Training Intensity Distribution and Changes in Performance and Physiology of a 2nd Place Finisher Team of the Race across America Over a 6 Month Preparation Period

Physiological and Locomotor Profiling Enables to Differentiate Between Sprinters, 400-m Runners, and Middle-Distance Runners

ABSTRACT

Thron, M, Woll, A, Doller, L, Quittmann, OJ, Härtel, S, Ruf, L, and Altmann, S. Physiological and locomotor profiling enables to differentiate between sprinters, 400-m runners, and middle-distance runners. J Strength Cond Res 38(8): 1419-1427, 2024-Different approaches exist for characterizing athletes, e.g., physiological and locomotor profiling. The aims of this study were to generate and compare physiological and locomotor profiles of male and female runners and to evaluate relationships between the different approaches. Thirty-four highly trained adolescent and young adult female and male athletes ( n = 11 sprinters; n = 11,400-m runners; n = 12 middle-distance runners) performed two 100-m sprints on a running track to determine maximal sprinting speed (MSS) and maximal lactate accumulation rate (ċLa max ). A cardiopulmonary exercise test was performed on a treadmill to determine maximal aerobic speed (MAS) and maximal oxygen uptake (V̇ o2 max). Anaerobic speed reserve (ASR) was calculated as the difference between MSS and MAS. Group comparisons were conducted with a 2-way ANOVA (discipline × sex; p < 0.05) and Bonferroni post hoc tests and Cohen's d as effect size. Parameters were correlated by Pearson's correlation coefficients. Maximal aerobic speed and V̇ o2 max were higher in 400-m and middle-distance runners compared with sprinters ( p ≤ 0.02; -2.24 ≤ d ≤ -1.29). Maximal sprinting speed and ċLa max were higher in sprinters and 400-m runners compared with middle-distance runners (0.03 ≤ p ≤ 0.28; 0.73 ≤ d ≤ 1.23). Anaerobic speed reserve was highest in sprinters and lowest in middle-distance runners ( p ≤ 0.03; 1.24 ≤ d ≤ 2.79). High correlations were found between ASR and MAS, MSS, and ċLa max ( p < 0.01; -0.55 ≤ r ≤ 0.91) and between ċLa max and MSS ( p < 0.01; r = 0.74). Our results indicate that athletes of different sprinting and running disciplines show differing physiological and locomotor profiles, and that the parameters of these approaches are related to each other. This can be of interest for assessing strengths and weaknesses (e.g., for talent identification) or training prescription in these disciplines.

Reliability of power output, maximal rate of capillary blood lactate accumulation, and phosphagen contribution time following 15-s sprint cycling in amateur cyclists

Based on Mader's mathematical model, the rate of capillary blood lactate concentration (νLamax) following intense exercise is thought to reflect the maximal glycolytic rate. We aimed to investigate the reliability of important variables of Mader's model (i.e. power output, lactate accumulation, predominant phosphagen contribution time frames (tP Cr)) and resulting νLamax values derived during and after a 15-s cycling sprint. Fifty cyclists performed a 15-s all-out sprint test on a Cyclus2 ergometer three times. The first sprint test was considered a familiarization trial. Capillary blood was sampled before and every minute (for 8 min) after the sprint to determine νLamax. Test-retest analysis between T2 and T3 revealed excellent reliability for power output (Pmean and Ppeak; ICC = 0.99, 0.99), ∆La and νLamax with tPCr of 3.5 s (ICC = 0.91, 0.91). νLamax calculated with tPCr = tP peak (ICC = 0.87) and tP Cr = tPpeak-3.5% (ICC = 0.79) revealed good reliability. tPpeak and tPpeak-3.5% revealed only poor and moderate reliability (ICC = 0.41, 0.52). Power output and ∆La are reliable parameters in the context of this test. Depending on tPCr, reliability of νLamax varies considerably with tP Cr of 3.5 s showing excellent reliability. We recommend standardization of this type of testing especially tP Cr.

Ultra-Cycling- Past, Present, Future: A Narrative Review

BACKGROUND

Ultra-endurance events are gaining popularity in multiple exercise disciplines, including cycling. With increasing numbers of ultra-cycling events, aspects influencing participation and performance are of interest to the cycling community.

MAIN BODY

The aim of this narrative review was, therefore, to assess the types of races offered, the characteristics of the cyclists, the fluid and energy balance during the race, the body mass changes after the race, and the parameters that may enhance performance based on existing literature. A literature search was conducted in PubMed, Scopus, and Google Scholar using the search terms 'ultracycling', 'ultra cycling', 'ultra-cycling', 'ultra-endurance biking', 'ultra-bikers' and 'prolonged cycling'. The search yielded 948 results, of which 111 were relevant for this review. The studies were classified according to their research focus and the results were summarized. The results demonstrated changes in physiological parameters, immunological and oxidative processes, as well as in fluid and energy balance. While the individual race with the most published studies was the Race Across America, most races were conducted in Europe, and a trend for an increase in European participants in international races was observed. Performance seems to be affected by characteristics such as age and sex but not by anthropometric parameters such as skin fold thickness. The optimum age for the top performance was around 40 years. Most participants in ultra-cycling events were male, but the number of female athletes has been increasing over the past years. Female athletes are understudied due to their later entry and less prominent participation in ultra-cycling races. A post-race energy deficit after ultra-cycling events was observed.

CONCLUSION

Future studies need to investigate the causes for the observed optimum race age around 40 years of age as well as the optimum nutritional supply to close the observed energy gap under consideration of the individual race lengths and conditions. Another research gap to be filled by future studies is the development of strategies to tackle inflammatory processes during the race that may persist in the post-race period.

Reliability of the Maximal Lactate Accumulation Rate in Rowers

The maximal lactate accumulation rate (VLamax) has been linked to lactic anaerobic performance. Hence, accurate and reliable assessment is crucial in sport-specific performance testing. Thus, between-day reliability data of rowing-specific VLamax assessment was examined. Seventeen trained rowers (eight females and nine males; 19.5±5.2 yrs; 1.76±0.08 m; 70.2±8.9 kg; V̇O2max: 54±13 ml/min/kg) performed 20-s sprint tests on two separate days (one week apart) on a rowing ergometer. VLamax, peak lactate concentration, time to peak lactate, and mean rowing power were measured. Good to excellent intraclass correlation coefficients (ICCs), low standard error of measurement (SEM), and acceptable levels of agreement (LoAs; 90% confidence interval) for VLamax (ICC=0.85; SEM=0.02 mmol/L/s; LoA±0.09 mmol/L/s), peak lactate (ICC=0.88; SEM=0.3 mmol/L; LoA±1.4 mmol/l), time to peak lactate (ICC=0.92; SEM=0.1 min; LoA±0.5 min), and mean rowing power (ICC=0.98; SEM=3 W; LoA±39 W) were observed. In addition, VLamax was highly correlated (r=0.96; p≤0.001) to rowing power. Thus, VLamax and sprint performance parameters can be measured highly reliably using this sport-specific sprint test in rowing.

A modified formula using energy system contributions to calculate pure maximal rate of lactate accumulation during a maximal sprint cycling test

Purpose: This study aimed at comparing previous calculating formulas of maximal lactate accumulation rate ( ν La.max) and a modified formula of pure ν La.max (P ν La.max) during a 15-s all-out sprint cycling test (ASCT) to analyze their relationships. Methods: Thirty male national-level track cyclists participated in this study (n = 30) and performed a 15-s ASCT. The anaerobic power output (Wpeak and Wmean), oxygen uptake, and blood lactate concentrations (La-) were measured. These parameters were used for different calculations of ν La.max and three energy contributions (phosphagen, W PCr; glycolytic, W Gly; and oxidative, W Oxi). The P ν La.max calculation considered delta La-, time until Wpeak (tPCr-peak), and the time contributed by the oxidative system (tOxi). Other ν La.max levels without tOxi were calculated using decreasing time by 3.5% from Wpeak (tPCr -3.5%) and tPCr-peak. Results: The absolute and relative W PCr were higher than W Gly and W Oxi (p < 0.0001, respectively), and the absolute and relative W Gly were significantly higher than W Oxi (p < 0.0001, respectively); ν La.max (tPCr -3.5%) was significantly higher than P ν La.max and ν La.max (tPCr-peak), while ν La.max (tPCr-peak) was lower than P ν La.max (p < 0.0001, respectively). P ν La.max and ν La.max (tPCr-peak) were highly correlated (r = 0.99; R 2 = 0.98). This correlation was higher than the relationship between P ν La.max and ν La.max (tPCr -3.5%) (r = 0.87; R 2 = 0.77). ν La.max (tPCr-peak), P ν La.max, and ν La.max (tPCr -3.5%) were found to correlate with absolute Wmean and W Gly. Conclusion: P ν La.max as a modified calculation of ν La.max provides more detailed insights into the inter-individual differences in energy and glycolytic metabolism than ν La.max (tPCr-peak) and ν La.max (tPCr -3.5%). Because W Oxi and W PCr can differ remarkably between athletes, implementing their values in P ν La.max can establish more optimized individual profiling for elite track cyclists.

A Novel Approach to Determining the Alactic Time Span in Connection with Assessment of the Maximal Rate of Lactate Accumulation in Elite Track Cyclists

PURPOSE

Following short-term all-out exercise, the maximal rate of glycolysis is frequently assessed on the basis of the maximal rate of lactate accumulation in the blood. Since the end of the interval without significant accumulation (talac) is 1 of 2 denominators in the calculation employed, accurate determination of this parameter is crucial. Although the very existence and definition of talac, as well as the validity of its determination as time-to-peak power (tPpeak), remain controversial, this parameter plays a key role in anaerobic diagnostics. Here, we describe a novel approach to determination of talac and compare it to the current standard.

METHODS

Twelve elite track cyclists performed 3 maximal sprints (3, 8, and 12 s) and a high-rate, low-resistance pedaling test on an ergometer with monitoring of crank force and pedaling rate. Before and after each sprint, capillary blood samples were taken for determination of lactate accumulation. Fatigue-free force-velocity and power-velocity profiles were generated. talac was determined as tPpeak and as the time point of the first systematic deviation from the force-velocity profile (tFf).

RESULTS

Accumulation of lactate after the 3-second sprint was significant (0.58 [0.19] mmol L-1; P < .001, d = 1.982). tFf was <3 seconds and tPpeak was ≥3 seconds during all sprints (P < .001, d = - 2.111). Peak power output was lower than maximal power output (P < .001, d = -0.937). Blood lactate accumulation increased linearly with increasing duration of exercise (R2 ≥ .99) and intercepted the x-axis at ∼tFf.

CONCLUSION

Definition of talac as tPpeak can lead to incorrect conclusions. We propose determination of talac based on tFf, the end of the fatigue-free state that may reflect the beginning of blood lactate accumulation.

Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?

Endurance running performance can be predicted by maximal oxygen uptake (V̇O2max), the fractional utilisation of oxygen uptake (%V̇O2max) and running economy at lactate threshold (REOBLA). This study aims to assess maximal lactate accumulation rate (ċLamax) in terms of improving running performance prediction in trained athletes. Forty-four competitive female and male runners/triathletes performed an incremental step test, a 100-m sprint test and a ramp test to determine their metabolic profile. Stepwise linear regression was used to predict 5000-m time trial performance. Split times were recorded every 200-m to examine the ‘finishing kick’. Females had a slower t5k and a lower V̇O2max, ċLamax, ‘finishing kick’ and REOBLA. Augmenting Joyner’s model by means of ċLamax explained an additional 4.4% of variance in performance. When performing the same analysis exclusively for males, ċLamax was not included. ċLamax significantly correlated with %V̇O2max (r=-0.439, p=0.003) and the ‘finishing kick’ (r=0.389, p=0.010). ċLamax allows for significant (yet minor) improvements in 5000-m performance prediction in a mixed-sex group. This margin of improvement might differ in middle-distance events. Due to the relationship to the ‘finishing kick’, ċLamax might be related to individual pacing strategies, which should be assessed in future research.

Effects of Alternating Unilateral vs. Bilateral Resistance Training on Sprint and Endurance Cycling Performance in Trained Endurance Athletes: A 3-Armed, Randomized, Controlled, Pilot Trial

ABSTRACT

Ji, S, Donath, L, and Wahl, P. Effects of alternating unilateral vs. bilateral resistance training on sprint and endurance cycling performance in trained endurance athletes: A 3-armed, randomized, controlled, pilot trial. J Strength Cond Res 36(12): 3280-3289, 2022-Traditional preparatory resistance training for cyclists mainly relies on simultaneous bilateral movement patterns. This lack of movement specificity may impede transfer effects to specific aerobic and anaerobic requirements on the bike. Hence, this study investigated the effects of resistance training in alternating unilateral vs. simultaneous bilateral movement pattern on strength and anaerobic as well as aerobic cycling performance indices. Twenty-four trained triathletes and cyclists (age: 31.1 ± 8.1 years; V̇ o2 max: 57.6 ± 7.1 ml·min -1 ·kg -1 ) were randomly assigned to either an alternating unilateral (AUL), a simultaneous bilateral (BIL) training group or a control group (CON). Ten weeks of resistance training (4 × 4-10 repetition maximum) were completed by both training groups, although CON maintained their usual training regimen without resistance training. Maximal strength was tested during isometric leg extension, leg curl, and leg press in both unilateral and bilateral conditions. To compare the transfer effects of the training groups, determinants of cycling performance and time to exhaustion at 105% of the estimated anaerobic threshold were examined. Maximal leg strength notably increased in both training groups (BIL: ∼28%; AUL: ∼27%; p < 0.01) but not in CON (∼6%; p > 0.54). A significant improvement in cycling time trial performance was also observed in both training groups (AUL: 67%; BIL: 43%; p < 0.05) but not for CON (37%; p = 0.43). Bilateral group exhibited an improved cycling economy at submaximal intensities (∼8%; p < 0.05) but no changes occurred in AUL and CON (∼3%; p > 0.24). While sprint cycling performance decreased in CON (peak power: -6%; acceleration index: -15%; p < 0.05), improvement in favor of AUL was observed for acceleration abilities during maximal sprinting (20%; d = 0.5). Our pilot data underpin the importance of resistance training independent of its specific movement pattern both for improving the endurance cycling performance and maximal leg strength. Further research should corroborate our preliminary findings on whether sprint cycling benefits favorably from AUL resistance training.

Case Report: Training Monitoring and Performance Development of a Triathlete With Spinal Cord Injury and Chronic Myeloid Leukemia During a Paralympic Cycle

Introduction

Paratriathlon allows competition for athletes with various physical impairments. The wheelchair category stands out from other paratriathlon categories, since competing in swimming, handcycling, and wheelchair racing entails substantial demands on the upper extremity. Therefore, knowledge about exercise testing and training is needed to improve performance and avoid overuse injuries. We described the training monitoring and performance development throughout a Paralympic cycle of an elite triathlete with spinal cord injury (SCI) and a recent diagnosis of chronic myeloid leukemia (CML).

Case Presentation/Methods

A 30-year-old wheelchair athlete with 10-years experience in wheelchair basketball contacted us for guidance regarding testing and training in paratriathlon. Laboratory and field tests were modified from protocols used for testing non-disabled athletes to examine their physical abilities. In handcycling, incremental tests were used to monitor performance development by means of lactate threshold (P_OBLA) and define heart rate-based training zones. All-out sprint tests were applied to calculate maximal lactate accumulation rate (V˙Lamax) as a measure of glycolytic capabilities in all disciplines. From 2017 to 2020, training was monitored to quantify training load (TL) and training intensity distribution (TID).

Results

From 2016 to 2019, the athlete was ranked within the top ten at the European and World Championships. From 2017 to 2019, annual TL increased from 414 to 604 h and demonstrated a shift in TID from 77-17-6% to 88-8-4%. In this period, P_OBLA increased from 101 to 158 W and V˙Lamax decreased from 0.56 to 0.36 mmol·l⁻¹·s⁻¹. TL was highest during training camps. In 2020, after he received his CML diagnosis, TL, TID, and P_OBLA were 317 h, 94-5-1%, and 108 W, respectively.

Discussion

TL and TID demonstrated similar values when compared with previous studies in para-swimming and long-distance paratriathlon, respectively. In contrast, relative TL during training camps exceeded those described in the literature and was accompanied by physical stress. Increased volumes at low intensity are assumed to increase P_OBLA and decrease V˙Lamax over time. CML treatment and side effects drastically decreased TL, intensity, and performance, which ultimately hindered a qualification for Tokyo 2020/21. In conclusion, there is a need for careful training prescription and monitoring in wheelchair triathletes to improve performance and avoid non-functional overreaching.

High Energetic Demand of Elite Rowing - Implications for Training and Nutrition

Purpose: Elite rowers have large body dimensions, a high metabolic capacity, and they realize high training loads. These factors suggest a high total energy requirement (TER), due to high exercise energy expenditure (EEE) and additional energetic needs. We aimed to study EEE and intensity related substrate utilization (SU) of elite rowers during rowing (EEE_ROW) and other (EEE_NON-ROW) training.

Methods: We obtained indirect calorimetry data during incremental (N = 174) and ramp test (N = 42) ergometer rowing in 14 elite open-class male rowers (body mass 91.8 kg, 95% CI [87.7, 95.9]). Then we calculated EEE_ROW and SU within a three-intensity-zone model. To estimate EEE_NON-ROW, appropriate estimates of metabolic equivalents of task were applied. Based on these data, EEE, SU, and TER were approximated for prototypical high-volume, high-intensity, and tapering training weeks. Data are arithmetic mean and 95% confidence interval (95% CI).

Results: EEE_ROW for zone 1 to 3 ranged from 15.6 kcal·min⁻¹, 95% CI [14.8, 16.3] to 49.8 kcal·min⁻¹, 95% CI [48.1, 51.6], with carbohydrate utilization contributing from 46.4%, 95% CI [42.0, 50.8] to 100.0%, 95% CI [100.0, 100.0]. During a high-volume, a high-intensity, or a taper week, TER was estimated to 6,775 kcal·day⁻¹, 95% CI [6,651, 6,898], 5,772 kcal·day⁻¹, 95% CI [5,644, 5,900], or 4,626 kcal∙day⁻¹, 95% CI [4,481, 4,771], respectively.

Conclusion: EEE in elite open-class male rowers is remarkably high already during zone 1 training and carbohydrates are dominantly utilized, indicating relatively high metabolic stress even during low intensity rowing training. In high-volume training weeks, TER is presumably at the upper end of the sustainable total energy expenditure. Periodized nutrition seems warranted for rowers to avoid low energy availability, which might negatively impact performance, training, and health.

Racing and Training Physiology of an Elite Ultra-Endurance Cyclist: Case Study of 2 Record-Setting Performances

PURPOSE

To present a case report of an elite ultra-endurance cyclist, who was the winner and course record holder of 2 distinct races within a 4-month span: a 24-hour solo cycling race and a 2-man team multiday race (Race Across America).

METHODS

The athlete's raw data (cycling power, heart rate [HR], speed, and distance) were obtained and analyzed for 2 ultra-endurance races and 11 weeks of training in between.

RESULTS

For the 24-hour race, the athlete completed 861.6 km (average speed 35.9 km·h-1, average power 210 W [2.8 W·kg-1], average HR 121 beats per minute) with a 37% decrease in power and a 22% decrease in HR throughout the race. During the 11 weeks between the 24-hour race and Race Across America, training intensity distribution (Zone 1/2/3) based on HR was 51%/39%/10%. For the Race Across America, total team time to complete the 4939-km race was 6 days, 10 hours, 39 minutes, at an average speed of 31.9 km·h-1. Of this, the athlete featured in this case study rode 75.2 hours, completing 2532 km (average speed 33.7 km·h-1, average power 203 W [2.7 W·kg-1]), with a 12% decrease in power throughout the race. Power during daytime segments was greater than nighttime (212 [25] vs 189 [18] W, P < .001, ηp2=.189).

CONCLUSIONS

This case report highlights the performance requirements of elite ultra-endurance cycling. Although average power was similar when riding for 24 hours continuously and 75 hours intermittently over 6.5 days, there were large differences in pacing strategies and within-day power-output changes.

Maximal Lactate Accumulation Rate in All-out Exercise Differs between Cycling and Running

This study aims to compare maximal lactate accumulation rate (V̇ La_max) and power output (P_max) between cycling and running in terms of reliability, differences between, and correlations among modalities. Eighteen competitive triathletes performed a 15-s all-out exercise test in cycling and a 100-m sprint test in running. Each test was performed twice and separated by one week. Exercise tests in cycling were performed on an ergometer whereas sprint tests in running were performed on an indoor track. Differences between trials and exercise modality were analyzed using two-way ANOVA. V̇ La_max (ICC=0.894, ICC=0.868) and P_max (ICC=0.907, ICC=0.965) attained 'good' to 'excellent' reliability in both cycling and running, respectively. V̇ La_max was higher in running (d=0.709, p=0.016) whereas P_max was lower in running (d=-0.862, p < 0.001). For V̇ La_max, limits of agreement between modalities ranged from -0.224 to +0.437 mmol·l^-1·s^-1. P_max correlated between modalities (r=0.811, p < 0.001), whereas no correlation was found in V̇ La_max (r=0.418, p=0.084). V̇ La_max is highly reliable in both modalities and higher in running compared to cycling. Since V̇ La_max does not correlate between cycling and running, it should be determined sport-specifically.

Fractal Correlation Properties of Heart Rate Variability: A New Biomarker for Intensity Distribution in Endurance Exercise and Training Prescription?

Exercise and training prescription in endurance-type sports has a strong theoretical background with various practical applications based on threshold concepts. Given the challenges and pitfalls of determining individual training zones on the basis of subsystem indicators (e.g., blood lactate concentration, respiratory parameters), the question arises whether there are alternatives for intensity distribution demarcation. Considering that training in a low intensity zone substantially contributes to the performance outcome of endurance athletes and exceeding intensity targets based on a misleading aerobic threshold can lead to negative performance and recovery effects, it would be desirable to find a parameter that could be derived via non-invasive, low cost and commonly available wearable devices. In this regard, analytics conducted from non-linear dynamics of heart rate variability (HRV) have been adapted to gain further insights into the complex cardiovascular regulation during endurance-type exercise. Considering the reciprocal antagonistic behavior and the interaction of the sympathetic and parasympathetic branch of the autonomic nervous system from low to high exercise intensities, it may be promising to use an approach that utilizes information about the regulation quality of the organismic system to determine training-intensity distribution. Detrended fluctuation analysis of HRV and its short-term scaling exponent alpha1 (DFA-alpha1) seems suitable for applied sport-specific settings including exercise from low to high intensities. DFA-alpha1 may be taken as an indicator for exercise prescription and intensity distribution monitoring in endurance-type sports. The present perspective illustrates the potential of DFA-alpha1 for diagnostic and monitoring purposes as a “global” system parameter and proxy for organismic demands.

Power profile, physiological characteristics and their correlation in elite canoe polo players

BACKGROUND

This study aimed to examine the physical capabilities of elite canoe polo players and to identify interrelationships between anthropometric or physiological characteristics and performance on a kayak ergometer.

METHODS

Eight male participants (age 24.6±4.8 years, weight 84.1±5.3 kg, height 180.0±5.9 cm) completed four all-out time trials (15 s, 180 s, 420 s, 900 s) to determine peak power output (PPO), mean power output (MPO), maximal oxygen uptake (VO<inf>2max</inf>), maximal rate of lactate accumulation (VLa<inf>max</inf>), and maximal lactate steady-state (cMLSS). Critical power (CP) and work that can be performed above CP (W') were assessed using a linear power model. Further, the 30-second end-test power (EP) and work done above EP (WEP) were derived from the 180 s time trial. Finally, indices were calculated from the metabolic and power data. The level of significance was set at P≤0.05.

RESULTS

Weak to moderate correlations were found for body weight and height compared to PPO and MPOs. VO<inf>2max</inf> correlated strongly with MPO180 and MPO420. VLa<inf>max</inf> correlated moderately with PPO and MPO15. While the calculations of CP, EP, and cMLSS correlated moderately to strongly, their means differed significantly. W' and WEP also differed significantly with a mean difference of 10.2±2.5 kJ.

CONCLUSIONS

Canoe polo players are similar to sprint paddlers in their constitution, although VO<inf>2max</inf> and PPO are lower. The high correlation between physiological and power parameters also shows that simple tests that do not require blood or gas sampling can be established quickly in daily training practice.

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.

Maximal lactate accumulation rate and post-exercise lactate kinetics in handcycling and cycling

The aim of this study was to assess lactate kinetics, maximal lactate accumulation rate (⩒La_max) and peak power output (PO_max) in a 15-s all-out exercise in handcycling (HC) and cycling (C) in terms of (1) reliability, (2) differences and (3) correlations between HC and C. Eighteen female and male competitive triathletes performed two trials (separated by one week) of a 15-s all-out sprint test in HC and C. Tests were performed in a recumbent racing handcycle and on the participants' own road bike that were attached to an ergometer. Reliability was assessed using intraclass correlation coefficient (ICC). PO_max and ⩒La_max demonstrated high reliability in HC (ICC = 0.972, ICC = 0.828) and C (ICC = 0.937, ICC = 0.872). PO_max (d = -2.54, P < 0.0005) and ⩒La_max (d = -1.62, P < 0.0005) were lower in HC compared to C. PO_max and ⩒La_max correlated in HC (r = 0.729, P = 0.001) and C (r = 0.710, P = 0.001). There was no significant correlation between HC and C in PO_max (r = 0.442, P = 0.066) and ⩒La_max (r = 0.455, P = 0.058). Whereas the exchange velocity of lactate (k₁) was similar in HC and C, the removal velocity (k₂) was significantly higher in HC. ⩒La_max and PO_max during sprint exercise are highly reliable and demonstrate a correlation in both HC and C. However, since ⩒La_max and PO_max are significantly higher in C and not correlated between HC and C, ⩒La_max and PO_max seem to be extremity-specific.

Evaluation of a sport-specific field test to determine maximal lactate accumulation rate and sprint performance parameters in running

OBJECTIVES

The aim of this study was to examine the reliability of maximal lactate accumulation rate (V˙La_max) and sprint performance parameters in running and assess different approaches to determine alactic time interval (t_alac).

DESIGN

Sixteen competitive runners (female=5; male=11) performed three trials (T1, T2 and T3) of an all-out 100-m sprint test separated by 48h.

METHODS

Time to cover the 100m was determined by using a photoelectric light-barrier (t_100,LB) and a stop-watch (t_100,SW). Throughout the sprints, velocity was measured using a laser velocity guard (LAVEG) to estimate maximal velocity (v_max) and power (P_max). The t_alac was calculated as the time when power decreased by 3.5% (t_pmax-3.5%) and interpolated based on the sprint time (t_inter,LB and t_inter,SW). Reliability was assessed using intraclass correlation coefficient (ICC), typical error (TE) and smallest worthwhile change (SWC).

RESULTS

After initial familiarisation, t₁₀₀, t_inter, v_max, P_max and V˙La_max attained excellent reliability (ICC≥0.90), whereas t_pmax-3.5% attained moderate reliability (ICC=0.518). The reliability of V˙La_max was higher when t_inter,LB or t_inter,SW were used (ICC=0.960) compared to using t_pmax-3.5% (ICC=0.928). At T1, V˙La_max was significantly higher when stop-watch measurements were used. There was no difference between t_pmax-3.5% and the interpolated time intervals and the associated V˙La_max-estimates.

CONCLUSIONS

In running, V˙La_max and sprint performance parameters can easily and high-reliably be measured using this sport-specific field test. Interpolating t_alac results in similar and more reliable values of V˙La_max. To improve the reliability and accuracy of the stop-watch estimate, a familiarisation should be performed.

The Training Characteristics of the World's Most Successful Female Cross-Country Skier

The main aim of this study was to investigate the training characteristics of the most successful female cross-country skier ever during the best period of her career. The participant won six gold medals at the Olympic Games, 18 gold medals at the World Championship, and 110 World Cup victories. Day-to-day training diary data, interviews, and physiological tests were analyzed. Training data was systemized by training form (endurance, strength, and speed), intensity [low- (LIT), moderate- (MIT), and high-intensity training (HIT)], and mode (running, cycling, and skiing/roller skiing), followed by a division into different periodization phases. Specific sessions utilized in the various periodization periods and the day-to-day periodization of training, in connection with altitude camps and tapering toward major championships, were also analyzed. Following a 12-year nonlinear increase in training load, the annual training volume during the five consecutive successful years stabilized at 937 ± 25 h, distributed across 543 ± 9 sessions. During these 5 years, total training time was distributed as 90.6% endurance-, 8.0% strength-, and 1.4% speed-training, with endurance-training time consisting of 92.3 ± 0.3% LIT, 2.9 ± 0.5% MIT, and 4.8 ± 0.5% HIT. Total LIT-time consisted of 21% warm-up, 14% sessions <90 min, and 65% long-duration sessions >90 min. While the total number of LIT sessions remained stable across phases (32 sessions), total LIT-time was reduced from GP (76 h/month) to SP (68 h/month) and CP (55 h/month). MIT-time decreased from GP (2.8 h/month) to SP (2.2 h/month) and CP (1 h/month). HIT-time increased from GP (2.8 h/month) to SP (3.2 h/month) and CP (4.7 h/month). Altitude training accounted for 18-25% of annual training volume and performed across relatively short training camps (≤16 days) with a clear reduction of HIT training, but increased total and LIT volume compared to sea-level training. Training before international championships included a 2-week increase in LIT and strength volume followed by a gradual reduction of training volume and increased HIT during the last week. This study provides unique data on the world's most successful female cross-country skier's long-term training process, including novel information about the distribution of and interplay between sessions of different forms, intensities, and exercise modes throughout the annual season.

The Lactate Minimum Test: Concept, Methodological Aspects and Insights for Future Investigations in Human and Animal Models

In 1993, Uwe Tegtbur proposed a useful physiological protocol named the lactate minimum test (LMT). This test consists of three distinct phases. Firstly, subjects must perform high intensity efforts to induce hyperlactatemia (phase 1). Subsequently, 8 min of recovery are allowed for transposition of lactate from myocytes (for instance) to the bloodstream (phase 2). Right after the recovery, subjects are submitted to an incremental test until exhaustion (phase 3). The blood lactate concentration is expected to fall during the first stages of the incremental test and as the intensity increases in subsequent stages, to rise again forming a “U” shaped blood lactate kinetic. The minimum point of this curve, named the lactate minimum intensity (LMI), provides an estimation of the intensity that represents the balance between the appearance and clearance of arterial blood lactate, known as the maximal lactate steady state intensity (iMLSS). Furthermore, in addition to the iMLSS estimation, studies have also determined anaerobic parameters (e.g., peak, mean, and minimum force/power) during phase 1 and also the maximum oxygen consumption in phase 3; therefore, the LMT is considered a robust physiological protocol. Although, encouraging reports have been published in both human and animal models, there are still some controversies regarding three main factors: (1) the influence of methodological aspects on the LMT parameters; (2) LMT effectiveness for monitoring training effects; and (3) the LMI as a valid iMLSS estimator. Therefore, the aim of this review is to provide a balanced discussion between scientific evidence of the aforementioned issues, and insights for future investigations are suggested. In summary, further analyses is necessary to determine whether these factors are worthy, since the LMT is relevant in several contexts of health sciences.