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Jac Orie, Nico Hofman, Jos J. de Koning and Carl Foster

During the last decade discussion about training-intensity distribution has been an important issue in sports science. Training-intensity distribution has not been adequately investigated in speed skating, a unique activity requiring both high power and high endurance.

Purpose:

To quantify the training-intensity distribution and training hours of successful Olympic speed skaters over 10 Olympiads.

Methods:

Olympic-medal-winning trainers/coaches and speed skaters were interviewed and their training programs were analyzed. Each program was qualified and quantified: workout type (specific and nonspecific) and training zones (zone 1 ≤2 mMol/L lactate, zone 2 2–4 mMol/L lactate, zone 3 lactate >4 mMol/L). Net training times were calculated.

Results:

The relation between total training hours and time (successive Olympiads) was not progressive (r = .51, P > .5). A strong positive linear relation (r = .96, P < .01) was found between training distribution in zone 1 and time. Zones 2 and 3 both showed a strong negative linear relation to time (r = –.94, P < .01; r = –.97, P < .01). No significant relation was found between speed skating hours and time (r = –.11, P > .05). This was also the case for inline skating and time (r = –.86, P > .05).

Conclusions:

These data indicate that in speed skating there was a shift toward polarized training over the last 38 y. This shift seems to be the most important factor in the development of Olympic speed skaters. Surprisingly there was no relation found between training hours, skating hours, and time.

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Stephen A. Ingham, Barry W. Fudge and Jamie S. Pringle

This case study observed the training delivered by a 1500-m runner and the physiological and performance change during a 2-y period. A male international 1500-m runner (personal best 3:38.9 min:s, age 26 y, height 1.86 m, body mass 76 kg) completed 6 laboratory tests and 14 monitored training sessions, during 2 training years. Training distribution and volume was ascertained from training diary and spot-check monitoring of heart rate and accelerometry measurements. Testing and training information were discussed with coach and athlete from which training changes were made. In the first training year, low-intensity training was found to be performed above the prescribed level, which was adjusted with training and coach support in y 2 (training zone < 80% of vVO2max, y 1 = 20%; y 2 = 55%). “Tempo” training was also performed at an excessively high intensity (Δ [blood lactate] 5–25 min of tempo run, y 1 = Δ6.7 mM, y 2 = Δ2.5 mM). From y 1 to 2, there was a concomitant increase in the proportion of training in the high-intensity zone of 100 to 130% vVO2max from 7 to 10%. Values for VO2max increased from 72 to 79 mL · kg−1 · min, economy improved from 210 to 206 mL · kg−1 · min, and 1500-m performance time improved from 3:38.9 to 3:32.4 min:s from the beginning of y 1 to the end of y 2. This case shows a modification in training methodology that was coincident with a greater improvement in physiological capability and furtherance in performance improvement.

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Dean Ritchie, Will G. Hopkins, Martin Buchheit, Justin Cordy and Jonathan D. Bartlett

Context:

Training volume, intensity, and distribution are important factors during periods of return to play.

Purpose:

To quantify the effect of injury on training load (TL) before and after return to play (RTP) in professional Australian Rules football.

Methods:

Perceived training load (RPE-TL) for 44 players was obtained for all indoor and outdoor training sessions, while field-based training was monitored via GPS (total distance, high-speed running, mean speed). When a player sustained a competition time-loss injury, weekly TL was quantified for 3 wk before and after RTP. General linear mixed models, with inference about magnitudes standardized by between-players SDs, were used to quantify effects of lower- and upper-body injury on TL compared with the team.

Results:

While total RPE-TL was similar to the team 2 wk before RTP, training distribution was different, whereby skills RPE-TL was likely and most likely lower for upper- and lower-body injury, respectively, and most likely replaced with small to very large increases in running and other conditioning load. Weekly total distance and high-speed running were most likely moderately to largely reduced for lower- and upper-body injury until after RTP, at which point total RPE-TL, training distribution, total distance, and high-speed running were similar to the team. Mean speed of field-based training was similar before and after RTP compared with the team.

Conclusions:

Despite injured athletes’ obtaining comparable TLs to uninjured players, training distribution is different until after RTP, indicating the importance of monitoring all types of training that athletes complete.

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Andrew J. Carnes and Sara E. Mahoney

effective training in this population, who comprise a large proportion of runners and who dedicate considerable time and effort to individual achievement. Endurance training distribution is typically quantified using 3 intensity “zones” delineated by ventilatory thresholds (VTs) and/or blood lactate levels

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Dean Ritchie, Will G. Hopkins, Martin Buchheit, Justin Cordy and Jonathan D. Bartlett

Purpose:

Load monitoring in Australian football (AF) has been widely adopted, yet team-sport periodization strategies are relatively unknown. The authors aimed to quantify training and competition load across a season in an elite AF team, using rating of perceived exertion (RPE) and GPS tracking.

Methods:

Weekly totals for RPE and GPS loads (including accelerometer data; PlayerLoad) were obtained for 44 players across a full season for each training modality and for competition. General linear mixed models compared mean weekly load between 3 preseason and 4 in-season blocks. Effects were assessed with inferences about magnitudes standardized with between-players SD.

Results:

Total RPE load was most likely greater during preseason, where the majority of load was obtained via skills and conditioning. There was a large reduction in RPE load in the last preseason block. During in-season, half the total load came from games and the remaining half from training, predominantly skills and upper-body weights. Total distance, high-intensity running, and PlayerLoad showed large to very large reductions from preseason to in-season, whereas changes in mean speed were trivial across all blocks. All these effects were clear at the 99% level.

Conclusions:

These data provide useful information about targeted periods of loading and unloading across different stages of a season. The study also provides a framework for further investigation of training periodization in AF teams.

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Espen Tønnessen, Vegard Rasdal, Ida S. Svendsen, Thomas A. Haugen, Erlend Hem and Øyvind Sandbakk

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.

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Iker Muñoz, Stephen Seiler, Javier Bautista, Javier España, Eneko Larumbe and Jonathan Esteve-Lanao

Purpose:

To quantify the impact of training-intensity distribution on 10K performance in recreational athletes.

Methods:

30 endurance runners were randomly assigned to a training program emphasizing low-intensity, sub-ventilatory-threshold (VT), polarized endurance-training distribution (PET) or a moderately high-intensity (between-thresholds) endurance-training program (BThET). Before the study, the subjects performed a maximal exercise test to determine VT and respiratory-compensation threshold (RCT), which allowed training to be controlled based on heart rate during each training session over the 10-wk intervention period. Subjects performed a 10-km race on the same course before and after the intervention period. Training was quantified based on the cumulative time spent in 3 intensity zones: zone 1 (low intensity, <VT), zone 2 (moderate intensity, between VT and RCT), and zone 3 (high intensity, >RCT). The contribution of total training time in each zone was controlled to have more low-intensity training in PET (±77/3/20), whereas for BThET the distribution was higher in zone 2 and lower in zone 1 (±46/35/19).

Results:

Both groups significantly improved their 10K time (39min18s ± 4min54s vs 37min19s ± 4min42s, P < .0001 for PET; 39min24s ± 3min54s vs 38min0s ± 4min24s, P < .001 for BThET). Improvements were 5.0% vs 3.6%, ~41 s difference at post-training-intervention. This difference was not significant. However, a subset analysis comparing the 12 runners who actually performed the most PET (n = 6) and BThET (n = 16) distributions showed greater improvement in PET by 1.29 standardized Cohen effect-size units (90% CI 0.31–2.27, P = .038).

Conclusions:

Polarized training can stimulate greater training effects than between-thresholds training in recreational runners.

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R. Pla, Y. Le Meur, A. Aubry, J.F. Toussaint and P. Hellard

experimental point of view, Arroyo-Toledo et al 5 performed the only swimming study comparing the performance responses of regional swimmers for different training distributions and reported improvement in the pure performances with a low volume and a distribution (49%, 33%, and 18%) compared with moderate

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Andrés Pérez, Domingo J. Ramos-Campo, Cristian Marín-Pagan, Francisco J. Martínez-Noguera, Linda H. Chung and Pedro E. Alcaraz

determine the most optimal and effective intensity training distribution to obtain the appropriate adaptations needed for ultraendurance events. To our knowledge, no studies have examined how the different intensity distribution programs with 2 strength training sessions per week affect fat metabolism and

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Roberto Baldassarre, Marco Bonifazi, Romain Meeusen and Maria Francesca Piacentini

Most models of training distribution in endurance events in literature present data on runners, cyclists, rowers, or skiers, indicating that the majority of training is performed at low intensities with only 20% performed at high intensities. 1 , 2 Open-water swimming (OWS) is an outdoor endurance