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This study aimed to compare the accuracy of the power output, measured by a power meter, with respect to the speed, measured by an inertial measurement unit (IMU) and a global navigation satellite system (GNSS) sport watch to determine the critical power (CP) and speed (CS), work over CP (W') and CS (D'), and long‐duration performance (i.e., 60 min). Fifteen highly trained athletes randomly performed seven time trials on a 400 m track. The CP/CS and W'/D' were defined through the inverse of time model using the 3, 4, 5, 10, and 20 min trials. The 60 min performance was estimated through the power law model using the 1, 3, and 10 min trials and compared with the actual performance. A lower standard error of the estimate was obtained when using the power meter (CP: 2.7 [2.1–3.3] % and W': 13.8 [10.4–17.3] %) compared to the speed reported by the IMU (CS: 3.4 [2.5–4.3] %) and D': 20.7 [16.6–24.7] %) and GNSS sport watch (CS: 3.4 [2.5–4.3] % and D': 20.6 [16.7–24.7] %). A lower coefficient of variation was also observed for the power meter (4.9 [3.7–6.1] %) Regarding the speed reported by the IMU (10.9 [7.1–14.8] %) and GNSS sport watch (10.9 [7.0–14.7] %) in the 60 min performance estimation, the power meter offered lower errors than the IMU and GNSS sport watch for modelling endurance performance on the track. Highlights: Recent advances in wearable technology are creating new opportunities to accurately monitor running intensity in contexts where precision is essential (i.e., track running) for athletes' (e.g., pacing) and coaches' (e.g., performance analysis) tasks.The track mode of recent global navigation satellite system (GNSS) sport watches seems to offer a decent improvement. Alternatively, new inertial measurement units (IMUs) designed specifically for running have emerged offering the capability to monitor distance in specific contexts such as treadmills and indoor tracks. Additionally, these IMUs provide new metrics of the external load.The power meter provided by the Stryd inertial measurement unit (IMU) demonstrated lower estimation errors in modelling endurance running performance on the track compared to speed data reported by the same IMU and a Garmin GNSS sports watch (using the track mode). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Ruiz-Alias, SA, Nncupil-Andrade, AA, Pe' rez-Castilla, A, and Garc'ıa-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 (CPwork), power-1/time (CP1/time), 2-parameter hyperbolic (CP2hyp), 3-parameter hyperbolic (CP3hyp), the undisclosed Stryd (CPstryd), and Golden Cheetah (CPcheetah) 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 CP2hyp, CP3hyp, CPstryd, and CPcheetah provided valid 30- and 60-minute power output estimations (#2.6%). The CPwork and CP1/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: #21.6%; 60 minutes: #2 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "Running Critical Power: A Comparison of Different Theoretical Models" published within a previous issue of the periodical.