Resumen de Can We Predict Long-Duration Running Power Output?: Validity of the Critical Power, Power Law, and Logarithmic Models
Santiago Ruiz Alias, Alberto Alejandro Ñancupil Andrade, Alejandro Pérez Castilla, Felipe García Pinillos
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: <=-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.
