Mean maximal power from an on-water 1000-m time-trial predicts lactate threshold power in well-trained flat-water sprint kayak athletes.

This study utilised on-water graded exercise tests (GXT) to determine the power output (PO) corresponding to the first and second lactate thresholds (LT1PO and LT2PO), subsequently examining their relationship to the mean maximal power (MMP) and race time achieved across three on-water sprint kayak time-trials. Twelve well-trained sprint kayak athletes completed an on-water GXT and a 200-, 500- and 1000-m time-trial utilising novel instrumented paddle technology. Stepwise multiple regression was used to determine whether equations incorporating 200-, 500- and 1000-m MMP data could be used as an alternative method for estimating LT1PO and LT2PO. On-water GXT derived LT1PO and LT2PO were 151 ± 34 and 194 ± 39 W, respectively. For the 200-, 500- and 1000-m time-trials, MMP were 528 ± 143, 358 ± 92 and 287 ± 67 W, respectively. Athletes' LT1PO and LT2PO had very-large inverse relationships to 200-, 500- and 1000-m time-to-completion (r = -.71 to -.85, P ≤ .010) and very-large, to near-perfect positive relationships to 200-, 500- and 1000-m MMP (r = .81 to .94, P ≤ .001). The equation incorporating 1000-m MMP alone provided the best prediction of LT1PO and LT2PO, explaining 78% and 88% of the variance, and yielding a standard error of estimate (SEE) of 11.3% and 7.1% for these measures, respectively. The results of this study provide further evidence to support the ecological validity of recently developed on-water GXTs graded by PO, since LT1PO and LT2PO were significantly correlated to 200-, 500- and 1000-m performance. Practitioners could also predict LT2PO with reasonable accuracy based solely from a 1000-m time-trial; potentially providing an alternative, non-invasive, competition-specific protocol for threshold determination.HighlightsThe fact that LT1PO and LT2PO had very-large, to near-perfect positive relationships to 200-, 500- and 1000-m MMP suggests that coaches should consider these relative submaximal aerobic-fitness variables when evaluating the performance of sprint kayak athletes, regardless of their race specialty.While the SEE and 95% limits of agreement (95%LoA) values for the prediction of LT1PO may be too large to be practically meaningful, measures of LT2PO could be predicted with a reasonable level of accuracy based upon 1000-m MMP.The ability to inform athletes' LT2PO from a single 1000-m time-trial is advantageous since it would provide a more feasible, and time-efficient testing protocol within the athletes' training schedule compared to GXTs, potentially allowing coaches and practitioners to monitor changes in LT2PO, and subsequently review individual training zones, more regularly.Given that LT1PO and LT2PO derived from on-water GXTs had very-large, to nearly perfect relationships to 200-, 500- and 1000-m performance, practitioners may prefer to use on-water, rather than laboratory-based GXTs given their greater practical significance and ecological validity.

Quantifying sprint kayak training on a flowing river: Exploring the utility of novel power measures and its relationship to measures of relative boat speed.

Quantification of external training load for sprint kayak athletes can be challenging due to the influence of the water flow on boat velocity in a flowing river environment. Therefore, this study examined the utility of novel measures of power output (PO) and its relationship to measures of relative boat speed when training on a flowing river. Twelve (8 males, 4 female) well-trained sprint kayak athletes completed 4 separate on-water sessions comprising one time-trial session (2 × 1000-m maximal efforts) and three repeated sprint kayak training sessions (5 x split 1000-m [2 × 500-m up and down the river] submaximal efforts) in their individual (K1) kayak. For each session, a Kayak Power Meter recorded athletes' PO, and a SpeedCoach device recorded relative land-speed via a Global Positioning System (GPS) (SGPS), and relative water-speed via an impeller mounted under the boat hull (SIMP). Non-linear least squares regression were used to evaluate the curvilinear relationship between PO and speed (SGPS and SIMP) data. The exponents of velocity in the PO-SIMP relationship (2.87 females, 2.94 males) were closer to theoretical values (3.00) and showed greater model accuracy (root mean squared error (RMSE) = 20-26 W) than the PO-SGPS relationships (speed exponents = 1.58-2.02, RMSE = 31-40 W). Overall, PO measures could better account for the influence of water flow compared to traditional SGPS measures, and therefore, may be more suitable for quantifying athletes' external load in their training environment.Highlights Since traditional SGPS and time-to-completion measures do not adjust for the water flow, these measures appear limited for prescribing and monitoring sprint kayak training within flowing river environments.The prescription of paddling PO across a wide spectrum of relative PO values elicited similar internal and external athlete responses, regardless of the direction travelled on a flowing river (i.e. upstream or downstream).The relationship between PO and SIMP during on-water sprint kayaking appears similar to those observed in rowing, where every percent change in boat speed measured relative to water (SIMP) requires a 2.87 and 2.94-fold percent change in paddling PO in female and male sprint kayak athletes, respectively.Continued evaluation of the PO-speed relationship for individual athletes may provide further insight into modelling performance and training targets for sprint kayak athletes.

Heart rate and stroke rate misrepresent supramaximal sprint kayak training as quantified by power.

This study examined the utility of novel measures of power output (PO) compared to traditional measures of heart rate (HR) and stroke rate (SR) for quantifying high-intensity sprint kayak training. Twelve well-trained, male and female sprint kayakers (21.3 ± 6.8 y) completed an on-water graded exercise test (GXT) and a 200-, 500- and 1000-m time-trial for the delineation of individualised training zones (T) for HR (5-zone model, T1-T5), SR and PO (8-zone model, T1-T8). Subsequently, athletes completed two repeat trials of a high-intensity interval (HIIT) and a sprint interval (SIT) training session, where intensity was prescribed using individualised PO-zones. Time-in-zone (minutes) using PO, SR and HR was then compared for both HIIT and SIT. Compared to PO, time-in-zone using HR was higher for T1 in HIIT and SIT (P < 0.001, d ≥ 0.90) and lower for T5 in HIIT (P < 0.001, d = 1.76). Average and peak HR were not different between HIIT (160 ± 9 and 173 ± 11 bpm, respectively) and SIT (157 ± 13 and 174 ± 10 bpm, respectively) (P ≥ 0.274). In HIIT, time-in-zone using SR was higher for T4 (P < 0.001, d = 0.85) and was lower for T5 (P = 0.005, d = 0.43) and T6 (P < 0.001, d = 0.94) compared to PO. In SIT, time-in-zone using SR was lower for T7 (P = 0.001, d = 0.66) and was higher for T8 (P = 0.004, d = 0.70), compared to PO. Heart rate measures were unable to differentiate training demands across different high-intensity sessions, and could therefore misrepresent the training load in such instances. Furthermore, SR may not provide a sensitive measure for detecting changes in intensity due to fatigue, whereas PO may be more suitable.

Competition warm-up strategies in sub-elite and elite flat-water sprint kayak athletes.

This study compared warm-up strategies employed by sub-elite and world-class elite sprint kayak athletes, evaluating their impact on subsequent race performance. Forty-seven (n = 33 male, n = 14 female) athletes competing at a National Sprint Kayak Championships had Global Navigation Satellite System devices fitted to their kayak to measure speed, distance and stroke rate during the on-water warm-up before racing (OWWU), and during racing. The OWWU total duration, average/peak speeds and stroke rates, and the time spent in speed-zones classified based upon athletes' relative race-pace (low-to-moderate, moderate-to-high, and race-specific) were compared between events, sexes, and athlete standard. The relationship of these variables to subsequent race performance, expressed as a percentage of the best time-to-completion for each event (%racebest), was also examined. Women spent greater OWWU time at moderate-to-high and race-specific speeds compared to men prior to 200-m and 500-m races (P ≤.001). Sub-elite men reported greater total OWWU duration for 200-m and 500-m (P ≤.025), but not for 1000-m races (P >.05) compared to elite men. Finally, %racebest had large inverse correlations to OWWU peak speed for men's 200-m (r = -.53), and average stroke rate for women's 500-m races (r = -.50). This study provides valuable insight for competition warm-up routines based upon data from an elite athlete population.

Comparison of Training Monitoring and Prescription Methods in Sprint Kayaking.

PURPOSE: To compare methods of monitoring and prescribing on-water exercise intensity (heart rate [HR], stroke rate [SR], and power output [PO]) during sprint kayak training. METHODS: Twelve well-trained flat-water sprint kayak athletes completed a preliminary on-water 7 × 4-min graded exercise test and a 1000-m time trial to delineate individual training zones for PO, HR, and SR into a 5-zone model (T1-T5). Subsequently, athletes completed 2 repeated trials of an on-water training session, where intensity was prescribed based on individual PO zones. Times quantified for T1-T5 during the training session were then compared between PO, HR, and SR. RESULTS: Total time spent in T1 was higher for HR (P < .01) compared with PO. Time spent in T2 was lower for HR (P < .001) and SR (P < .001) compared with PO. Time spent in T3 was not different between PO, SR, and HR (P > .05). Time spent in T4 was higher for HR (P < .001) and SR (P < .001) compared with PO. Time spent in T5 was higher for SR (P = .03) compared with PO. Differences were found between the prescribed and actual time spent in T1-T5 when using PO (P < .001). CONCLUSIONS: The measures of HR and SR misrepresented time quantified for T1-T5 as prescribed by PO. The stochastic nature of PO during on-water training may explain the discrepancies between prescribed and actual time quantified for power across these zones. For optimized prescription and monitoring of athlete training loads, coaches should consider the discrepancies between different measures of intensity and how they may influence intensity distribution.

Development of an On-Water Graded Exercise Test for Flat-Water Sprint Kayak Athletes.

PURPOSE: To determine the reliability and validity of a power-prescribed on-water (OW) graded exercise test (GXT) for flat-water sprint kayak athletes. METHODS: Nine well-trained sprint kayak athletes performed 3 GXTs in a repeated-measures design. The initial GXT was performed on a stationary kayak ergometer in the laboratory (LAB). The subsequent 2 GXTs were performed OW (OW1 and OW2) in an individual kayak. Power output (PWR), stroke rate, blood lactate, heart rate, oxygen consumption, and rating of perceived exertion were measured throughout each test. RESULTS: Both PWR and oxygen consumption showed excellent test-retest reliability between OW1 and OW2 for all 7 stages (intraclass correlation coefficient > .90). The mean results from the 2 OW GXTs (OWAVE) were then compared with LAB, and no differences in oxygen consumption across stages were evident (P ≥ .159). PWR was higher for OWAVE than for LAB in all stages (P ≤ .021) except stage 7 (P = .070). Conversely, stroke rate was lower for OWAVE than for LAB in all stages (P < .010) except stage 2 (P = .120). CONCLUSIONS: The OW GXT appears to be a reliable test in well-trained sprint kayak athletes. Given the differences in PWR and stroke rate between the LAB and OW tests, an OW GXT may provide more specific outcomes for OW training.

Classification of Intensity in Team Sport Activity.

PURPOSE: This study aimed to assess the efficacy of critical metabolic power derived from variable-speed movement for classifying intensity in team sport activity. METHODS: Elite male hockey players (n = 12) completed a series of time trials (100 yards, 400 yards, 1500 yards) and a 3-min all-out test to derive both critical speed (CS) and critical power (CP). Heart rate (HR), blood lactate, and rating of perceived exertion were measured during each protocol. Participants (n = 10) then played two competitive hockey matches. Time spent greater than 85% of maximum HR was compared with time spent above CS (from the time trials) and CP (from the 3-min test). RESULTS: Between protocols, there was a moderate and nonsignificant association for CS (r = 0.359, P = 0.252) and a very large association for CP (r = 0.754, P = 0.005); the association was very large for peak HR (r = 0.866, P < 0.001), large for blood lactate (r = 0.506, P = 0.093), and moderate for rating of perceived exertion (rho = 0.441, P = 0.152). Time trials produced higher CS (4.3 vs 2.0 m·s, P < 0.001) and CP (18.3 vs 10.5 W·kg, P < 0.001) values than did the 3-min test. In matches, there was a very large association between time spent above 85% of maximum HR and time spent above both CS (r = 0.719, P < 0.001) and CP (r = 0.867, P < 0.001). This relationship was stronger for CP compared with CS (Z = 3.29, P = 0.0007). CONCLUSIONS: Speed is not an appropriate parameter for the classification of team sport activity comprising continual changes in speed and direction; however, critical metabolic power derived from variable-speed activity seems useful for this purpose.