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Purpose: To compare designs of training sessions applied by world-class cross-country skiers during their most successful junior and senior season. Methods: Retrospective analysis of self-reported training characteristics (ie, training form, intensity, and exercise mode) among 8 male and 7 female world-class cross-country skiers was conducted. Results: Total number of sessions (441 [71] vs 519 [34], P <.001, large effect) and mean duration (1.5 [0.1] h vs 1.7 [0.1] h, P <.001, moderate effect) increased from junior to senior age. More double-session days were performed at senior age (124 [50] vs 197 [29] d, P <.001, large). The number (310 [64] vs 393 [64], P <.001, large effect) and duration (1.3 [0.1] h vs 1.5 [0.1] h, P <.001, moderate effect) of low-intensity training sessions increased from junior to senior age. Regarding intensive training, most emphasis was put on high-intensity training sessions lasting 20 to 39 minutes with <5-minute intervals at junior age, while 40 to 59 minutes of moderate-intensity training with 5- to 9-minute intervals was predominant at senior age. More MIXED (combined moderate- and high-intensity) sessions (9 [7] vs 14 [7], P =.023, moderate effect) and longer races (0.5 [0.1] h vs 0.6 [0.1] h, P = 0.29, moderate effect) compensated for fewer high-intensity training sessions at senior age (36 [17] vs 25 [10], P =.027, moderate effect). Duration of strength-training sessions increased significantly (0.6 [0.1] vs 0.8 [0.2] h, P = 0.30, moderate effect), while other training forms remained unchanged. Conclusions: World-class cross-country skiers increased their training volume from junior to senior age primarily by more and longer low-intensity training sessions and more often training twice per day. Concurrently, the most frequent intensive sessions were modified from high- to moderate-intensity training, lasted longer, and contained longer intervals. [ABSTRACT FROM AUTHOR]

Background: Elite sport is continuously evolving. World records keep falling and athletes from a longer list of countries are involved. Purpose: This commentary was designed to provide insights into present and future trends associated with world-class endurance training based on the perspectives, experience, and knowledge of an expert panel of 25 applied sport scientists. Results: The key drivers of development observed in the past 10–15 years were related to (1) more accessible scientific knowledge for coaches and athletes combined with (2) better integration of practical and scientific exchange across multidisciplinary perspectives within professionalized elite athlete support structures, as well as (3) utilization of new technological advances. Based on these perspectives, we discerned and exemplified the main trends in the practice of endurance sports into the following categories: better understanding of sport-specific demands; improved competition execution; larger, more specific, and more precise training loads; improved training quality; and a more professional and healthier lifestyle. The main areas expected to drive future improvements were associated with more extensive use of advanced technology for monitoring and prescribing training and recovery, more precise use of environmental and nutritional interventions, better understanding of athlete–equipment interactions, and greater emphasis on preventing injuries and illnesses. Conclusions: These expert insights can serve as a platform and inspiration to develop new hypotheses and ideas, encourage future collaboration between researchers and sport practitioners, and, perhaps most important, stimulate curiosity and further collaborative studies about the training, physiology, and performance of endurance athletes. [ABSTRACT FROM AUTHOR]

Purpose: The concept of training quality reflects that the effect of training is dependent on more than the mere product of training load (eg, duration, intensity, frequency). The aims of this commentary are to (1) propose a practice-oriented framework to describe training quality and its general and context-dependent characteristics and (2) discuss how athletes and coaches can work to improve training quality. Conclusions: Training quality can be viewed from different perspectives. The holistic dimension includes the entire training process (goal setting, gap analysis, application of training principles and methods, etc), while a narrower dimension encompasses the specific training sessions and how they are executed in relation to the intended purpose. To capture the varying contexts, we define training quality as the degree of excellence related to how the training process or training sessions are executed to optimize adaptations and, thereby, improve overall performance. Although training quality is challenging to quantify, we argue that identification and assessment of quality indicators will increase our scientific understanding and consequently help coaches and athletes to improve training quality. We propose that the physical, technical, and psychological factors of training quality can be improved through an individualized learning process of systematic planning, execution, and debriefing. However, assessment tools should be identified and scientifically validated across different training sessions and sports. We encourage further interventions to improve training quality. [ABSTRACT FROM AUTHOR]

Purpose: To describe the training volume, intensity distribution, and use of swimming styles during a Paralympic cycle in a multiple swimming champion with paraplegia. Methods: The female Paralympic swimmer was 23–26 years of age and had a body mass of 60 to 62 kg and a body height of 174 cm. She has a spinal cord injury at the Th6 level, competed in the S5/SB4 Para swimming classes, and uses a wheelchair for mobility. Training time, as well as distance in the different intensity zones and swimming styles, was registered with the "workouts for swim coaches" software throughout a full Paralympic cycle. Results: The Para swimmer performed a total of 388, 524, 471, and 656 annual hours of swimming, corresponding to 1126, 1504, 1463, and 1993 km, in the 2012–13, 2013–14, 2014–15, and 2015–16 seasons, respectively. In addition, she performed 1 to 3 weekly dry-land strength sessions and 4 to 6 weekly dry-land basic skill sessions. She conducted 91% to 94% of the swimming distance in each macrocycle at low intensity, 2% to 4% at moderate intensity, and 3% to 6% at high intensity. She performed 78% to 84% of the swimming distance in each macrocycle in the freestyle swimming technique and the remaining 16% to 22% in the backstroke, breaststroke, and butterfly techniques. Conclusion: This case study exemplifies how a female Paralympic swimmer with paraplegia progressed her training in the seasons leading up to the Paralympic Games, reaching an annual training distance of 2000 km, which is similar to that of able-bodied swimmers. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the factors associated with underperformance and the subsequent changes in training characteristics and supportive actions when returning to the world's best cross-country skier. Methods: The participant is the most decorated winter Olympian, with 8 Olympic gold medals, 18 World Championship titles, and 114 World Cup victories. Training data were categorized by training form (endurance, strength, and speed); intensity (low, moderate, and high); and mode (running, cycling, and skiing/roller skiing). In addition, test data were retrospectively analyzed, and interviews were performed with the participant and her support team. Results: After the competitive season, the participant had 8 weeks without systematic training and an evaluation process aiming to detect the factors contributing to underperformance. Here physiological, technical, and psychological challenges were detected. As a consequence, the participant included less high-intensity training (1.2 vs 2.1 sessions/wk, P =.011); more moderate-intensity training (0.9 vs 0.4 sessions/wk, P =.016); and more low-intensity training (6.9 vs 5.9 sessions/wk, P =.036) during the general preparation phase but with similar total endurance training load as previous season. In addition, more strength training (1.6 vs 1.1 h/wk, P =.036) and new ski-specific strength exercises were included. Finally, the athlete's autonomy when planning and adjusting training was increased, nontraining stressors were reduced, more frequent testing was included, systematic mental training was initiated, her nutritional strategy was adjusted, and her asthma treatment was optimized. Conclusions: Overall, the current case study could be used as a framework for the holistic approach to treating an overtraining condition and for generation of new hypothesis in this exiting area. [ABSTRACT FROM AUTHOR]

Performing at an elite level in Nordic combined (NC) requires both the explosiveness required for ski jumping performance and the endurance capacity required for cross-country skiing. Purpose: To describe the characteristics of world-class NC athletes' training and determine how endurance and non-endurance (ie, strength, power, and ski jumping) training is periodized. Methods: Annual training characteristics and the periodization of endurance and non-endurance training were determined by analyzing the training diaries of 6 world-class NC athletes. Results: Of 846 ± 72 annual training hours, 540 ± 37 h were endurance training, with 88.6% being low-, 5.9% moderate-, and 5.5% high-intensity training. While training frequency remained relatively constant, the total training volume was reduced from the general preparatory to the competition phase, primarily due to less low- and moderate-intensity training (P < .05). A total of 236 ± 55 h/y were spent as non-endurance training, including 211 ± 44 h of power and ski-jump-specific training (908 ± 165 ski jumps and ski-jump imitations). The proportion of non-endurance training increased significantly toward the competition phase (P < .05). Conclusion: World-class NC athletes reduce the volume of low- and moderate-intensity endurance training toward the competition phase, followed by an increase in the relative contribution of power and ski-jump training. These data provide novel insight on how successful athletes execute their training and may facilitate more-precise coaching of future athletes in this sport. In addition, this information is of high relevance for the training organization of other sports that require optimization of 2 fundamentally different physical capacities. [ABSTRACT FROM AUTHOR]

Purpose: To generate updated Olympic-medal benchmarks for ...O2max in winter endurance disciplines, examine possible differences in ...O2max between medalists and nonmedalists, and calculate gender difference in ...O2max based on a homogeneous subset of world-leading endurance athletes. Methods: The authors identiied 111 athletes who participated in winter Olympic Games/World Championships in the period 1990 to 2013. All identiied athletes tested ...O2max at the Norwegian Olympic Training Center within ±1 y of their championship performance. Testing procedures were consistent throughout the entire period. Results: For medal-winning athletes, the following relative ...O2max values (mean:95% conidence intervals) for men/women were observed (mL ⋅ min-1 ⋅ kg-1): 84:87-81/72:77-68 for cross-country distance skiing, 78:81-75/68:73-64 for cross-country sprint skiing, 81:84-78/67:73-61 for biathlon, and 77:80-75 for Nordic combined (men only). Similar benchmarks for absolute ...O2max (L/min) in male/female athletes are 6.4:6.1-6.7/4.3:4.1-4.5 for cross-country distance skiers, 6.3:5.8-6.8/4.0:3.7-4.3 for cross-country sprint skiers, 6.2:5.7-6.4/4.0:3.7-4.3 for biathletes, and 5.3:5.0-5.5 for Nordic combined (men only). The difference in relative ...O2max between medalists and nonmedalists was large for Nordic combined, moderate for cross-country distance and biathlon, and small/trivial for the other disciplines. Corresponding differences in absolute ...O2max were small/trivial for all disciplines. Male cross-country medalists achieve 15% higher relative ...O2max than corresponding women. Conclusions: This study provides updated benchmark ...O2max values for Olympic-medal-level performance in winter endurance disciplines and can serve as a guideline of the requirements for future elite athletes. [ABSTRACT FROM AUTHOR]

Human upper performance limits in the 100-m sprint remain the subject of much debate. The aim of this commentary is to highlight the vulnerabilities of prognoses from historical trends by shedding light on the mechanical and physiological limitations associated with human sprint performance. Several conditions work against the athlete with increasing sprint velocity; air resistance and braking impulse in each stride increase while ground contact time typically decreases with increasing running velocity. Moreover, muscle force production declines with increasing speed of contraction. Individual stature (leg length) strongly limits the stride length such that conditioning of senior sprinters with optimized technique mainly must be targeted to enhance the stride frequency. More muscle mass means more power and thereby greater ground reaction forces in sprinting. However, as the athlete gets heavier, the energy cost of accelerating that mass also increases. This probably explains why body mass index among world-class sprinters show low variability and average 23.7 ±1.5 and 20.4 ±1.4 for male and female sprinters, respectively. Performance development of world-class athletes indicates that ~8% improvement from the age of 18 represents the current maximum trainability of sprint performance. However, drug abuse is a huge confounding factor associated with such analyses, and available evidence suggests that we are already very close to "the citius end" of 100-m sprint performance. [ABSTRACT FROM AUTHOR]

One year of training data from 8 elite orienteers were divided into a transition phase (TP), general preparatory phase (GPP), specific preparatory phase (SPP), and competition phase (CP). Average weekly training volume and frequency, hours at different intensities (zones 1–3), cross-training, running, orienteering, interval training, continuous training, and competition were calculated. Training volume was higher in GPP than TP, SPP, and CP (14.9 vs 9.7, 11.5, and 10.6 h/wk, P < .05). Training frequency was higher in GPP than TP (10 vs 7.5 sessions/wk, P < .05). Zone 1 training was higher in GPP than TP, SPP, and CP (11.3 vs 7.1, 8.3, and 7.7 h/wk, P < .05). Zone 3 training was higher in SPP and CP than in TP and GPP (0.9 and 1.1 vs 1.6 and 1.5 h/ wk, P < .05). Cross-training was higher in GPP than SPP and CP (4.3 vs 0.8 h/wk, P < .05). Interval training was higher in GPP than TP, SPP, and CP (0.7 vs 0.3 h/wk, P < .05). High-intensity continuous training was higher in GPP than CP (0.9 vs 0.4 h/ wk, P < .05), while competition was higher in SPP and CP than in TP and GPP (1.3 and 1.5 vs 0.6 and 0.3 h/wk, P < .01). In conclusion, these champion endurance athletes achieved a progressive reduction in total training volume from GPP to CP via a shortening of each individual session while the number of training sessions remained unchanged. This decrease in training volume was primarily due to a reduction in the number of hours of low-intensity, non-sport-specific cross-training. [ABSTRACT FROM AUTHOR]

Purpose: The authors directly compared 3 frequently used methods of heart-rate-based training-intensity- distribution (TID) quantification in a large sample of training sessions performed by elite endurance athletes. Methods: Twenty-nine elite cross-country skiers (16 male, 13 female; 25 ± 4 y; 70 ± 11 kg; 76 ± 7 mL • min-1 • kg-1 VO2max) conducted 570 training sessions during a ~14-d altitude-training camp. Three analysis methods were used: time in zone (TIZ), session goal (SG), and a hybrid session-goal/time-in-zone (SG/TIZ) approach. The proportion of training in zone 1, zone 2, and zone 3 was quantified using total training time or frequency of sessions, and simple conversion factors across different methods were calculated. Results: Comparing the TIZ and SG/TIZ methods, 96.1% and 95.5%, respectively, of total training time was spent in zone 1 (P < .001), with 2.9%/3.6% and l.l%/0.8% in zones 2/3 (P < .001). Using SG, this corresponded to 86.6% zone 1 and 1 l.l%/2.4% zone 2/3 sessions. Estimated conversion factors from TIZ or SG/TIZ to SG and vice versa were 0.9/1.1, respectively, in the low-intensity training range (zone 1) and 3.0/0.33 in the high-intensity training range (zones 2 and 3). Conclusions: This study provides a direct comparison and practical conversion factors across studies employing different methods of TID quantification associated with the most common heart-rate-based analysis methods. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to validate the accuracy of self-reported (SR) training duration and intensity distribution in elite endurance athletes. Methods: Twenty-four elite cross-country skiers (25 ± 4 y, 67.9 ± 9.88 kg, 75.9 ± 6.50 mL • min -1 • kg -11) SR all training sessions during an ~14-d altitude-training camp. Heart rate (HR) and some blood lactate measurements were collected during 466 training sessions. SR training was compared with recorded training duration from HR monitors, and SR intensity distribution was compared with expert analysis (EA) of all session data. Results: SR training was nearly perfectly correlated with recorded training duration (r = .99), but SR training was 1.7% lower than recorded training duration (P < .001). SR training duration was also nearly perfectly correlated (r - .95) with recorded training duration >55% HRmax, but SR training was 11.4% higher than recorded training duration >55% HRmax (P < .001) due to SR inclusion of time <55% HRmax. No significant differences were observed in intensity distribution in zones 1-2 between SR and EA comparisons, but small discrepancies were found in zones 3-4 (P < .001). Conclusions: This study provides evidence that elite endurance athletes report their training data accurately, although some small differences were observed due to lack of a SR "gold standard." Daily SR training is a valid method of quantifying training duration and intensity distribution in elite endurance athletes. However, additional common reporting guidelines would further enhance accuracy. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this investigation was to quantify maximal aerobic power (VO2max) in soccer as a function of performance level, position, age, and time of season. In addition, the authors examined the evolution of VO2max among professional players over a 23-y period. Methods: 1545 male soccer players (22 ± 4 y, 76 ± 8 kg, 181 ± 6 cm) were tested for VO2max at the Norwegian Olympic Training Center between 1989 and 2012. Results: No differences in VO2max were observed among national-team players, 1st- and 2nd-division players, and juniors. Midfielders had higher VO2max than defenders, forwards, and goalkeepers (P < .05). Players <18 y of age had ~3% higher VO2max than 23- to 26-y-old players (P = .016). The players had 1.6% and 2.1 % lower VO2max during off-season than preseason (P = .046) and in season (P = .021), respectively. Relative to body mass, VO2max among the professional players in this study has not improved over time. Professional players tested during 2006-2012 actually had 3.2% lower VO2max than those tested from 2000 to 2006 (P = .001). Conclusions: This study provides effect-magnitude estimates for the influence of performance level, player position, age, and season time on VO2max in men's elite soccer. The findings from a robust data set indicate that VO2max values ~62-64 mL • kg-1 • min-1 fulfill the demands for aerobic capacity in men's professional soccer and that VO2max is not a clearly distinguishing variable separating players of different standards. [ABSTRACT FROM AUTHOR]

Purpose: To compare sprint and countermovement-jump (CMJ) performance among competitive soccer players as a function of performance level, field position, and age. In addition, the authors wanted to quantify the evolution of these physical characteristics among professional players over a 15-y period. Methods: 939 athletes (22.1 ± 4.3 y), including national-team players, tested 40-m sprint with electronic timing and CMJ on a force platform at the Norwegian Olympic Training Center between 1995 and 2010. Results: National-team and lst-division players were faster (P < .05) than 2nd-division (1.0-1.4%), 3rd- to 5th-division (3.0-3.8%), junior national-team (1.7-2.2%), and junior players (2.8-3.7%). Forwards were faster than defenders (1.4%), midfielders (2.5%), and goalkeepers (3.2%) over 0-20 m (P < .001). Midfielders jumped -2.0 cm lower than the other playing positions (P < .05). Sprinting velocity peaked in the age range 20-28 y and declined significantly thereafter (P < .05). Players from 2006-2010 had 1-2% faster 0-20 m and peak velocity than players from the 1995-1999 and 2000-2005 epochs, whereas no differences in CMJ performance were observed. Conclusions: This study provides effect-magnitude estimates for the influence of performance level, position, and age on sprint and CMJ performance in soccer. While CMJ performance has remained stable over the time, there has been a small but positive development in sprinting velocity among professional players. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this investigation was to compare sprint and countermovement-jump (CMJ) performance among female competitive soccer players as a function of performance level, field position, and age. In addition, the authors wanted to quantify the evolution of these physical characteristics among elite players over a 15-y period. Methods: 194 female elite players (22± 4.1 y, 63 ± 5.6 kg), including an Olympic winning squad, tested 40-m sprint with electronic timing and CMJ on a force platform at the Norwegian Olympic training center from 1995 to 2010. Results: Moderate to large velocity differences across performance levels and positions were observed. National-team players were 2% faster than lst-division players (P = .027, d = 0.5) and 5% faster than 2nd-division players (P < .001, d= 1.3) over 0-20 m. National-team players jumped 8-9% higher than 1st-division players (P = .001, d = 0.6) and junior elite players (P = .023, d = 0.5). Forwards were 3^% faster than midfielders (P < .001, d - 0.8) and goalkeepers (P = .003, d - 0.9) over 0-20 m. No differences in velocity or CMJ height were observed among the age categories. Players from 2006-2010 were 2% faster (P < .05, d = 0.6) than players from 1995-1999 over 20 m, whereas no differences in 20- to 40-m velocity or CMJ performance were observed. Conclusions: This study provides effect-magnitude estimates for the influence of performance level, age, and player position on sprint and CMJ performance in female soccer players. While 20- to 40-m velocity and CMJ performance have remained stable over the time, there has been a moderate but positive development in 0- to 20-m velocity among elite performers. [ABSTRACT FROM AUTHOR]

Purpose: A review of published studies monitoring sprint performance reveals considerable variation in start distance behind the initial timing gate. The aim of the current study was to generate correction factors across varying flying-start distances used in sprint testing with photocells. Methods: Forty-four well-trained junior soccer players (age 18.2 ± 1.0 y, height 175 ± 8 cm, body mass 68.4 ± 8.9 kg) performed sprint testing on an indoor sprint track. They were allocated to 3 groups based on sprintperformance level. Times for 10- and 200-m sprint with foot placement ranging from 0.5 to 15 m back from the initial timing gate were recorded twice for each athlete. Results: Correction-factor equation coefficients were generated for each of the 3 analyzed groups derived from the phase-decay equation y = (y0 - PL) x exp(-k x x) + PL, where y = time difference (0.5-m flying start as reference), x = flying-start distance, y0 is the y value when time is zero, PL (plateau) is the y value at infinite times, and k is the rate constant, expressed in reciprocal of the x-axis time units; if x is in seconds, then k is expressed in inverse seconds. R² was ≥.998 across all athlete groups and sprint distances, demonstrating excellent goodness of fit. Within-group time differences were significant (P < .05) across all flying-start distance checkpoints for all groups. Between-groups time-saving differences up to 0.04 s were observed between the fastest and the slowest groups (P < .05). Conclusions: Small changes in flying-start distances can cause time differences larger than the typical gains made from specific training, or even the difference between the fastest and slowest elite team-sport athletes. The presented correction factors should facilitate more meaningful comparisons of published sprint-performance results. [ABSTRACT FROM AUTHOR]

The present study investigated the effects of initial levels of cycling performance, peak oxygen uptake ( O2peak) and gross efficiency (GE) on the subsequent adaptations of these variables and their relationship following high-intensity training (HIT) designed to increase O2peak in competitive cyclists. Sixty cyclists ( O2peak = 61 ± 6 mL kg-1 min-1) were assigned a 12-week training program consisting of twenty-four supervised high-intensity interval training sessions and ad libitum low intensity training. GE was calculated at 125, 175, and 225 W and performance was determined by mean power during a 40-min time-trial (Power40 min). In addition to correlation analyses between initial level and pre- to post-intervention changes of the different variables, we compared these changes between four groups where participants were categorized with either low and/or high initial levels of O2peak and GE. Average volume of high- and low-intensity training during the 12-week intervention was 1.5 ± 0.3 and 8.3 ± 2.7 h·week-1, respectively. Following the 12-week training period, there was a significant increase in absolute and body mass normalized O2peak and Power40 min (p < 0.05) and a significant decrease in GE (p < 0.05) for all athletes pooled. There was no change in body mass following the 12-week training period. We found a moderate negative correlation between initial level of O2peak and the change in O2peak following the training period (r = -0.32; p < 0.05). A small negative correlation was also found between initial Power40 min and its change following training both when expressed in absolute power and power normalized for body mass (r = -0.27 and -0.28; both p < 0.05). A moderate negative correlation was also found between initial levels for GE and its change following training (r = -0.44; p < 0.01). There were no differences between the four groups based on initial levels of O2peak and GE in the response to training on O2peak, GE, or Power40 min (all p > 0.12). In conclusion, the present findings suggest that there are statistically significant effects of initial levels of cycling performance and O2peak and on the subsequent adaptations following a 12-week HIT program, but the small and moderate effects indicate limited influence on training practice. [ABSTRACT FROM AUTHOR]