Methodological approaches and related challenges associated with the determination of critical power and W'

Whilst Critical Speed (CS) has been successfully translated from the laboratory into the field, this translation is still outstanding for the related maximum running distance (). Using iso-duration exhaustive laboratory and field runs, this study investigated the potential interchangeable use of both parameters, and CS. After an incremental exercise test, 10 male participants (age: 24.9±2.1 yrs; height: 180.8±5.8 cm; body mass: 75.3±8.6 kg; V̇ ˙VO 52.9±3.1 mL∙min∙kg) performed 3 time-to-exhaustion runs on a treadmill followed by 3 exhaustive time-trial runs on a-400 m athletics outdoor track. Field time-trial durations were matched to their respective laboratory time-to-exhaustion runs. and CS were calculated using the inverse-time model (speed=/t+CS). Laboratory and field values of and CS were not significantly different (221±7 m vs. 225±72 m;=0.73 and 3.75±0.36 m∙s vs. 3.77±0.35 m∙s, =0.68), and they were significantly correlated (=0.86 and 0.94). The 95% LoA were ±75.5 m and ±0.24 m∙s for and CS, respectively. Applying iso-durations provides non-significant differences for and CS and a significant correlation between conditions. This novel translation method can consequently be recommended to coaches and practitioners, however a questionable level of agreement indicates to use with caution.

To compare critical power (CP) and the maximum work performed above CP (W') obtained from a single-visit laboratory test with a single-visit field test, 10 trained cyclists (V˙O(2max) 63.2±5.5 mL·min(-1)·kg(-1)) performed a laboratory and a field test. The laboratory test consisted of 3 trials to exhaustion between 2-15 min and the field test comprised 3 maximal efforts of 2, 6 and 12 min, where power output was measured using a mobile power meter. CP and W' were estimated using 3 mathematical models (hyperbolic, linear work-time, linear power -1/time). The agreement between laboratory and field conditions was assessed with the 95% limits of agreement (LoA). CP was not significantly different between laboratory (280±33 W) and field conditions (281±28 W) (P=0.950). W' was significantly higher in laboratory (21.6±7.1 kJ) compared to field conditions (16.3±7.4 kJ) (P=0.013). The bias was -2.8±27 W (95% LoA: -55 to 50 W) and 6.4±5.1 kJ (95% LoA: -3.5 to 16.4 kJ) for CP and W', respectively. No differences between the mathematical models were found for CP and W' (P=0.054-1.000). Although CP was not significantly different between conditions, a high random variation does not support its interchangeable use. The mathematical model used has no influence on estimates of CP and W'.

Nimmerichter, A, Novak, N, Triska, C, Prinz, B, and Breese, BC. Validity of treadmill-derived critical speed on predicting 5,000-meter track-running performance. J Strength Cond Res 31(3): 706-714, 2017-To evaluate 3 models of critical speed (CS) for the prediction of 5,000-m running performance, 16 trained athletes completed an incremental test on a treadmill to determine maximal aerobic speed (MAS) and 3 randomly ordered runs to exhaustion at the [INCREMENT]70% intensity, at 110% and 98% of MAS. Critical speed and the distance covered above CS (D') were calculated using the hyperbolic speed-time (HYP), the linear distance-time (LIN), and the linear speed inverse-time model (INV). Five thousand meter performance was determined on a 400-m running track. Individual predictions of 5,000-m running time (t = [5,000-D']/CS) and speed (s = D'/t + CS) were calculated across the 3 models in addition to multiple regression analyses. Prediction accuracy was assessed with the standard error of estimate (SEE) from linear regression analysis and the mean difference expressed in units of measurement and coefficient of variation (%). Five thousand meter running performance (speed: 4.29 ± 0.39 m·s; time: 1,176 ± 117 seconds) was significantly better than the predictions from all 3 models (p < 0.0001). The mean difference was 65-105 seconds (5.7-9.4%) for time and -0.22 to -0.34 m·s (-5.0 to -7.5%) for speed. Predictions from multiple regression analyses with CS and D' as predictor variables were not significantly different from actual running performance (-1.0 to 1.1%). The SEE across all models and predictions was approximately 65 seconds or 0.20 m·s and is therefore considered as moderate. The results of this study have shown the importance of aerobic and anaerobic energy system contribution to predict 5,000-m running performance. Using estimates of CS and D' is valuable for predicting performance over race distances of 5,000 m.