This article reviews the major physiological and performance effects of aerobic high-intensity and speed-endurance training in football, and provides insight on implementation of individual game-related physical training. Analysis and physiological measurements have revealed that modern football is highly energetically demanding, and the ability to perform repeated high-intensity work is of importance for the players. Furthermore, the most successful teams perform more high-intensity activities during a game when in possession of the ball. Hence, footballers need a high fitness level to cope with the physical demands of the game. Studies on football players have shown that 8 to 12 wk of aerobic high-intensity running training (>85% HRmax) leads to VO2max enhancement (5% to 11%), increased running economy (3% to 7%), and lower blood lactate accumulation during submaximal exercise, as well as improvements in the yo-yo intermittent recovery (YYIR) test performance (13%). Similar adaptations are observed when performing aerobic high-intensity training with small-sided games. Speed-endurance training has a positive effect on football-specific endurance, as shown by the marked improvements in the YYIR test (22% to 28%) and the ability to perform repeated sprints (~2%). In conclusion, both aerobic and speed-endurance training can be used during the season to improve high-intensity intermittent exercise performance. The type and amount of training should be game related and specific to the technical, tactical, and physical demands imposed on each player.
F. Marcello Iaia, Rampinini Ermanno, and Jens Bangsbo
Frank Nugent, Thomas Comyns, Alan Nevill, and Giles D. Warrington
that large amounts of practice, typically around 11 to 20 hours per week, are required to develop efficient stroke mechanics. 2 , 3 , 7 In recent years, a number of studies have investigated the effects of a low-volume, high-intensity training (HIT) program versus a low-intensity, high-volume training
Nivash Rugbeer, Demitri Constantinou, and Georgia Torres
poor quality of life, and premature death. 6 High-intensity training has become a popular exercise choice among overweight and obese persons. 7 High-intensity training is categorized as either high-intensity interval training (HIIT) and sprint interval training (SIT). 8 HIIT incorporates high
Petros G. Botonis, Ioannis Malliaros, Gavriil G. Arsoniadis, Theodoros I. Platanou, and Argyris G. Toubekis
defensive actions, and decision making is crucial for performance. Hence, in this aspect, sport-specific drills appear more favorable than swimming itself for water polo. Furthermore, the application of long-interval high-intensity training using water polo–specific ball drills may be more effective as it
David T. Martin, Mark B. Andersen, and Ward Gates
This study examined whether the Profile of Mood States questionnaire (POMS) is a useful tool for monitoring training stress in cycling athletes. Participants (n = 11) completed the POMS weekly during six weeks of high-intensity interval cycling and a one-week taper. Cycling performance improved over the first three weeks of training, plateaued during Weeks 4 and 5, decreased slightly following Week 6, and then significantly increased during the one-week taper. Neither the high-intensity interval training nor the one-week taper significantly affected total mood or specific mood states. POMS data from two cyclists who did not show improved performance capabilities during the taper (overtraining) were not distinctly unique when compared to cyclists who did improve. Also, one cyclist, who on some days had the highest total mood disturbance, responded well to the taper and produced his best personal effort during this time period. These findings raise questions about the usefulness of POMS to distinguish, at an individual level, between periods of productive and counterproductive high-intensity training.
Lorenzo Pugliese, Simone Porcelli, Matteo Bonato, Gaspare Pavei, Antonio La Torre, Martina A. Maggioni, Giuseppe Bellistri, and Mauro Marzorati
Recently, some studies have suggested that overall training intensity may be more important than training volume for improving swimming performance. However, those studies focused on very young subjects, and/or the difference between high-volume and high-intensity training was blurred. The aim of this study was to investigate in masters swimmers the effects of manipulation of training volume and intensity on performance and physiological variables.
A group of 10 male masters swimmers (age 32.3 ± 5.1 y) performed 2 different 6-wk training periods followed by 1 wk of tapering. The first period was characterized by high training volume performed at low intensity (HvLi), whereas the second period was characterized by low training volume performed at high intensity (LvHi). Peak oxygen consumption (V̇O2peak) during incremental arm exercise, individual anaerobic threshold (IAT), and 100-m, 400-m, and 2000-m-freestyle time were evaluated before and at the end of both training periods.
HvLi training significant increased V̇O2peak (11.9% ± 4.9% [mean change ± 90%CL], P = .002) and performance in the 400-m (–2.8% ± 1.8%, P = .002) and 2000-m (–3.4% ± 2.9%, P = .025), with a likely change in IAT (4.9% ± 4.7%, P > .05). After LvHi training, speed at IAT (12.4% ± 5.3%, P = .004) and 100-m performance (–1.2% ± 0.8%, P = .001) also improved, without any significant changes in V̇O2peak, 2000-m, and 400-m.
These findings indicate that in masters swimmers an increase of training volume may lead to an improvement of V̇O2peak and middle- to long-distance performance. However, a subsequent period of LvHi training maintains previous adjustments and positively affects anaerobic threshold and short-distance performance.
Benoit Capostagno, Michael I. Lambert, and Robert P. Lamberts
To determine whether a submaximal cycling test could be used to monitor and prescribe high-intensity interval training (HIT).
Two groups of male cyclists completed 4 HIT sessions over a 2-wk period. The structured-training group (SG; n = 8, VO2max = 58.4 ± 4.2 mL · min−1 · kg−1) followed a predetermined training program while the flexible-training group (FG; n = 7, VO2max = 53.9 ± 5.0 mL · min−1 · kg−1) had the timing of their HIT sessions prescribed based on the data of the Lamberts and Lambert Submaximal Cycle Test (LSCT).
Effect-size calculations showed large differences in the improvements in 40-km time-trial performance after the HIT training between SG (8 ± 45 s) and FG (48 ± 42 s). Heart-rate recovery, monitored during the study, tended to increase in FG and remain unchanged in SG.
The results of the current study suggest that the LSCT may be a useful tool for coaches to monitor and prescribe HIT.
Jan Sommer Jeppesen, Jeppe F. Vigh-Larsen, Mikkel S. Oxfeldt, Niklas M. Laustsen, Magni Mohr, Jens Bangsbo, and Morten Hostrup
J . 1993 ; 15 : 44 – 46 . 10.1519/0744-0049(1993)015<0044:APAOIH>2.3.CO;2 30. Hostrup M , Onslev J , Jacobson GA , Wilson R , Bangsbo J . Chronic β 2 -adrenoceptor agonist treatment alters muscle proteome and functional adaptations induced by high intensity training in young men . J
Pål Haugnes, Jan Kocbach, Harri Luchsinger, Gertjan Ettema, and Øyvind Sandbakk
with the skating style among 7 elite male junior cross-country skiers. diff indicates difference; LIT, low-intensity training; MIT, moderate-intensity training; HIT, high-intensity training. Table 2 Skiing Time, Speed, Heart Rate, and RPE Over the Total Course and Different Terrains While 5-km Cross
Heidi R. Thornton, Grant M. Duthie, Nathan W. Pitchford, Jace A. Delaney, Dean T. Benton, and Ben J. Dascombe
To investigate the effects of a training camp on the sleep characteristics of professional rugby league players compared with a home period.
During a 7-d home and 13-d camp period, time in bed (TIB), total sleep time (TST), sleep efficiency (SE), and wake after sleep onset were measured using wristwatch actigraphy. Subjective wellness and training loads (TL) were also collected. Differences in sleep and TL between the 2 periods and the effect of daytime naps on nighttime sleep were examined using linear mixed models. Pearson correlations assessed the relationship of changes in TL on individuals’ TST.
During the training camp, TST (–85 min), TIB (–53 min), and SE (–8%) were reduced compared with home. Those who undertook daytime naps showed increased TIB (+33 min), TST (+30 min), and SE (+0.9%). Increases in daily total distance and training duration above individual baseline means during the training camp shared moderate (r = –.31) and trivial (r = –.04) negative relationships with TST.
Sleep quality and quantity may be compromised during training camps; however, daytime naps may be beneficial for athletes due to their known benefits, without being detrimental to nighttime sleep.