Polarized Training Is Optimal for Endurance Athletes

Training for Elite Team-Pursuit Track Cyclists-Part II: A Comparison of Preparation Phases in Consecutive World-Record-Breaking Seasons

PURPOSE

To compare the training characteristics of an elite team pursuit cycling squad in the 3-month preparation phases prior to 2 successive world-record (WR) performances.

METHODS

Training data of 5 male track endurance cyclists (mean [SD]; age 23.4 [3.46] y; body mass 80.2 [2.74] kg; 4.5 [0.17] W·kg-1 at LT2; maximal aerobic power 6.2 [0.27] W·kg-1; maximal oxygen uptake 65.9 [2.89] mL·kg-1·min-1) were analyzed with weekly total training volume by training type and heart rate, power output, and torque intensity distributions calculated with reference to the respective WRs' performance requirements.

RESULTS

Athletes completed 805 (82.81) and 725 (68.40) min·wk-1 of training, respectively, in each season. In the second season, there was a 32% increase in total track volume, although track sessions were shorter (ie, greater frequency) in the second season. A pyramidal intensity distribution was consistent across both seasons, with 81% of training, on average, performed below LT1 power output each week, whereas 6% of training was performed above LT2. Athletes accumulated greater volume above WR team pursuit lead power (2.4% vs 0.9%) and torque (6.2% vs 3.2%) in 2019. In one athlete, mean single-leg-press peak rate of force development was 71% and 46% higher at mid- and late-phases, respectively, during the preparation period.

CONCLUSIONS

These findings provide novel insights into the common and contrasting methods contributing to successive WR team pursuit performances. Greater accumulation of volume above race-specific power and torque (eg, team pursuit lead), as well as improved neuromuscular force-generating capacities, may be worthy of investigation for implementation in training programs.

Training for Elite Team-Pursuit Track Cyclists-Part I: A Profile of General Training Characteristics

PURPOSE

To profile the training characteristics of an elite team pursuit cycling squad and assess variations in training intensity and load accumulation across the 36-week period prior to a world-record performance at the 2018 Commonwealth Games.

METHODS

Training data of 5 male track endurance cyclists (mean [SD]; age 21.9 [3.52] y; 4.4 [0.16] W·kg-1 at anaerobic threshold; 6.2 [0.28] W·kg-1 maximal oxygen uptake 68.7 [2.99] mL kg·min-1) were analyzed with weekly total training volume and heart rate, power output, and torque intensity distributions calculated with reference to their 3:49.804 min:s.ms performance requirements for a 4-km team pursuit.

RESULTS

Athletes completed 543 (37) h-1 of training across 436 (16) sessions. On-bike activities accounted for 69.9% of all training sessions, with participants cycling 11,246 (1139) km-1 in the training period of interest, whereas 12.7% of sessions involved gym/strength training. A pyramidal intensity distribution was evident with over 65% and 70% of training, respectively, performed at low-intensity zone heart rate and power output, whereas 5.3% and 7.7% of training was performed above anaerobic threshold. The athletes accumulated 4.4% of total training volume at, or above, their world-record team pursuit lead position torque (55 N·m).

CONCLUSIONS

These data provide updated and novel insight to the power and torque demands and load accumulation contributing to world-record team pursuit performance. Although the observed pyramidal intensity distribution is common in endurance sports, the lack of shift toward a polarized intensity distribution during taper and competition peaking differs from previous research.

Molecular aspects of the exercise response and training adaptation in skeletal muscle

Skeletal muscle plasticity enables an enormous potential to adapt to various internal and external stimuli and perturbations. Most notably, changes in contractile activity evoke a massive remodeling of biochemical, metabolic and force-generating properties. In recent years, a large number of signals, sensors, regulators and effectors have been implicated in these adaptive processes. Nevertheless, our understanding of the molecular underpinnings of training adaptation remains rudimentary. Specifically, the mechanisms that underlie signal integration, output coordination, functional redundancy and other complex traits of muscle adaptation are unknown. In fact, it is even unclear how stimulus-dependent specification is brought about in endurance or resistance exercise. In this review, we will provide an overview on the events that describe the acute perturbations in single endurance and resistance exercise bouts. Furthermore, we will provide insights into the molecular principles of long-term training adaptation. Finally, current gaps in knowledge will be identified, and strategies for a multi-omic and -cellular analyses of the molecular mechanisms of skeletal muscle plasticity that are engaged in individual, acute exercise bouts and chronic training adaptation discussed.

Training Intensity Distribution of a 7-Day HIIT Shock Microcycle: Is Time in the "Red Zone" Crucial for Maximizing Endurance Performance? A Randomized Controlled Trial

BACKGROUND

Various studies have shown that the type of intensity measure affects training intensity distribution (TID) computation. These conclusions arise from studies presenting data from meso- and macrocycles, while microcycles, e.g., high-intensity interval training shock microcycles (HIIT-SM) have been neglected so far. Previous literature has suggested that the time spent in the high-intensity zone, i.e., zone 3 (Z3) or the "red zone", during HIIT may be important to achieve improvements in endurance performance parameters. Therefore, this randomized controlled trial aimed to compare the TID based on running velocity (TIDV), running power (TIDP) and heart rate (TIDHR) during a 7-day HIIT-SM. Twenty-nine endurance-trained participant were allocated to a HIIT-SM consisting of 10 HIIT sessions without (HSM, n = 9) or with (HSM + LIT, n = 9) additional low-intensity training or a control group (n = 11). Moreover, we explored relationships between time spent in Z3 determined by running velocity (Z3V), running power (Z3P), heart rate (Z3HR), oxygen uptake ( Z 3 V ˙ O 2 ) and changes in endurance performance.

RESULTS

Both intervention groups revealed a polarized pattern for TIDV (HSM: Z1: 38 ± 17, Z2: 16 ± 17, Z3: 46 ± 2%; HSM + LIT: Z1: 59 ± 18, Z2: 14 ± 18, Z3: 27 ± 2%) and TIDP (Z1: 50 ± 8, Z2: 14 ± 11, Z3: 36 ± 7%; Z1: 62 ± 15, Z2: 12 ± 16, Z3: 26 ± 2%), while TIDHR (Z1: 48 ± 13, Z2: 26 ± 11, Z3: 26 ± 7%; Z1: 65 ± 17, Z2: 22 ± 18, Z3: 13 ± 4%) showed a pyramidal pattern. Time in Z3HR was significantly less compared to Z3V and Z3P in both intervention groups (all p < 0.01). There was a time x intensity measure interaction for time in Z3 across the 10 HIIT sessions for HSM + LIT (p < 0.001, pη2 = 0.30). Time in Z3V and Z3P within each single HIIT session remained stable over the training period for both intervention groups. Time in Z3HR declined in HSM from the first (47%) to the last (28%) session, which was more pronounced in HSM + LIT (45% to 16%). A moderate dose-response relationship was found for time in Z3V and changes in peak power output (rs = 0.52, p = 0.028) as well as time trial performance (rs = - 0.47, p = 0.049) with no such associations regarding time in Z3P, Z3HR, and Z 3 V ˙ O 2 .

CONCLUSION

The present study reveals that the type of intensity measure strongly affects TID computation during a HIIT-SM. As heart rate tends to underestimate the intensity during HIIT-SM, heart rate-based training decisions should be made cautiously. In addition, time in Z3V was most closely associated with changes in endurance performance. Thus, for evaluating a HIIT-SM, we suggest integrating a comprehensive set of intensity measures. Trial Registration Trial register: Clinicaltrials.gov, registration number: NCT05067426.

ChatGPT Generated Training Plans for Runners are not Rated Optimal by Coaching Experts, but Increase in Quality with Additional Input Information

ChatGPT may be used by runners to generate training plans to enhance performance or health aspects. However, the quality of ChatGPT generated training plans based on different input information is unknown. The objective of the study was to evaluate ChatGPT-generated six-week training plans for runners based on different input information granularity. Three training plans were generated by ChatGPT using different input information granularity. 22 quality criteria for training plans were drawn from the literature and used to evaluate training plans by coaching experts on a 1-5 Likert Scale. A Friedmann test assessed significant differences in quality between training plans. For training plans 1, 2 and 3, a median rating of <3 was given 19, 11, and 1 times, a median rating of 3 was given 3, 5, and 8 times and a median rating of >3 was given 0, 6, 13 times, respectively. Training plan 1 received significantly lower ratings compared to training plan 2 for 3 criteria, and 15 times significantly lower ratings compared to training plan 3 (p < 0.05). Training plan 2 received significantly lower ratings (p < 0.05) compared to plan 3 for 9 criteria. ChatGPT generated plans are ranked sub-optimally by coaching experts, although the quality increases when more input information are provided. An understanding of aspects relevant to programming distance running training is important, and we advise avoiding the use of ChatGPT generated training plans without an expert coach's feedback.

Effects of a 16-Week Training Program with a Pyramidal Intensity Distribution on Recreational Male Cyclists

Different training intensity distributions (TIDs) have been proposed to improve cycling performance, especially for high-competition athletes. The objectives of this study were to analyze the effect of a 16-week pyramidal training intensity distribution on somatic and power variables in recreational cyclists and to explore the training zone with the greatest impact on performance improvement. The sample consisted of 14 male recreational cyclists aged 41.00 ± 7.29 years of age. A number of somatic variables were measured. During an incremental protocol, power at a 4 mMol·L-1 blood lactate concentration (P4), corresponding power to body mass ratio (P/W P4), and heart rate (HR P4) were also measured. Among the somatic variables, the percentage of fat mass showed the greatest improvement between moments (p < 0.001, d = 0.52). Both P4 (p < 0.001, d = 1.21) and P/W P4 (p < 0.001, d = 1.54) presented a significant increase between moments. The relative improvement in P4 (% P4) showed a significant correlation (Rs = 0.661, p = 0.038) and relationship (R2 = 0.61, p = 0.008) mainly with training zone Z2 (blood lactate levels ≥ 2 and <4 mMol·L-1). It seems that spending more time in Z2 promoted an improvement in both somatic and power variables in recreational cyclists.

A Perspective on High-Intensity Interval Training for Performance and Health

Interval training is a simple concept that refers to repeated bouts of relatively hard work interspersed with recovery periods of easier work or rest. The method has been used by high-level athletes for over a century to improve performance in endurance-type sports and events such as middle- and long-distance running. The concept of interval training to improve health, including in a rehabilitative context or when practiced by individuals who are relatively inactive or deconditioned, has also been advanced for decades. An important issue that affects the interpretation and application of interval training is the lack of standardized terminology. This particularly relates to the classification of intensity. There is no common definition of the term "high-intensity interval training" (HIIT) despite its widespread use. We contend that in a performance context, HIIT can be characterized as intermittent exercise bouts performed above the heavy-intensity domain. This categorization of HIIT is primarily encompassed by the severe-intensity domain. It is demarcated by indicators that principally include the critical power or critical speed, or other indices, including the second lactate threshold, maximal lactate steady state, or lactate turnpoint. In a health context, we contend that HIIT can be characterized as intermittent exercise bouts performed above moderate intensity. This categorization of HIIT is primarily encompassed by the classification of vigorous intensity. It is demarcated by various indicators related to perceived exertion, oxygen uptake, or heart rate as defined in authoritative public health and exercise prescription guidelines. A particularly intense variant of HIIT commonly termed "sprint interval training" can be distinguished as repeated bouts performed with near-maximal to "all out" effort. This characterization coincides with the highest intensity classification identified in training zone models or exercise prescription guidelines, including the extreme-intensity domain, anaerobic speed reserve, or near-maximal to maximal intensity classification. HIIT is considered an essential training component for the enhancement of athletic performance, but the optimal intensity distribution and specific HIIT prescription for endurance athletes is unclear. HIIT is also a viable method to improve cardiorespiratory fitness and other health-related indices in people who are insufficiently active, including those with cardiometabolic diseases. Research is needed to clarify responses to different HIIT strategies using robust study designs that employ best practices. We offer a perspective on the topic of HIIT for performance and health, including a conceptual framework that builds on the work of others and outlines how the method can be defined and operationalized within each context.

From juniors to seniors: changes in training characteristics and aerobic power in 17 world-class cross-country skiers

Purpose: To compare training characteristics and aerobic power (VO2max) between the most successful junior and senior seasons of world-class cross-country (XC) skiers and to identify differences between sexes and among sprint and distance skiers. Methods: Retrospective analysis was conducted on self-reported training and VO2max tests of ten male and seven female world-class XC-skiers, collectively holding 38 Olympic medals. Training was categorized by form (endurance, strength, speed, other) and mode (specific, unspecific) and was divided into low- (LIT), moderate- (MIT), and high-intensity training (HIT). Results: Total training increased by 203 ± 130 h (35% ± 31%, p < .001, large effect) and 78 ± 69 sessions (21% ± 24%, p < .001, very large effect). Junior training volume (658 ± 107 h) did not correlate with senior volume (861 ± 74 h) but correlated negatively with changes in volume (r = -.822, p < .001). No sex differences were observed related to total volume, but distance skiers increased their total volume more than sprint skiers (p = .037, large effect). Endurance training increased by 197 ± 117 h (p < .001; large effect) tied to increased low-intensity training (186 ± 115 h, p < .001; large effect) and moderate-intensity training (13 ± 7 h, p < .001; large effect). Training intensity distribution (% LIT/MIT/HIT) was 91/3/6 in junior and 92/4/4 in senior season. Women demonstrated greater increase of unspecific modes (100 ± 58 vs. 37 ± 44 h, p = .022; large effect) and strength training (25 ± 23 vs. -3 ± 17 h, p = .010, large effect). Men improved absolute (8% ± 5%; p = .009; large effect) and relative VO2max (6% ± 4%; p = .016; large effect) from junior to senior, while women only increased relative VO2max (7% ± 5%, p = .012; large effect). Conclusion: This study provides novel information regarding changes in training characteristics and aerobic power from junior to senior age in world-class XC-skiers. Overall, the enhanced training volume during this transition was primarily driven by increased LIT and MIT and the exceptionally high relative VO2max at junior age further increased in both sexes.

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.

Long-Term Development of Training Characteristics and Performance-Determining Factors in Elite/International and World-Class Endurance Athletes: A Scoping Review

OBJECTIVE

In this scoping review, we aimed to 1) identify and evaluate existing research that describes the long-term development of training characteristics and performance-determining factors in male and female endurance athletes reaching an elite/international (Tier 4) or world-class level (Tier 5), 2) summarize the available evidence and 3) point out existing knowledge gaps and provide methodological guidelines for future research in this field.

METHODS

This review was conducted following the Joanna Briggs Institute methodology for scoping reviews.

RESULTS

Out of 16772 screened items across a 22-year period (1990-2022), a total of 17 peer-reviewed journal articles met the inclusion criteria and were considered for further analysis. These 17 studies described athletes from seven different sports and seven different countries, with 11 (69%) of the studies being published during the last decade. Of the 109 athletes included in this scoping review, one quarter were women (27%), and three quarters were men (73%). Ten studies included information about the long-term development of training volume and training intensity distribution. A non-linear, year-to-year increase in training volume was found for most athletes, resulting in a subsequent plateau. Furthermore, 11 studies described the development of performance determining factors. Here, most of the studies showed improvements in submaximal variables (e.g., lactate/anaerobic threshold and work economy/efficiency) and maximal performance-indices (e.g., peak speed/watt during performance testing). Conversely, the development of VO2max was inconsistent across studies. No evidence was found regarding possible sex differences in development of training or performance-determining factors among endurance athletes.

CONCLUSION

Overall, a low number of studies describing the long-term development of training and performance-determining factors is available. This suggests that existing talent development practices in endurance sports are built upon limited scientific evidence. Overall, there is an urgent need for additional long-term studies based on systematic monitoring of athletes from a young age utilizing high-precision, reproducible measurements of training and performance-determining factors.

Effect of Polarized Training on Cardiorespiratory Fitness of Untrained Healthy Young Adults: A Randomized Control Trial with Equal Training Impulse

To explore the effects of 8-week polarized training (POL), high-intensity interval training (HIIT), and threshold training (THR) interventions on the cardiorespiratory fitness (CRF) of untrained healthy young adults. This study recruited 36 young adults and randomly assigned them to POL, HIIT, THR, or control (CG) groups to undergo an 8-week training intervention. The training impulse applied to all three intervention groups was identical. The training intensity was divided into Zone 1, 2, and 3 (Z1, Z2 and Z3) on the basis of the ventilatory thresholds (VT). The weekly training intensity distribution for POL was 75% of Z1 and 25% of Z3; HIIT was 100% of Z3 and THR was 50% of Z1 and 50% of Z2. Each group underwent Bruce protocol testing and supramaximal testing before, during, and after the intervention; relevant CRF parameters were assessed. 8 weeks of POL and HIIT significantly increased VT2 (p < 0.05); 8 weeks of POL, HIIT, THR and significantly increased VO2max and TTE (p < 0.05). The effect size of POL in relation to VO2max and TTE improvements was greater than that of HIIT and THR (g = 2.67 vs. 1.26 and 1.49; g = 2.75 vs. 2.05 and 1.60). Aerobic training models with different intensity distributions have different time effects on improving CRF. Relative to HIIT and THR, POL improved more variables of CRF. Therefore, POL is a feasible aerobic training method for improving CRF.

Effects of plyometric training on different 8-week training intensity distributions in well-trained endurance runners

The aim of this four-armed parallel group randomized-controlled trial was to evaluate if plyometric training could have different effects on running performance and physiological adaptations depending on the training intensity distribution (TID) in an 8-week intervention in endurance athletes. Sixty well-trained male runners (age: 34 ± 6 years, relative ⩒O_2peak : 69 ± 3 ml kg^-1  min^-1 ) were recruited and allocated to a pyramidal (PYR), pyramidal + plyometric training (PYR + PLY), polarized (POL), and polarized + plyometric training (POL + PLY) periodization. The periodization patterns were isolated manipulations of TID, while training load was kept constant. Participants were tested pre- and post-intervention for body mass, velocity at 2 and 4 mmol·L^-1 of blood lactate concentration (vBLa2, vBLa4), absolute and relative ⩒O_2peak and 5-km running time trial performance, counter movement jump and squat jump. There were significant group × time interactions for vBla4 (p = 0.0235), CMJ (p = 0.0234), SJ (p = 0.0168), and 5-km running time trial performance (p = 0.0035). Specifically, vBla4 and 5-km running time trial performance showed the largest post-intervention improvements in PYR + PLY (2.4% and 1.6%) and POL + PLY (2.1% and 1.8%), respectively. No significant interactions were observed for body mass, absolute and relative ⩒O_2peak , peak heart rate, lactate peak and rating of perceived exertion. In conclusion, an 8-week training periodization seems to be effective in improving performance of well-trained endurance runners. Including plyometric training once a week appeared to be more efficacious in maximizing running performance improvements, independently from the TID adopted.

Does Lactate-Guided Threshold Interval Training within a High-Volume Low-Intensity Approach Represent the "Next Step" in the Evolution of Distance Running Training?

The aim of the present study was to describe a novel training model based on lactate-guided threshold interval training (LGTIT) within a high-volume, low-intensity approach, which characterizes the training pattern in some world-class middle- and long-distance runners and to review the potential physiological mechanisms explaining its effectiveness. This training model consists of performing three to four LGTIT sessions and one VO2max intensity session weekly. In addition, low intensity running is performed up to an overall volume of 150-180 km/week. During LGTIT sessions, the training pace is dictated by a blood lactate concentration target (i.e., internal rather than external training load), typically ranging from 2 to 4.5 mmol·L-1, measured every one to three repetitions. That intensity may allow for a more rapid recovery through a lower central and peripheral fatigue between high-intensity sessions compared with that of greater intensities and, therefore, a greater weekly volume of these specific workouts. The interval character of LGTIT allows for the achievement of high absolute training speeds and, thus, maximizing the number of motor units recruited, despite a relatively low metabolic intensity (i.e., threshold zone). This model may increase the mitochondrial proliferation through the optimization of both calcium and adenosine monophosphate activated protein kinase (AMPK) signaling pathways.

Training Periodization, Intensity Distribution, and Volume in Trained Cyclists: A Systematic Review

A well-planned periodized approach endeavors to allow road cyclists to achieve peak performance when their most important competitions are held.

PURPOSE

To identify the main characteristics of periodization models and physiological parameters of trained road cyclists as described by discernable training intensity distribution (TID), volume, and periodization models.

METHODS

The electronic databases Scopus, PubMed, and Web of Science were searched using a comprehensive list of relevant terms. Studies that investigated the effect of the periodization of training in cyclists and described training load (volume, TID) and periodization details were included in the systematic review.

RESULTS

Seven studies met the inclusion criteria. Block periodization (characterized by employment of highly concentrated training workload phases) ranged between 1- and 8-week blocks of high-, medium-, or low-intensity training. Training volume ranged from 8.75 to 11.68 h·wk-1 and both pyramidal and polarized TID were used. Traditional periodization (characterized by a first period of high-volume/low-intensity training, before reducing volume and increasing the proportion of high-intensity training) was characterized by a cyclic progressive increase in training load, the training volume ranged from 7.5 to 10.76 h·wk-1, and pyramidal TID was used. Block periodization improved maximum oxygen uptake (VO2max), peak aerobic power, lactate, and ventilatory thresholds, while traditional periodization improved VO2max, peak aerobic power, and lactate thresholds. In addition, a day-by-day programming approach improved VO2max and ventilatory thresholds.

CONCLUSIONS

No evidence is currently available favoring a specific periodization model during 8 to 12 weeks in trained road cyclists. However, few studies have examined seasonal impact of different periodization models in a systematic way.

The Training Characteristics of World-Class Distance Runners: An Integration of Scientific Literature and Results-Proven Practice

In this review we integrate the scientific literature and results-proven practice and outline a novel framework for understanding the training and development of elite long-distance performance. Herein, we describe how fundamental training characteristics and well-known training principles are applied. World-leading track runners (i.e., 5000 and 10,000 m) and marathon specialists participate in 9 ± 3 and 6 ± 2 (mean ± SD) annual competitions, respectively. The weekly running distance in the mid-preparation period is in the range 160–220 km for marathoners and 130–190 km for track runners. These differences are mainly explained by more running kilometers on each session for marathon runners. Both groups perform 11–14 sessions per week, and ≥ 80% of the total running volume is performed at low intensity throughout the training year. The training intensity distribution vary across mesocycles and differ between marathon and track runners, but common for both groups is that volume of race-pace running increases as the main competition approaches. The tapering process starts 7–10 days prior to the main competition. While the African runners live and train at high altitude (2000–2500 m above sea level) most of the year, most lowland athletes apply relatively long altitude camps during the preparation period. Overall, this review offers unique insights into the training characteristics of world-class distance runners by integrating scientific literature and results-proven practice, providing a point of departure for future studies related to the training and development in the Olympic long-distance events.

Elite versus non-elite cyclist - Stepping up to the international/elite ranks from U23 cycling

This study investigated the physiological, performance and training characteristics of U23 cyclists and assessed the requirements of stepping up to the elite/international ranks. Twenty highly trained U23 cyclists (age, 22.1 ± 0.8 years; body mass, 69.1 ± 6.8 kg; VO_2max, 76.1 ± 3.9 ml·kg^-1·min^-1) participated in this study. The cyclists were a posteriori divided into two groups based on whether or not they stepped up to elite/international level cycling (U23_ELITE vs. U23_NON-ELITE). Physiological, performance and training and racing characteristics were determined and compared between groups. U23_ELITE demonstrated higher absolute peak power output (p = .016), 2 min (p = .026) 5 min (p = .042) and 12 min (p ≤ .001) power output as well as higher absolute critical power (p = .002). Further, U23_ELITE recorded more accumulated hours (p ≤ .001), covered distance (p ≤ .001), climbing metres (p ≤ .001), total sessions (p ≤ .001), total work (p ≤ .001) and scored more UCI points (p ≤ .001). These findings indicate that U23_ELITE substantially differed from U23_NON-ELITE regarding physiological, performance and training and racing characteristics derived from laboratory and field. These variables should be considered by practitioners supporting young cyclists throughout their development towards the elite/international ranks.

Simple Approach to Defining Training Intensity in Endurance Runners

Training intensity distribution is important to training program design. The zones 1 to 2 boundary can be defined by the Talk Test and the rating of perceived exertion. The zones 2 to 3 boundary can be defined by respiratory gas exchange, maximal lactate steady state, or, more simply, by critical speed (CS). The upper boundary of zone 3 is potential defined by the velocity at maximum oxygen uptake (vVO2max), although no clear strategy has emerged to categorize this intensity. This is not normally definable outside the laboratory.

PURPOSE

This study predicts vVO2max from CS, determined from 1 (1.61 km) and 2 (3.22 km) citizen races in well-trained runners.

METHODS

A heterogeneous group of well-trained runners (N = 22) performed 1- and 2-mile races and were studied during submaximal and maximal treadmill running to measure oxygen uptake, allowing computation of vVO2max. This vVO2max was compared with CS.

RESULTS

vVO2max (4.82 [0.53] m·s-1) was strongly correlated with CS (4.37 [0.49] m·s-1; r = .84, standard error of estimate [SEE] = 0.132 m·s-1), 1-mile speed (5.09 [0.51] m·s-1; r = .84, SEE = 0.130 m·s-1), and 2-mile speed (4.68 [0.49] m·s-1; r = .86, SEE = 0.120 m·s-1).

CONCLUSIONS

CS, calculated from 2 citizen races (or even training time trials), can be used to make reasonable estimates of vVO2max, which can be used in the design of running training programs.