Training Intensity Distribution Research Articles

Anthropometric Characteristics, Training Intensity Distribution, Physiological Profile and Performance of an Elite Trail Runner: A Longitudinal Case Study

Anthropometric Characteristics, Training Intensity Distribution, Physiological Profile and Performance of an Elite Trail Runner: A Longitudinal Case Study

Training Characteristics, Performance, and Body Composition of Three U23 Elite Female Triathletes throughout a Season.

(1) Background: There is a lack of data on the long-term training characteristics and performance markers of elite young female endurance athletes. The aim of this study was to present the training load (ECOs), as well as the evolution of the anthropometric values and performance of three elite U23 female triathletes over a season. (2) Methods: General training data and performance data relating to the swimming, cycling, and running legs of the 2021 season were described. The training intensity distribution (TID) was presented using the triphasic model, while the training load was based on the ECO model. An anthropometric analysis was also conducted in accordance with the ISAK standards. (3) Results: Triathletes increased their VO2max in cycling (6.9-10%) and running (7.1-9.1%), as well as their power and speed associated with the VO2max (7.7-8.6% in cycling and 5.1-5.3% in running) and their swimming speed associated with the lactate thresholds (2.6-4.0% in LT2 and 1.2-2.5% in LT1). The triathletes completed more than 10 h of weekly average training time, with peak weeks exceeding 15 h. The average TID of the three triathletes was 82% in phase 1, 6% in phase 2, and 12% in phase 3. A decrease in the sum of skinfolds and fat mass percentage was observed during the season in the three triathletes, although the last measurement revealed a stagnation or slight rise in these parameters. (4) Conclusions: The triathletes performed a combination of two training periodization models (traditional and block periodization) with a polarized TID in most of the weeks of the season. Improvements in performance and physiological parameters were observed after the general preparatory period as well as a positive body composition evolution throughout the season, except at the end, where the last measurement revealed stagnation or a slight decline. This study can be useful as a general guide for endurance coaches to organize a training season with female U23 triathletes.

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.

Polarized training intensity distribution in distance running

In this case study, we analysed the online available one-year training diary of a long-distance runner participating in the 2021 Olympic Games in terms of training volume and training intensity distribution during the year and in different phases to track periodization. Based on the literature, we categorized the distances covered in relation to the athlete's race speed into three zones: Z1 &lt;80% RP; Z2 80-95% RP; Z3 &gt;95% RP. The training intensity distribution was calculated using the Polarization Index: PI = log10 (Z1/Z2 x Z3*100). The athlete's average weekly training volume during the 52-week season was 141.77 ± 27.27 km/week (571.94 ± 106 min/week), completed in 10.4 ± 1.24 training sessions. Throughout the season (Z1: 89.95%; Z2: 4.58%; Z3: 5.43%) and also during the different preparation phases, the training intensity distribution showed a polarized pattern (PI &gt;2.00 a.U.). In a typical interval form, the athlete performed intense training (HIT) at and above the anaerobic threshold twice a week (vLT2). Most (&gt;80%) of the high average weekly training volume was sustained running at low intensities. High-intensity interval training (HIIT) twice weekly in the base period typically took the form of long partial distances at and above the anaerobic threshold (~90% vVO2max) and short partial (&lt;800m) distances close to race speed. The polarization rate increased as the racing season approached, and more extended interval training at race speeds was used. In conclusion, in addition to the Pyramid distribution, a Polarized training intensity distribution can also be observed during elite distance runners' training.

Norwegian double-threshold method in distance running

This study aimed to give a systematic literature review about the training of elite Norwegian long-distance runners (1500-10.000 meters). After a search in databases, we found 7 articles, that have systematically registered the training volume and intensity distribution of 13 elite runners over longer periods (n = 13). The results were the following: the best long-distance runners run 120 to 180 kilometers per week on average. The waist majority of this training (75-80 %) is done at low intensity (62-82% HRmax). Two to four sessions are done at the anaerobic threshold pace (82-20% HRmax), either in continuous or interval format during the base period, often done twice on the same day. One to two times weekly higher intensity sessions (&gt;97% HRmax) are done, in form of short intervals (&gt;800m) or short sprints. Longer intervals, above the anaerobic threshold (92-97 % HRmax) are rarely used during the base period. The training is closely monitored by a lactate meter or heart rate monitor. Before the racing season, in the pre-competition period, the athletes do fewer workouts at an anaerobic threshold pace and increase the number of sessions at a specific race pace.

Assessing the Use of Heart-Rate Monitoring for Competitive Swimmers.

Quantifying training intensity provides a comprehensive understanding of the training stimulus. Recent technological advances may have improved the feasibility of using heart-rate (HR) monitoring in swimming. However, the implementation of HR monitoring is yet to be assessed longitudinally in the daily training environment of swimmers. This study aimed to assess the implementation of HR by comparing the training-intensity distribution from an external measure, planned volume at set intensities (PVSI), with the internal training-intensity distribution measured using time in HR zones. Using a longitudinal observational design, 10 competitive swimmers (8 male and 2 female, age: 22.0 [2.3]y, Fédération Internationale de Natation point score: 842.9 [58.5], mean [SD]) were monitored daily for 6months. Each session, HR data, and coached-planned and athlete-reported session rating of perceived exertion (Modified Category Ratio 10 scale) were recorded. Based on previously determined training zones from an incremental step test, PVSI was calculated using the planned distance and planned intensity of each swim bout. Training-intensity distributions were analyzed using a linear mixed model (lme4). The model revealed a small to moderate relationship between PVSI and time in HR zone, based on the Nakagawa R-squared value (range .14-.42). Training-intensity distribution differed between the internal measure (ie,HR) and the external measure of intensity (ie,PVSI). This demonstrates that internal and planned external measures of intensity cannot be used interchangeably to monitor training. Further research should explore how to best integrate these measures to better understand training in swimming.

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.

Commentary: The polarization-index: a simple calculation to distinguish polarized from non-polarized training intensity distributions.

Commentary: The polarization-index: a simple calculation to distinguish polarized from non-polarized training intensity distributions.

Training characteristics and performance of two male elite short-distance triathletes: From junior to "world-class".

The sports-science literature lacks data on training and performance characteristics of international elite athletes over multiple seasons. The present case study provided general training characteristics and performance data of two male short-distance triathletes in the Junior, U23, and international Elite categories. General training and performance data of two male elite triathletes were described in swimming, cycling, and running segments from the 2015 to 2022 season. The training load was presented using the ECO model while the training intensity distribution (TID) was a triphasic model. Both triathletes increased their performance throughout the seasons. Triathlete A increased his VO2max in cycling by 20.6%, in running by 16.7%. His power at VO2max and his speed at VO2max by 18.9% and 11.0%, respectively. Triathlete B improved his VO2max by 17.8% in cycling, by 16.1% in running and his power at VO2max by 24%, and his speed at VO2max by 14.3%. The triathletes trained on average 14-17 h a week. The TID model was polarized. To achieve the top international level, it is necessary to consider the following measures: training load progression; improvements in physiological variables; and participation in international events starting from youth categories.

School's out for summer-Differences in training characteristics between adolescent biathletes of different performance levels.

The purpose of this study was to retrospectively describe the longitudinal changes of training variables in adolescent biathletes based on performance level. Thirty biathletes (15 men and 15 women) were included in the study and categorized as either national level biathletes (NLB, n = 21) or national team biathletes (NTB, n = 9). Retrospective training data was collected from training diary covering the biathletes' four years (Y1-Y4) as student-athletes at upper secondary school. Training data was divided into physical and shooting training variables. A linear mixed-effect model was used for comparing the difference of the performance group and year of upper secondary school on training characteristics. The NTB group achieved a greater annual training volume than the NLB group, especially during Y4 (594±71 h·y-1 vs 461±127 h·y-1, p < 0.001), through an increase in duration of each session and by completing more weekly training volume during the general phase (13.7±4.6 vs 10.0±4.9 h·w-1, p = 0.004). No difference was observed in relative training intensity distribution between the groups. The total number of shots fired was also greater for the NTB (9971±4716 vs 7355±2812 shots·y-1, p = 0.003). There was an equal frequency in illness and injury for both the NLB and NTB. Accordingly, the results of the present study describe longitudinal changes of biathlon training in adolescent biathletes that also may affect performance development.

Demarcation of Intensity From 3 to 5 Zones Aids in Understanding Physiological Performance Progression in Highly Trained Under-23 Rowing Athletes.

Watts, SP, Binnie, MJ, Goods, PSR, Hewlett, J, Fahey-Gilmour, J, and Peeling, P. Demarcation of intensity from 3 to 5 zones aids in understanding physiological performance progression in highly trained under-23 rowing athletes. J Strength Cond Res 37(11): e593-e600, 2023-The purpose of this investigation was to compare 2 training intensity distribution models (3 and 5 zone) in 15 highly trained rowing athletes ( n = 8 male; n = 7 female; 19.4 ± 1.1 years) to determine the impact on primary (2,000-m single-scull race) and secondary (2,000-m ergometer time trial, peak oxygen consumption [V̇O 2 peak], lactate threshold 2 [LT2 power]) performance variables. Performance was assessed before and after 4 months training, which was monitored through a smart watch (Garmin Ltd, Olathe, KS) and chest-strap heart rate (HR) monitor (Wahoo Fitness, Atlanta, GA). Two training intensity distribution models were quantified and compared: a 3-zone model (Z1: between 50% V̇O 2 peak and lactate threshold 1 (LT1); Z2: between LT1 and 95% LT2; Z3: >95% LT2) and a 5-zone model (T1-T5), where Z1 and Z3 were split into 2 additional zones. There was significant improvement in LT2 power for both male (4.08% ± 1.83, p < 0.01) and female (3.52% ± 3.38, p = 0.02) athletes, with male athletes also demonstrating significant improvement in 2,000-m ergometer time trial (2.3% ± 1.92, p = 0.01). Changes in V̇O 2 peak significantly correlated with high-quality aerobic training (percent time in T2 zone; r = 0.602, p = 0.02), whereas changes in LT2 power significantly correlated with "threshold" training (percent time in T4 zone; r = 0.529, p = 0.04). These correlations were not evident when examining intensity distribution through the 3-zone model. Accordingly, a 5-zone intensity model may aid in understanding the progression of secondary performance metrics in rowing athletes; however, primary (on-water) performance remains complex to quantify.

PERFORMANCE AND TRAINING PROGRAM CHARACTERISTICS IN ELITE YUNIOR FEMALE ROLLER SKIER FROM 2021 SEASON: A CASE REPORT

The purpose was to evaluate the training program, body mass composition, aerobic performance laboratory and field test results, blood hormone concentration in elite junior female roller skier in successful competition season. Methods. Totally 206 training sessions (278 training hours) were analysed during six months (from April till September). Athlete wight and body fat changes were monitored, laboratory tests on a treadmill and field tests were performed and concentration of hormones in the blood was detected. Results. A polarised training intensity distribution was observed. The highest volume of training workloads (70 training hours per month) was achieved in the last month before start of World cup season, this change corelated with change in blood testosterone levels. Heart rate decreased by 7.51% at the anaerobic threshold load intensity and by 10.1% at lower intensity loads. Peak oxygen uptake (VO2max) of 49 ml/kg/min was reached in laboratory test. Increase of lean body mass by 2.4 kg was observed. The progress in 3000m running race time was detected from 14:30 minutes in the beginning of April to 13:16 minutes in June. Conclusion. VO2max in junior elite female roller skier is low in comparison with cross-country skiers, but the training workload intensity and volume are comparable with skiers. This research shows insight in top junior level female roller-skiers physiology and training, but specific values determining the success of this athlete are still to be determined if compared to traditional cross-country skier.

Capturing the Complex Relationship Between Internal and External Training Load: A Data-Driven Approach.

Training load is typically described in terms of internal and external load. Investigating the coupling of internal and external training load is relevant to many sports. Here, continuous kernel-density estimation (KDE) may be a valuable tool to capture and visualize this coupling. Using training load data in speed skating, we evaluated how well bivariate KDE plots describe the coupling of internal and external load and differentiate between specific training sessions, compared to training impulse scores or intensity distribution into training zones. On-ice training sessions of 18 young (sub)elite speed skaters were monitored for velocity and heart rate during 2 consecutive seasons. Training session types were obtained from the coach's training scheme, including endurance, interval, tempo, and sprint sessions. Differences in training load between session types were assessed using Kruskal-Wallis or Kolmogorov-Smirnov tests for training impulse and KDE scores, respectively. Training impulse scores were not different between training session types, except for extensive endurance sessions. However, all training session types differed when comparing KDEs for heart rate and velocity (both P < .001). In addition, 2D KDE plots of heart rate and velocity provide detailed insights into the (subtle differences in) coupling of internal and external training load that could not be obtained by 2D plots using training zones. 2D KDE plots provide a valuable tool to visualize and inform coaches on the (subtle differences in) coupling of internal and external training load for training sessions. This will help coaches design better training schemes aiming at desired training adaptations.

Restricted nasal-only breathing during self-selected low intensity training does not affect training intensity distribution.

Introduction: Low-intensity endurance training is frequently performed at gradually higher training intensities than intended, resulting in a shift towards threshold training. By restricting oral breathing and only allowing for nasal breathing this shift might be reduced. Methods: Nineteen physically healthy adults (3 females, age: 26.5 ± 5.1years; height: 1.77 ± 0.08m; body mass: 77.3 ± 11.4kg; VO2peak: 53.4 ± 6.6mL·kg-1min-1) performed 60min of self-selected, similar (144.7 ± 56.3 vs. 147.0 ± 54.2 W, p = 0.60) low-intensity cycling with breathing restriction (nasal-only breathing) and without restrictions (oro-nasal breathing). During these sessions heart rate, respiratory gas exchange data and power output data were recorded continuously. Results: Total ventilation (p < 0.001, ηp 2 = 0.45), carbon dioxide release (p = 0.02, ηp 2 = 0.28), oxygen uptake (p = 0.03, ηp 2 = 0.23), and breathing frequency (p = 0.01, ηp 2 = 0.35) were lower during nasal-only breathing. Furthermore, lower capillary blood lactate concentrations were found towards the end of the training session during nasal-only breathing (time x condition-interaction effect: p = 0.02, ηp 2 = 0.17). Even though discomfort was rated marginally higher during nasal-only breathing (p = 0.03, ηp 2 = 0.24), ratings of perceived effort did not differ between the two conditions (p ≥ 0.06, ηp 2 = 0.01). No significant "condition" differences were found for intensity distribution (time spent in training zone quantified by power output and heart rate) (p ≥ 0.24, ηp 2 ≤ 0.07). Conclusion: Nasal-only breathing seems to be associated with possible physiological changes that may help to maintain physical health in endurance athletes during low intensity endurance training. However, it did not prevent participants from performing low-intensity training at higher intensities than intended. Longitudinal studies are warranted to evaluate longitudinal responses of changes in breathing patterns.

High-Intensity Interval Training, Performance, and Oxygen Uptake Kinetics in Highly Trained Traditional Rowers.

Oxygen uptake kinetics (VO2kinetics) is a measure of an athlete's capacity to respond to variations in energy demands. Faster VO2kinetics is associated with better performance in endurance sports, but optimal training methods to improve VO2kinetics remain unclear. This study compared the effects of 2 high-intensity interval-training (HIIT) programs on traditional rowing performance and VO2kinetics. Twelve highly trained rowers performed one of two 6-week HIIT protocols: either 3-minute repetitions at 90% (HIIT90; n = 5) of peak aerobic power (PAP) or 90-second repetitions at 100% (HIIT100; n = 7) of PAP. Before (PRE) and after (POST) the training intervention, they performed an incremental test to exhaustion to determine the individual lactate threshold, onset of blood lactate accumulation and PAP, and two 6-minute rest-to-exercise transitions to determine VO2kinetics. No significant changes (P > .05) were observed for rowing ergometer power output at individual lactate threshold (HIIT90 PRE 255 [12], POST 264 [13]; HIIT100 247 [24], 266 [28]W), onset of blood lactate accumulation (279 [12], 291 [16]; 269 [23], 284 [32]W), or PAP (359 [13], 381 [15]; 351 [21], 363 [29]W) or for any parameters of VO2kinetics. No differences were observed between HIIT interventions. The HIIT interventions did not induce significant performance or VO2kinetics improvements, although mean power output at individual lactate threshold, onset of blood lactate accumulation, and PAP increased by 5.7%, 5.0%, and 4.5%, respectively. This suggests that the exact intensity and duration of HIIT sessions performed in the same intensity domain may be of lesser importance than other well-established influential factors (eg,training volume progression, training intensity distribution, altitude training) to develop aerobic qualities in endurance athletes.

Training load and intensity distribution for sprinting among world-class track cyclists.

Only few studies analyzed real training programs of sprinters while that should be a valuable step in the understanding of sprint training. The present study aimed at characterizing track cycling sprinter training by training load and intensity distribution. Twenty-nine weeks of prechampionship training data were retrospectively analyzed for 6 world-class athletes. Training load was measured by the ratio of volume completed to maximal volume and categorized by five intensity zones (endurance: zones1-2; sprinting: zones3-5) and exercise type (on-bike or resistance). Intra-week (training monotony) and inter-week (acute-chronic workload ratio) variation was also studied. On-bike training represented 77.4±15.3% of total training load; resistance training, 22.6±15.2% (note high standard deviation). Total weekly training load significantly varied (P=0.0002) with high acute-chronic workload ratio (12.0±3.2 weeks >1.5 or <0.8), but low intra-week variations (training monotony, 1.81±0.20). Zone4 and zone5 made up 74.4±16.9% of total training load; zone1, 15.8±11%. Training load was seldom in zone2 (6.4±5.3%) or zone3 (3.3±4.2%). From the first to the second half of the period, zone3-4 training load decreased (39.3±3.3 to 27.4±1.7%; P=0.01), while zone5 increased (34.9±2.4 to 50±3.7%; P=0.002). In this reduced group of elite athletes, training appeared to mainly consist of on-bike exercises within the highest intensity zones. As demonstrated by monotony and acute-chronic workload ratio overloading and unloading are based on high variations over weeks, not days. Essentially, this study describes a polarized intensity distribution on the highest intensities which increased with world championships approach.

Periodization of altitude training: A collective case study of high-level swimmers.

The objective was to quantify parallel changes in performance and physiological measures in relation to periodization of sequential altitude training over a season in elite swimmers. The altitude training of four female and two male international swimmers in selected seasons was examined using a collective case study approach. All swimmers were a medalist in World (WC) and/or European Championships (EC) 2013, 2014, 2016 and 2018 in short or long course competition. A traditional periodization model was employed using three macrocycles with 3-4 altitude camps (duration 21-24days each) scheduled over the season, following a polarized training intensity distribution (TID) with a volume ranged between 729km and 862km. The timing of return from altitude prior to competition was between 20-32days, with 28days the most common period. Competition performance was assessed with major (international) and minor (regional or national) competitions. Hemoglobin concentration, hematocrit, anthropometric characteristics, were measured before and after each camp. Competition performance following the altitude training camps improved by 0.6% ± 0.8% (personal best time; mean ± SD) (95% confidence limits (CL) 0.1%-1.1%), 1.6% ± 0.7% (95% CL 1.2% to 2.0%) (season best time) and 1.6% ± 0.5% (95% CL 1.3%-1.9%) (previous season time). Hemoglobin concentration increased 4.9% from pre-to post-altitude training camps, while hematocrit increased by 4.5%. The sum of six skinfolds reduced by 14.4% (95% CL 18.8%-9.9%) and 4.2% (95% CL 2.4%-9.2%) for the two males (EC), and by 15.8% (95% CL 19.5%-12.0%) for two females (WC). Three to four altitude training camps in a competitive season, around 21-24days of duration, scheduling the last return between 20-32days before the main competition, integrated in a traditional periodized sequence, can induce worthwhile improvements in international swimming performance, hematological parameters, and anthropometric characteristics.

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

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

The return from underperformance to sustainable world-class level: A case study of a male cross-country skier.

Purpose: To determine the main factors associated with unexpected underperformance and prospectively describe the holistic process of returning to sustainable world-class level in a male cross-country skier. Methods: Longitudinal training data was retrospectively analyzed across nine seasons (2012-2013 to 2020-2021), and categorized into training forms (endurance, strength, and speed), intensities [low- (LIT), moderate- (MIT), and high-intensity training (HIT)], and modes (specific and non-specific). Performance data was obtained from the International Ski and Snowboard Federation. Following two seasons of unexpected underperformance (2019-2020 and 2020-2021), the participant was prospectively followed in the process of returning to sustainable world-class level (2021-2022). Day-to-day training data and physiological tests were analyzed, and interviews with the participant and the head coach conducted. Results: Longitudinal training data from 2012-2013 to 2018-2019 demonstrated a non-linear 30% increase in total training volume (from 772 to 1,002h), mainly caused by increased volume of ski-specific endurance training without changes in intensity distribution. Coincidingly, the participant gradually reached a world-class performance level. After two seasons of unexpected underperformance with relatively similar training volumes and intensity distributions as in the preceding seasons, the possible contributing factors were identified: lack of training periodization, limited monitoring and intensity control, particularly in connection with a "extreme" regime of training with low carbohydrate availability and days including two MIT sessions, as well as lack of systematic technique training and follow-up by coaches on a daily basis. Consequently, the return to world-class level included the introduction of a clear micro-cycle periodization, more systematic physiological monitoring and testing, more accurate intensity control, increased carbohydrate intake during and between sessions, as well as increased emphasize on technique training and an assistant coach present during day-to-day training. Conclusion: These longitudinal data describe the main factors leading to unexpected underperformance, in addition to providing unique insights into the corresponding process of returning to sustainable world-class level in a male cross-country skier. The holistic approach described in this case study may serve as a theoretical framework for future studies and practical work with underperforming endurance athletes.

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 ± 130h (35% ± 31%, p < .001, large effect) and 78 ± 69 sessions (21% ± 24%, p < .001, very large effect). Junior training volume (658 ± 107h) did not correlate with senior volume (861 ± 74h) 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 ± 117h (p < .001; large effect) tied to increased low-intensity training (186 ± 115h, p < .001; large effect) and moderate-intensity training (13 ± 7h, 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 ± 44h, p = .022; large effect) and strength training (25 ± 23 vs. -3 ± 17h, 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.