The proportional distribution of training by elite endurance athletes at different intensities during different phases of the season

The present review examines retrospective analyses of training intensity distribution (TID), i.e., the proportion of training at moderate (Zone 1, Z1), heavy (Z2) and severe (Z3) intensity by elite-to-world-class endurance athletes during different phases of the season. In addition, we discuss potential implications of our findings for research in this field, as well as for training by these athletes. Altogether, we included 175 TIDs, of which 120 quantified exercise intensity on the basis of heart rate and measured time-in-zone or employed variations of the session goal approach, with demarcation of zones of exercise intensity based on physiological parameters. Notably, 49% of the TIDs were single-case studies, predominantly concerning cross-country skiing and/or the biathlon. Eighty-nine TIDs were pyramidal (Z1 > Z2 > Z3), 65 polarized (Z1 > Z3 > Z2) and 8 "threshold" (Z2 > Z1 = Z3). However, these relative numbers varied between sports and the particular phases of the season. In 91% (n = 160) of the TIDs >60% of the endurance exercise was of low intensity. Regardless of the approach to quantification or phase of the season, cyclists and swimmers were found to perform a lower proportion of exercise in Z1 (<72%) and higher proportion in Z2 (>16%) than athletes involved in the triathlon, speed skating, rowing, running, cross-country skiing or biathlon (>80% in Z1 and <12% in Z2 in all these cases). For most of the athletes their proportion of heavy-to-severe exercise was higher during the period of competition than during the preparatory phase, although with considerable variability between sports. In conclusion, the existing literature in this area does not allow general conclusions to be drawn. The methods utilized for quantification vary widely and, moreover, contextual information concerning the mode of exercise, environmental conditions, and biomechanical aspects of the exercise is often lacking. Therefore, we recommend a more comprehensive approach in connection with future investigations on the TIDs of athletes involved in different endurance sports.

PARTICULAR CHARACTERISTICS OF PHYSICAL FITNESS IN THE TRAINING OF DANCERS

ABSTRACT Introduction: Chinese sports dance has occupied a prominent place worldwide due to its rapid development and the exchange between countries has gradually increased, requiring studies on the improvement in the training of these athletes. Objective: Study the particular characteristics of physical fitness and its insertion methods in the training of sport dancers. Methods: The author used the method of literature data, questionnaire survey and mathematical statistics to take the students specializing in sports dance in the School of Physical Education as research volunteers, performing a series of fitness index tests to check the most relevant characteristics to the fitness of their training. Results: The body shape training and special strength training, including special flexibility training is organized according to the demand standards. As for the physical training specific to dancers, the basic ballet training reaches 32 exercises, the strength training of the costal muscles, waist and abdomen 32 exercises, and the flexibility of the groin and legs 25 exercises, the latter being the key quality content for athletes. Conclusion: In-depth investigations and research are constantly being conducted into the content of special fitness training for students specializing in sports dance, and the factors influencing the particular fitness training have the potential to most effectively promote the development of sports dance. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Retrospective Analysis of Training Intensity Distribution Based on Race Pace Versus Physiological Benchmarks in Highly Trained Sprint Kayakers

Background

Research results on the training intensity distribution (TID) in endurance athletes are equivocal. This non-uniformity appears to be partially founded in the different quantification methods that are implemented. So far, TID research has solely focused on sports involving the lower-body muscles as prime movers (e.g. running). Sprint kayaking imposes high demands on the upper-body endurance capacity of the athlete. As there are structural and physiological differences between upper- and lower-body musculature, TID in kayaking should be different to lower-body dominant sports. Therefore, we aimed to compare the training intensity distribution during an 8-wk macrocycle in a group of highly trained sprint kayakers employing three different methods of training intensity quantification.

Methods

Heart rate (HR) and velocity during on-water training of nine highly trained German sprint kayakers were recorded during the final 8 weeks of a competition period leading to the national championships. The fractional analysis of TID was based on three zones (Z) derived from either HR (TID_Bla-HR) or velocity (TID_Bla-V) based on blood lactate (B_la) concentrations (Z1 ≤ 2.5 mmol L⁻¹ B_la, Z2 = 2.5–4.0 mmol L⁻¹ B_la, Z3 ≥ 4.0 mmol L⁻¹ B_la) of an incremental test or the 1000-m race pace (TID_Race): Z1 ≤ 85% of race pace, Z2 = 86–95% and Z3 ≥ 95%.

Results

TID_Bla-V (Z1: 68%, Z2: 14%, Z3: 18%) differed from TID_Bla-HR (Z1: 91%, Z2: 6%, Z3: 3%) in each zone (all p < 0.01). TID_Race (Z1: 73%, Z2: 20%, Z3: 7%) differed to Z3 in TID_Bla-V (p < 0.01) and all three TID_Bla-HR zones (all p < 0.01). Individual analysis revealed ranges of Z1, Z2, Z3 fractions for TID_Bla-HR of 85–98%, 2–11% and 0.1–6%. For TID_Bla-V, the individual ranges were 41–82% (Z1), 6–30% (Z2) and 8–30% (Z3) and for TID_Race 64–81% (Z1), 14–29% (Z2) and 4–10% (Z3).

Conclusion

The results show that the method of training intensity quantification substantially affects the fraction of TID in well-trained sprint kayakers. TID_Race determination shows low interindividual variation compared to the physiologically based TID_Bla-HR and TID_Bla-V. Depending on the aim of the analysis TID_Race, TID_Bla-HR and TID_Bla-V have advantages as well as drawbacks and may be implemented in conjunction to maximize adaptation.

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) (S_GPS), and relative water-speed via an impeller mounted under the boat hull (S_IMP). Non-linear least squares regression were used to evaluate the curvilinear relationship between PO and speed (S_GPS and S_IMP) data. The exponents of velocity in the PO-S_IMP 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-S_GPS 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 S_GPS measures, and therefore, may be more suitable for quantifying athletes' external load in their training environment.Highlights Since traditional S_GPS 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 S_IMP during on-water sprint kayaking appears similar to those observed in rowing, where every percent change in boat speed measured relative to water (S_IMP) 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.

The Relationship Between the Distribution of Training Intensity and Performance of Kayak and Canoe Sprinters: A Retrospective Observational Analysis of One Season of Competition

Purpose: To evaluate retrospectively the training intensity distribution (TID) among highly trained canoe sprinters during a single season and to relate TID to changes in performance.

Methods: The heart rates during on-water training by 11 German sprint kayakers (7 women, 4 men) and one male canoeist were monitored during preparation periods (PP) 1 and 2, as well as during the period of competition (CP) (total monitoring period: 37 weeks). The zones of training intensity (Z) were defined as Z1 [&lt;80% of peak oxygen consumption (VO2peak)], Z2 (81–87% VO2peak) and Z3 (&gt;87% VO2peak), as determined by 4 × 1,500-m incremental testing on-water. Prior to and after each period, the time required to complete the last 1,500-m stage (all-out) of the incremental test (1,500-m time-trial), velocities associated with 2 and 4 mmol·L−1 blood lactate (v2[BLa], v4[BLa]) and VO2peak were determined.

Results: During each period, the mean TID for the entire group was pyramidal (PP1: 84/12/4%, PP2: 80/12/8% and CP: 91/5/4% for Z1, Z2, Z3) and total training time on-water increased from 5.0 ± 0.9 h (PP1) to 6.1 ± 0.9 h (PP2) and 6.5 ± 1.0 h (CP). The individual ranges for Z1, Z2 and Z3 were 61–96, 2–26 and 0–19%. During PP2 VO2peak (25.5 ± 11.4%) markedly increased compared to PP1 and CP and during PP1 v2[bla] (3.6 ± 3.4%) showed greater improvement compared to PP2, but not to CP. All variables related to performance improved as the season progressed, but no other effects were observed. With respect to time-trial performance, the time spent in Z1 (r = 0.66, p = 0.01) and total time in all three zones (r = 0.66, p = 0.01) showed positive correlations, while the time spent in Z2 (r = −0.57, p = 0.04) was negatively correlated.

Conclusions: This seasonal analysis of the effects of training revealed extensive inter-individual variability. Overall, TID was pyramidal during the entire period of observation, with a tendency toward improvement in VO2peak, v2[bla], v4[bla] and time-trial performance. During PP2, when the COVID-19 lockdown was in place, the proportion of time spent in Z3 doubled, while that spent in Z1 was lowered; the total time spent training on water increased; these changes may have accentuated the improvement in performance during this period. A further increase in total on-water training time during CP was made possible by reductions in the proportions of time spent in Z2 and Z3, so that more fractions of time was spent in Z1.

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.Highlights The 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.

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.