hyperbolic (CP 2hyp ), 3-parameter hyperbolic (CP 3hyp ), the undisclosed Stryd (CP stryd ), and Golden Cheetah (CP cheetah ) proprietary models, and the power law and Peronnet models using the 3 to 20 minutes time trials. These ones were extrapolated to the 30- and 60-minute power output and compared with the actual performance. The CP 2hyp , CP 3hyp , CP stryd , and CP cheetah provided valid 30- and 60-minute power output estimations (≤2.6%). The CP work and CP 1/time presented a large predicting error for 30 minutes (≥4.4%), which increased for 60 minutes (≥8.1%). The power law and Peronnet models progressively increased their predicting error at the longest duration (30 minutes: ≤-1.6%; 60 minutes: ≤-6.6%), which was conditioned by the endurance capability of the athletes. Therefore, athletes and practitioners are encouraged to applicate the aforementioned valid models to their PDC to estimate the 30-minute and 60-minute power output.

Running Critical Power and W´: Influence of the Environment, Timing and Time Trial Order.

This study aimed to determine the influence of the testing environment (track vs. treadmill), time trial order (long-short vs. short-long), and timing (within-session vs. between-sessions) on the critical power (CP) and work over CP (W´), using the power metric in runners. Fifteen highly trained athletes performed three test sessions composed of two time trials of 9- and 3-min, separated by a 30-min rest period. One session was performed on a track, and two sessions on a treadmill, alternating the order of the time trials. The CP and W´ values determined on the track were significantly greater and lower than on the treadmill, respectively (p<0.001; CP≥89 W; W´≥3.7 kJ). Their degree of agreement was low (SEE CP>5%; W´>10%) and therefore was not interchangeable. There were no performance differences in the timing of the time trials (p=0.320). Lastly, performing the 9-min trial first resulted in a greater power output compared to when executed last (p<0.001; 4.9 W), although this resulted in similar CP and W´ values (Bias<5 and 10%, respectively). In conclusion, it is feasible to test CP and W´ in a single testing session, irrespective of the time trial order, although not interchangeably between track and treadmill.

Running Critical Power: A Comparison Of Different Theoretical Models.

This study aimed (i) to compare the critical power (CP) and work capacity over CP (W´) values reported by the different CP models available in current analysis software packages (Golden Cheetah and Stryd platform), (ii) to locate the CP values in the power-duration curve (PDC), and (iii) to determine the influence of the CP model used on the W´ balance. Fifteen trained athletes performed four time trials (i. e., 3, 5, 10, 20 minutes) to define their PDC through different CP models: work-time (CPwork), power-1/time (CP1/time), Morton hyperbolic (CPhyp), Stryd platform (CPstryd), and Bioenergetic Golden Cheetah (CPCheetah). Three additional time trials were performed: two to locate the CP values in the PDC (30 and 60 minutes), and one to test the validity of the W' balance model (4 minutes). Significant differences (p<0.001) were reported between models for the estimated parameters (CP, W´). CPcheetah was associated with the power output developed between 10 to 20 minutes, CP1/time, CPstryd CPwork and CPhyp. The W´ reported by the three-parameter CP models overestimated the actual 4 minutes time to exhaustion, with CPwork (0.48 [- 0.19 to 1.16] minutes); and CP1/time (0.40 [- 0.13 to 0.94] minutes) being the only valid models (p≥0.240).

Can we predict long-duration running power output? A matter of selecting the appropriate predicting trials and empirical model.

When facing a long-distance race, athletes and practitioners could develop an efficient pacing strategy and training paces if an accurate performance estimate of the target distance is achieved. Therefore, this study aims to determine the validity of different empirical models (i.e. critical power [CP], Power law and Peronnet) to predict long-duration power output (i.e. 60 min) when using two or three time trial configurations. In a 5-week training period, fifteen highly trained athletes performed nine-time trials (i.e. 1, 2, 3, 4, 5, 10, 20, 30, and 60 min) in a randomized order. Their power-duration curves were defined through the work-time (CPwork), power-1/time (CP1/time), two-parameter hyperbolic (CP2hyp), three-parameter hyperbolic (CP3hyp) CP models using different two- and three-time trial configurations. The undisclosed proprietary CP models of the Stryd (CPstryd) and Golden Cheetah training software (CPcheetah) were also computed as well as the non-asymptotic Power law and Peronnet models. These were extrapolated to the 60-min power output and compared to the actual performance. The shortest valid configuration (95% confidence interval < 12 W) for CPwork and CP1/time was 3-30 min (Bias: 8.3 [4.9 to 11.7] W), for CPstryd was 10-30 min (Bias: 4.2 [- 1.0 to 9.4] W), for CP2hyp, CP3hyp and CPcheetah was 3-5-30 min (Bias < 5.7 W), for Power law was 1-3-10 min (- 1.0 [- 11.9 to 9.9] W), and for Peronnet was 4-20 min (- 3.0 [- 10.2 to 4.3] W). All the empirical models provided valid estimates when the two or three predicting trial configurations selected attended each model fitting needs.

9/3-Minute Running Critical Power Test: Mechanical Threshold Location With Respect to Ventilatory Thresholds and Maximum Oxygen Uptake.

PURPOSE: The critical power (CP) concept has been extended from cycling to the running field with the development of wearable monitoring tools. Particularly, the Stryd running power meter and its 9/3-minute CP test is very popular in the running community. Locating this mechanical threshold according to the physiological landmarks would help to define each boundary and intensity domain in the running field. Thus, this study aimed to determine the CP location concerning anaerobic threshold, respiratory compensation point (RCP), and maximum oxygen uptake (VO2max). METHOD: A group of 15 high-caliber athletes performed the 9/3-minute Stryd CP test and a graded exercise test in 2 different testing sessions. RESULTS: Anaerobic threshold, RCP, and CP were located at 73% (5.41%), 86.82% (3.85%), and 88.71% (5.84%) of VO2max, respectively, with a VO2max of 66.3 (7.20) mL/kg/min. No significant differences were obtained between CP and RCP in any of its units (ie, in watts per kilogram and milliliters per kilogram per minute; P ≥ .184). CONCLUSIONS: CP and RCP represent the same boundary in high-caliber athletes. These results suggest that coaches and athletes can determine the metabolic perturbance threshold that CP and RCP represent in an easy and accessible way.