Purpose: To provide novel insight regarding the influence of exercise modality on training load management by (1) providing a theoretical framework for the impact of physiological and biomechanical mechanisms associated with different exercise modalities on training load management in endurance exercise and (2) comparing effort-matched low-intensity training sessions performed by top-level athletes in endurance sports with similar energy demands. Practical Applications and Conclusions: The ability to perform endurance training with manageable muscular loads and low injury risks in different exercise modalities is influenced both by mechanical factors and by muscular state and coordination, which interrelate in optimizing power production while reducing friction and/or drag. Consequently, the choice of exercise modality in endurance training influences effort beyond commonly used external and internal load measurements and should be considered alongside duration, frequency, and intensity when managing training load. By comparing effort-matched low- to moderate-intensity sessions performed by top-level athletes in endurance sports, this study exemplifies how endurance exercise with varying modalities leads to different tolerable volumes. For example, the weight-bearing exercise and high-impact forces in long-distance running put high loads on muscles and tendons, leading to relatively low training volume tolerance. In speed skating, the flexed knee and hip position required for effective speed skating leads to occlusion of thighs and low volume tolerance. In contrast, the non-weight-bearing, low-contraction exercises in cycling or swimming allow for large volumes in the specific exercise modalities. Overall, these differences have major implications on training load management in sports.
Øyvind Sandbakk, Thomas Haugen, and Gertjan Ettema
Dean Ritchie, Will G. Hopkins, Martin Buchheit, Justin Cordy, and Jonathan D. Bartlett
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.
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.
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.
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.
Successful endurance training involves the manipulation of training intensity, duration, and frequency, with the implicit goals of maximizing performance, minimizing risk of negative training outcomes, and timing peak fitness and performances to be achieved when they matter most. Numerous descriptive studies of the training characteristics of nationally or internationally competitive endurance athletes training 10 to 13 times per week seem to converge on a typical intensity distribution in which about 80% of training sessions are performed at low intensity (2 mM blood lactate), with about 20% dominated by periods of high-intensity work, such as interval training at approx. 90% VO2max. Endurance athletes appear to self-organize toward a high-volume training approach with careful application of high-intensity training incorporated throughout the training cycle. Training intensification studies performed on already well-trained athletes do not provide any convincing evidence that a greater emphasis on high-intensity interval training in this highly trained athlete population gives long-term performance gains. The predominance of low-intensity, long-duration training, in combination with fewer, highly intensive bouts may be complementary in terms of optimizing adaptive signaling and technical mastery at an acceptable level of stress.
Frank Nugent, Thomas Comyns, Alan Nevill, and Giles D. Warrington
Purpose: To assess the effects of a 7-wk low-volume, high-intensity training (HIT) intervention on performance parameters in national-level youth swimmers. Methods: Sixteen swimmers (age 15.8 [1.0] y, age at peak height velocity 12.9 [0.6] y, 100-m freestyle 61.4 [4.1] s) were randomly assigned to an HIT group or a low-intensity, high-volume training (HVT) group that acted as a control. The HIT group reduced their weekly training volume of zone 1 (low-intensity) training by 50% but increased zone 3 (high-intensity) training by 200%. The HVT group performed training as normal. Pretest to posttest measures of physiological performance (velocity at 2.5- and 4-mM blood lactate [velocity2.5mM and velocity4mM] and peak blood lactate), biomechanical performance (stroke rate, stroke length [SL], and stroke index [SI] over a 50- and 400-m freestyle), and swimming performance (50-, 200-, and 400-m freestyle) were assessed. Results: There were no significant 3-way interactions between time, group, and sex for all performance parameters (P > .05). There was a significant 2-way interaction between time and group for velocity4mM (P = .02,
Dean Ritchie, Justin Keogh, Steven Stern, Peter Reaburn, Fergus O’Connor, and Jonathan D. Bartlett
Little is known about the effect of preceding endurance-exercise bouts on subsequent resistance-training (RT) performance in team-sport players. Purpose: To examine the effect of prior skills/endurance training and different recovery time periods on subsequent same-day RT performance in professional Australian football players. Methods: Sport-specific endurance-running loads (duration [in minutes], total distance [in meters], mean speed [in meters per minute], high-speed running >15 km·h−1, and relative high-speed running [>75% and >85% of maximal velocity]) were obtained for 46 professional Australian football players for each training session across an entire competitive season. RT was prescribed in 3 weekly mesocycles with tonnage (in kilograms) lifted recorded as RT performance. Endurance and RT sessions were interspersed by different recovery durations: ∼20 min and 1, 2, and 3 h. Fixed- and mixed-effect linear models assessed the influence of skills/endurance-running loads on RT performance. Models also accounted for season period (preseason vs in-season) and recovery duration between concurrent training bouts. Results: An increase in high-speed running and distance covered >75% and >85% of maximal velocity had the greatest reductions on RT performance. In-season total distance covered displayed greater negative effects on subsequent RT performance compared with preseason, while ∼20-min recovery between skills/endurance and RT was associated with greater reductions in RT performance, compared with 1-, 2-, and 3-h recovery. Conclusions: Sport-specific endurance-running loads negatively affect subsequent same-day RT performance, and this effect is greater in-season and with shorter recovery durations between bouts.
Detailed accounts of the training programs followed by today’s elite triathletes are lacking in the sport-science literature. This study reports on the training program of a world-class female triathlete preparing to compete in the London 2012 Olympic Games. Over 50 wk, she performed 796 sessions (303 swim, 194 bike, 254 run, 45 strength training), ie, 16 ± 4 sessions/wk (mean ± SD). Swim, bike, and run training volumes were, respectively, 1230 km (25 ± 8 km/wk), 427 h (9 ± 3 h/wk), and 250 h (5 ± 2 h/wk). Training tasks were categorized and prescribed based on heart-rate values and/or speeds and power outputs associated with different blood lactate concentrations. Training performed at intensities below her individual lactate threshold (ILT), between the ILT and the onset of blood lactate accumulation (OBLA), and above the OBLA for swim were 74% ± 6%, 16% ± 2%, 10% ± 2%; bike 88% ± 3%, 10% ± 1%, 2.1% ± 0.2%; and run 85% ± 2%, 8.0% ± 0.3%, 6.7% ± 0.3%. Training organization was adapted to the busy competition calendar (18 events, of which 8 were Olympic-distance triathlons) and continuously responded to emerging information. Training volumes were 35–80% higher than those previously reported for elite male and female triathletes, but training intensity and tapering strategies successfully followed recommended best practice for endurance athletes. This triathlete placed 7th in London 2012, and her world ranking improved from 14th to 8th at the end of 2012.
Arne Guellich and Stephen Seiler
To compare the intensity distribution during cycling training among elite track cyclists who improved or decreased in ergometer power at 4 mM blood lactate during a 15 wk training period.
51 young male German cyclists (17.4 ± 0.5 y; 30 international, 21 national junior finalists) performed cycle ergometer testing at the onset and at the end of a 15 wk basic preparation period, and reported their daily volumes of defined exercise types and intensity categories. Training organization was compared between two subgroups who improved (Responders, n = 17; ΔPLa4⋅kg-1 = +11 ± 4%) or who decreased in ergometer performance (Non-Responders, n = 17; ΔPLa4⋅kg-1 = –7 ± 6%).
Responders and Non-Responders did not differ significantly in the time invested in noncycling specific training or in the total cycling distance performed. They did differ in their cycling intensity distribution. Responders accumulated significantly more distance at low intensity (<2 mM blood lactate) while Non-Responders performed more training at near threshold intensity (3–6 mM). Cycling intensity distribution accounted for approx. 60% of the variance of changes in ergometer performance over time. Performance at t1 combined with workout intensity distribution explained over 70% of performance variance at t2.
Variation in lactate profle development is explained to a substantial degree by variation in training intensity distribution in elite cyclists. Training at <2 mM blood lactate appears to play an important role in improving the power output to blood lactate relationship. Excessive training near threshold intensity (3–6 mM blood lactate) may negatively impact lactate threshold development. Further research is required to explain the underlying adaptation mechanisms.
Hongjun Yu, Xiaoping Chen, Weimo Zhu, and Chunmei Cao
To examine the effectiveness of threshold and polarized models in the training organization of Chinese top-level sprint speed skaters using a 2-y quasi-experimental design.
Two years (2004–05 and 2005–06 seasons) of the Chinese national speed-skating team’s daily training load (N = 9; 5 men, 23.6 ± 1.7 y, weight 76.6 ± 4.1 kg, competitive experience 5.0 ± 0.8 y, 500-m time 35.45 ± 0.72 s, 1000-m time 71.18 ± 2.28 s; 4 women, 25.3 ± 6.8 y, 73.0 ± 8.5 kg, 6.3 ± 3.5 y, 37.81 ± 0.46 s, 75.70 ± 0.81 s) were collected and analyzed. Each season’s training load included overall duration (calculated in min and km), frequency (calculated by overall sessions), and training intensity (measured by ear blood lactate or estimated by heart rate), Their performances at national, World Cup, and Olympic competitions during the 2 seasons (2004–06), as well as lactate data measured 15 and 30 min after these competitions, were also collected and analyzed. Based on the lactate data (<2, 2–4, >4 mmol/L), training zones were classified as low, moderate, and high intensity.
The total durations and frequencies of the training load were similar across the seasons, but a threshold-training model distribution was used in 2004–05, and a polarized-training-load organization in 2005–06. Under the polarized-training model, or load organization, all speed skaters’ performance improved and their lactate after competition decreased considerably.
Training-intensity distribution based on a polarized-training model led to the success in top Chinese sprint speed skaters in the 2005–06 season.
Guellich Arne, Seiler Stephen, and Emrich Eike
To describe the distribution of exercise types and rowing intensity in successful junior rowers and its relation to later senior success.
36 young German male rowers (31 international, 5 national junior finalists; 19.2 ± 1.4 y; 10.9 ± 1.6 training sessions per week) reported the volumes of defined exercise and intensity categories in a diary over 37 wk. Training categories were analyzed as aggregates over the whole season and also broken down into defined training periods. Training organization was compared between juniors who attained national and international senior success 3 y later.
Total training time consisted of 52% rowing, 23% resistance exercise, 17% alternative training, and 8% warm-up programs. Based on heart rate control, 95% of total rowing was performed at intensities corresponding to <2 mmol·L-1, 2% at 2 to 4 mmol·L-1, and 3% at >4 mmol·L-1 blood lactate. Low-intensity work remained widely unchanged at ~95% throughout the season. In the competition period, the athletes exhibited a shift within <2 mmol exercise toward lower intensity and within the remaining ~5% of total rowing toward more training near maximal oxygen consumption (VO2max) intensity. Retrospectively, among subjects going on to international success 3 y later had their training differed significantly from their peers only in slightly higher volumes at both margins of the intensity scope.
The young world-class rowers monitored here exhibit a constant emphasis on low-intensity steady-state rowing exercise, and a progressive polarization in the competition period. Possible mechanisms underlying a potential association between intensity polarization and later success require further investigation.
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.
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.
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.
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).
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.