In: World Book of Swimming: From Science to Performance ISBN: 978-1-61668-202-6 Editors: L. Seifert, D. Chollet and I.Mujika ©2011 Nova Science Publishers, Inc.

Chapter 18

TRAINING LOAD AND PERFORMANCE IN SWIMMING Jean-Claude Chatard1 and Andrew M Stewart2 1

Laboratoire de Physiologie Clinique et de l’Exercice, Faculté de Médecine de Saint-Etienne, France, 2 Department of Osteopathy, Faculty of Social and Health Sciences Unitec New Zealand

ABSTRACT More than three quarters of all competitive swimming events are completed in less than two and a half minutes by athletes of at least national class. To prepare for these events, coaches manipulate training load (usually described as a combination of volume, intensity, frequency, and dry-land training) at various times of the season in an attempt to prepare their swimmers to peak just at the right time. Leading into competition, there is usually a phase of high load training followed by some kind of tapering (reduced load) program. Scientific data support bigger performance gains through a program based on high intensity and low volume prior to a high-load phase and taper phase leading into competition. Individual athletes will respond differently to such fluctuations in training load and will depend on parameters such as training status at the time and performance level. Individual responses can be monitored using simple observational or monitoring techniques, regression analysis, or with the help of a systems model. These analytical processes may be useful tools to establish individualized training programs.

Key words: fatigue, fitness, taper, super compensation, mathematical model

1. INTRODUCTION Most competitive swimming events are completed in a relatively short period of time (less than two and a half minutes by athletes of national standard or better). Preparation for competing in these events usually involves varying the training load at various times during the season to have the swimmer peak at the desired moment. This training load is usually described as a combination of volume swum, intensity of effort, frequency of workout, and dry-land training (30). The premise of most traditional coaching programmes has been to lay

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down an initial base of fitness at the start of the season, then to gradually increase the training load to accelerate fitness gains and stress the athlete to a point close to breakdown, then to back off the training load through a tapering phase that allows recovery in time for optimum performance at the chosen competition. The aim of this chapter is twofold: First, to discuss the most effective combination of each of the factors contributing to training load during various phases of the season that may lead to an optimum enhancement in performance. Second, to indicate that training load and performance data can be useful tools for estimating the individual adaptation profiles either by means of simple observations, statistical analyses, or a systems model.

2. MEASUREMENT OF TRAINING LOAD Training load is ultimately the combination of volume swum, intensity of effort, frequency of workout, and dry-land training. The volume of training undertaken by elite swimmers ranges usually from around 10-12 km.d-1 during light-load periods up to 15-20 km.d-1 during high-load phases over either two or three sessions per day (11, 25, and 48). 80

% of total swimming distance

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Training Intensity Figure 1. Mean ± SD percentage of total swimming distance covered at each intensity level (30).

For example, it has been reported that the Sydney and Athens 1500 m Olympic Champion, Grant Hackett, swam between 2400 km and 2800 km per year from 1995 to 2004. Training intensity has been measured in several ways; including heart rate, oxygen uptake, swim pace, percent effort, and blood lactate concentration. The most valid and reliable of these measures appears to be swimming pace as most physiologically-based measures are too slow to react to non steady-state conditions. One exception appears to be the use of blood

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lactate concentration, even though its response time to changing intensity is somewhat slow (minutes). Several authors have used such a measure to beneficial effect during progressive incremental step tests (16, 30, and 35). In particular, Mujika et al. (30) have defined five ranges of blood lactate concentration: intensity I is swimming speed close to 2 mM; intensity II is speed close to 4 mM; intensity III speed close to 6 mM; intensity IV highly lactic swimming (10 mM); and intensity V maximal intensity sprint swimming. Training frequency can be quantified either by the number of training sessions or the number of half days of rest. One hour dry-land training has been empirically considered equivalent to 1 km swum at intensity I, 0.5 km at intensity IV, and 0.5 km at intensity V using a stress index scale of training load and blood lactate concentration over different training sets (30). Using the above training load factors, Mujika et al. (30) measured a mean (± SD) training volume of 1126 ± 222 km, a training frequency of 316 ± 44 half days of rest (range from 264 to 370), and 1108 ± 828 min (range from 0 to 2415) of dry-land training in a group of 18 international French swimmers for a complete season of training. The percentages of the total distance covered over the season at each intensity are presented in Figure 1.

3. VOLUME OF TRAINING AND PERFORMANCE In competitive swimming, it is generally assumed, though unsubstantiated, that improvements in strength and endurance are proportional to the volume of work performed during training (14). It is the general belief (particularly among coaches) that increased volume produces an adaptive response that directly leads to an improvement in performance. This belief is indoctrinated in most swim coaches to the extent that a progressive increase in training volumes over years is the norm. For example, from 1968 to 1980, a regular increase in training volume from around 1,300-1,700 km per year to around 1,900-3,500 km was observed for elite swimmers (33). In contrast to this approach, the French Swimming Academy recommends an increase in volume only as the swimmer matures, but beyond such an age there is a ‘ceiling effect’ when other factors (primarily intensity) become more the focus to provide the training stimulus (Table 1). Table 1. Recommended daily and weekly training volume for age groups swimmers

daily weekly

10 years 3.5 - 4 km 20 km

11-12 years 4 - 4.5 km 25 km

13-14 years 4.5 - 5.5 km 30 km

15-16 years 5.5 - 10 km 35-40 km

> 17 years 6 - 10 km 45 - 60 km

Rigorous scientific investigation over the last 20 years or so, has questioned this volumebased philosophy. In 1995, Mujika et al. (30) found that training volume, ranging from 749 km to 1475 km for a season did not significantly correlate with performance in 18 international sprint swimmers. Stewart and Hopkins (42) followed the training practices of 24 highly-qualified coaches and 185 of their national age-group swimmers over two consecutive seasons. This study concluded that periodization of training and differences in training between sprint and middle-distance events were broadly in accord with principles of specificity, but that strong effects of specificity of training on performance were not apparent. Stewart and Hopkins (42) also noted that the majority of training for most of the season was

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freestyle-based (on average from 46% to 62%), which is counterintuitive to stroke or distance speciality (43). This result highlights the practice of ‘filler mileage’ within training prescription (additional slow to moderate pace swimming to make up the target volume for the session). Costill et al. (14) investigated the effects of doubling training volume for a group of swimmers from 5 km.d-1 to 9.4 km.d-1 for six weeks, while another group continued to train normally. The results showed that the larger training volumes neither increased aerobic or anaerobic capacities, while maximal sprinting velocity and performance were decreased. Moreover, a 50% reduction in training volume (4.5 km.d-1 vs 8.7 km.d-1) over two competitive seasons resulted in improved swimming power and performance, with no changes in V O2max or blood lactate concentration after a standardized swim (11). In a more recent study (15), Faude et al. implemented a randomized cross-over trial of 10 weeks. During this time national-level age-group swimmers performed a four-week period consisting of either high-volume or high-intensity workouts. The intervention period was then followed by an identical taper in each group. Results clearly showed no advantageous effect of additional volume on performance in 100m or 400m swims and similar performance gains were noted for both groups three months post-study. Taken together, these results agree with previously reported data concerning the influence of training volume on the adaptation to training in competitive swimmers (11, 12, 13, and 24). In all these studies, the authors suggest that in highly trained swimmers, increased volume ultimately loses its capacity to stimulate adaptation beyond some critical training threshold, while training intensity becomes the key parameter to produce a further positive response. It might be concluded from previous observations that low intensity training is not useful for short distance swimmers. It may be possible that a high volume of low intensity training could improve the recovery process and thus make high intensity training easier to tolerate (39), however, such a possibility has yet to be rigorously studied. Gliding ability in the water could also be developed with increased low intensity training, with a consequent reduction in the energy cost of swimming (9, 39). After several weeks or months of high volume training, a short period of gradually reduced training load of around two to four weeks (taper) results in vastly improved performances (11, 22, 25, and 28). Mujika, et al. (30) found that the reduction in training volume during the taper was related to performance improvements (Figure 2A). Studies by Stewart et al. (41) and Stewart and Hopkins (42) found similar results. The key question here relates to what aspect(s) of overall training load should be reduced. Banister and Calvert (5) indicated that training impulse engenders fitness states, but also fatigue that limits the performance. As fatigue has a shorter time constant than fitness, reducing the quantity of training over the tapering period improves the performance as the body learns to “supercompensate” in a classical biological adaptive response. It is suggested that the key element of training load that has to be retained is that of intensity to maintain fitness levels. The overall load could still be reduced by a combination of less frequency and lower volumes. The ‘art’ of coaching is to manipulate this load to suit the individual needs of the swimmer and in time for peak performance to occur at the desired moment at the end of the taper (45).

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Figure 2. A - Relationship between the improvement in performance and the percentage reduction in training volume (mean pre-taper weekly volume vs. mean weekly volume during the taper) during a 3week taper. B - Relationship between the improvement in performance throughout the follow-up training season and the mean intensity of training, MITS (30). FS=12 Performance (% pace)

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Figure 3. Simple recording of the performances and volumes of training, measured during normal training sessions and averaged per week (10). FS = Fatigue Score. When over 20 points, it indicates a state of fatigue. These measurements allowed to distinguish a 3-wk overreaching period (weeks 19-21) and an 11-wk overtraining period (weeks 35-45).

Tapering periods from four to 28 days may be linear or by steps (22, 28). A 14-day taper consisting of a progressive reduction in swimming training volume from about 9 km.day-1 to about 3 km.day-1 resulted in increased power on both a biokinetic swim bench (17.7%) and a power swim apparatus (24.6%). The taper had no influence on acid-base balance after a standardized 183-m swim and competition performance times improved by an average of 3.1% (9). Improvements in muscular power (≈ 5%) and performance (≈ 3%) after two to four

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weeks of reduced volume taper have also been reported in other studies concerning competitive swimmers (8, 14, and 22). A number of different methods have been utilized to monitor individual responses to training loads. These methods have included various enzyme markers, monitoring immune status, endocrine assays, and heart rate variability (18, 36, and 34). None of these markers though seem to temporally track training status and performance as accurately as the swimmers’ psychological response. As a consequence, regular and brief questionnaires of fatigue and mood states may help to quantify the tolerance of swimmers to training (Table 2). Such questionnaires have been demonstrated to relate to variations of training and performance (10, 18, and 19) and are considered better markers than physiological assays. An example of the use of such monitoring can be found in Figure 3. Table 2. Description of the eight items of the questionnaire of fatigue in English, Arabic, and French. A total score over 20 points indicates a state of fatigue (10). Answer the 8 questions: The previous week….. ....‫ ﺍﻷﺳﺒﻮﻉ ﺍﻟﻤﺎﺿﻲ‬:‫ﺃﺟﺐ ﻋﻦ ﺍﻷﺳﺌﻠﺔ ﺍﻟﺘﺎﻟﻴﺔ‬ Repondre aux 8 questions: Cette semaine …

No.

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2. 3. 4. 5.

6.

7.

8.

Rating Scale ____________________________________ Questions No Average Yes ‫ﺍﻷﺳﺌﻠﺔ‬ I found training more difficult than usual ‫ﺃﺟﺪ ﺃﻥ ﺍﻟﺘﺪﺭﻳﺐ ﺃﻛﺜﺮ ﺻﻌﻮﺑﺔ ﻣﻦ ﺍﻟﻤﻌﺘﺎﺩ‬ 1 2 3 4 5 6 7 J’ai trouvé l’entraînement plus difficile I slept more ‫ﺃﻧﺎﻡ ﺃﻛﺜﺮ‬ J’ai plus dormi 1 2 3 4 5 6 7 My legs felt heavy ‫ﺷﻌﺮﺕ ﺑﺄﻥ ﺃﺭﺟﻠﻲ ﺛﻘﻴﻠﺔ‬ Mes jambes étaient plus lourdes 1 2 3 4 5 6 7 I caught cold/infection/flue ‫ ﺍﻟﺰﻛﺎﻡ‬/‫ﺃﺻﺒﺖ ﺑﺎﻟﺒﺮﺩ‬ J’ai attrapé froid ou eu une infection 1 2 3 4 5 6 7 My concentration was poorer than usual ‫ﻗﺪﺭﺗﻲ ﻋﻠﻰ ﺍﻟﺘﺮﻛﻴﺰ ﻛﺎﻧﺖ ﺃﻗﻞ ﻣﻦ ﺍﻟﻤﻌﺘﺎﺩ‬ 1 2 3 4 5 6 7 Ma concentration était plus difficile I worked less efficiently than usual ‫ﻋﻤﻠﻲ ﻛﺎﻥ ﺃﻗﻞ ﻛﻔﺎءﻩ ﻋﻦ ﺍﻟﻤﻌﺘﺎﺩ‬ 1 2 3 4 5 6 7 J’ai travaillé moins efficacement I felt more anxious or irritable than usual ‫ﺷﻌﺮﺕ ﺑﺎﻟﻘﻠﻖ ﻭﺍﻟﺘﻮﺗﺮ ﺃﻛﺜﺮ ﻣﻦ ﺍﻟﻤﻌﺘﺎﺩ‬ 1 2 3 4 5 6 7 Je me suis senti plus anxieux et irritable I had more stress at home, school, training ‫ ﺃﺛﻨﺎء ﺍﻟﺘﺪﺭﻳﺐ‬،‫ ﺍﻟﻤﺪﺭﺳﺔ‬،‫ﺷﻌﺮﺕ ﺑﺎﻹﺟﻬﺎﺩ ﻓﻲ ﺍﻟﺒﻴﺖ‬ 1 2 3 4 5 6 7 J’ai été plus stressé à la maison ou à l’école

4. INTENSITY OF TRAINING AND PERFORMANCE Mujika et al. (30) found that mean intensity of the training season was the major parameter influencing the improvement in performance throughout the season (Figure. 2B), in international sprint swimmers. This relationship is in accordance with previous reports

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indicating that the intensity of training is the key factor in producing a training effect in welltrained athletes (1, 27, 32, and 38). Different experimental results suggest that specific high intensity anaerobic training could be included in the training programs for short distance swimmers; especially early to mid-season in preparation for the high-load phase prior to the taper. When an exercise lasts from around one to two minutes (most 100m and 200m swimming events), the relative part of anaerobic energy release varies approximately between 35% and 60% (26). It is questionable, however, whether this possibility could be extended to apply to swimmers of longer distances (e.g. 400m, 800m, and 1500m), since training volume could be much more important for those swimmers than for the short distance swimmers. During the taper, maintenance of training intensity appears to be necessary to avoid detraining, provided that reductions in other training characteristics allow sufficient recovery to optimize performance (28). However, the taper should not be considered the time to increase the total sprinting distance. As other components of training load (i.e. frequency and volume) are reduced, the absolute amount of sprinting must be reduced during the taper in order to allow time for recovery (25). The subtlety in the art of effective tapering is that the percent of total training volume prescribed as high-intensity training may actually increase up to (but not beyond) some critical threshold for the individual swimmer (41, 45). Van Handel and co-workers (48) studied a group of elite swimmers during 60 days of long-course training and 20 days of taper. Training volume dropped from 11 km.day-1 to 2.5 km.day-1 during the taper, while training intensity was held constant or increased. They observed an absolute increase in V O2max and a shift to the right of the blood lactate versus swimming velocity curve during training, with no further significant changes during the taper, but a non significant curve shift back to the left. Based on their own data and previously reported results (mainly those of Costill’s group), these authors suggested that the absolute volume of high-intensity training may also be reduced to further optimize the effects of taper by allowing adequate rest and recovery. Unfortunately, data on swimming performance during the different phases of training were not reported in the study.

5. TRAINING PRESCRIPTION AND COMPLIANCE There are a variety of means to prescribe and monitor training load. Volume swum, number of repetitions, rest intervals, and frequency of training are straightforward (Figure 4), but the intensity of training is somewhat problematic. Most physiological measures take several minutes to attain steady state, whereas most swim training is conducted using repeat short bouts (interval training) so the interval is usually completed before physiology has accurately ‘tracked’ the intensity. Incremental blood lactate step tests have been used (2, 3, and 30) that work well, but the exact mechanism of how such a measure tracks non-steady state intensity is little understood. Indeed, in the studies by Anderson et al. (2, 3) and Pyne et al. (35), it was reported that while physiological monitoring was shown to be a useful means to track performance during test sets, there was little relationship between the use of such blood lactate testing and competition performance. Furthermore, it appears that only large changes in competition performance are able to be predicted through the use of physiologic monitoring and/or training prescription (2, 3, 30, and 42).

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© 2001 A M Stewart & W G Hopkins

training for…

Recording Form for a Set of Swimming Reps

1 = sprint 2 = m.d. 3 = both

Place: ______________________ Swimmer: ______________________

coach

swimmer

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training for… 1,2,3 free

Date: _________________

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Figure 4. Part of a data coding sheet to quantify training (40).

From a practical point of view, training pace is a good (arguably the most valid) marker of training intensity (47). In such a case, the best method for quantifying training is direct observation of swimmers (40). An example of how to use training pace can be seen in Figure 5. Even though there exists a substantial body of knowledge relating to popular training prescription and substantial evidence calling for greater application of the principles of specificity in training, there is little mention in the literature of the compliance of swimmers and coaches to such training practices and scientific intervention. One such study of compliance (40) found that swimmers adhere closely to all aspects of training load, except intensity. Considering that this aspect of training is arguably the most crucial, such a result is somewhat of a concern. Similarly, coaches do not appear to comply strongly with scientific intervention (41). Until coaches comply with the application of scientific interventions and swimmers comply with training prescription, the effects of studies investigating the impact of specificity on swim performance will remain somewhat unclear.

6. INDIVIDUAL RESPONSE TO TRAINING The individual response to training depends, to a great extent, on the level of fitness and practice of the subjects. Mujika et al. (30) found a highly significant correlation between the initial level of performance and the improvement in performance during the season (Figure 6A). Furthermore, the percentage loss in performance between the end of the previous season and the beginning of the new season was significantly different for the swimmers that improved their personal best times (fast) than for the others (slow, Figure 6B). No significant differences existed in training volume, intensity, frequency or dry-land training between groups. From these results, it could be suggested that in spite of good adaptation to training,

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the best performance achieved depended less on the effects of training than on the influence of previous detraining. However, the reason why some swimmers were more detrained than others was not explored. CURRENT

VERY HARD

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20.2 22.2 24.2 26.3 28.3 30.3 32.3 34.3 36.4 38.4 40.4 42.4 44.4 46.5 48.5 50.5 52.5 54.5 56.6 58.6

20.6 22.4 24.5 26.5 28.6 30.6 32.6 34.7 36.7 38.8 40.8 42.8 44.9 46.9 49.0 51.0 53.0 55.1 57.1 59.2

20.6 22.7 24.7 26.8 28.8 30.9 33.0 35.0 37.1 39.1 41.2 43.3 45.3 47.4 49.4 51.5 53.6 55.6 57.7 1.00

20.8 22.9 25.0 27.0 29.1 31.2 33.3 35.4 37.4 39.5 41.6 43.7 45.8 47.8 49.9 52.0 54.1 56.2 58.2 1.00

21.2 23.3 25.4 27.6 29.7 31.8 33.9 36.0 38.2 40.3 42.4 44.5 46.6 48.8 50.9 53.0 55.1 57.2 59.4 1.01

21.6 23.8 25.9 28.1 30.2 32.4 34.6 36.7 38.9 41.0 43.2 45.4 47.5 49.7 51.8 54.0 56.2 58.3 1.00 1.03

22.0 24.2 26.4 28.6 30.8 33.0 35.2 37.4 39.6 41.8 44.0 46.2 48.4 50.6 52.8 55.0 57.2 59.4 1.02 1.04

22.4 24.6 26.9 29.1 31.4 33.6 35.8 38.1 40.3 42.6 44.8 47.0 49.3 51.5 53.8 56.0 58.2 1.00 1.03 1.05

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Figure 5. Part of a pace chart used for prescribing and monitoring intensity (40).

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Figure 6. Relationship between the improvement in performance throughout a follow-up training season, the initial performance (A) and the best of the previous season (B) (30).

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Individual adaptation profiles can be estimated from swimming training and performance data either by means of simple and stepwise regression analysis or with the help of a systems model. Mujika et al. (29) used regression analysis to indicate that for some swimmers, several training variables were correlated with a decline in swimming performance, while for other swimmers these relationships were very scant. This observation could indicate that the former swimmers had a higher sensitivity to the training stimulus than the latter. The analysis of the relationships between the training variables and the variations in performance for each swimmer could thus be a helpful tool for coaches and swimmers in order to establish individualized training programs based on individual adaptation profiles, especially during periods of taper. Avalos et al. (4) and Hellard et al. (17) used mixed linear modelling instead of the accepted Bannister (6) model to account for the residual effects of different training loads at various times of the season. From these models, the authors concluded that the training of individuals and groups of swimmers (by stroke and/or by distance) closely tracked changes in performance over several seasons. In a practical sense, Stewart et al. (45) followed the performances of 25 age-group swimmers (ranging from 14 to 17 yrs and seasonal best performances of ≈ 80% world-record pace) over several seasons and monitored their compliance to the training prescription. From this approach, it would appear that there may be an additional positive effect (≈ 1 to 1.5%) of tapering for swimmers who comply strongly to the training prescription throughout the season as opposed to those who comply moderately or poorly. These results have yet to be rigorously verified. Systems models assume that performance can be estimated from the difference between a positive gain ascribed to the adaptation to exercise and a negative gain as a result of the negative effects of the training load (5, 7, 29, and 31). Negative and positive influences may represent respectively fatigue and fitness accumulated in response to training. The main advantage of the mathematical models from a practical point of view is that they allow an evaluation of the individual’s adaptation processes. For example, the time required following a training stimulus for the effect of fatigue to dissipate may be calculated and the optimum duration of the taper for each subject estimated. In this respect, values ranging from 12 to 32 days were reported (28). An individual example of data analyzed by means of a systems model is given in Figure 7.

Figure 7. Comparison between the real and modelled performances (A). Positive and negative influence calculated by the systems model from the training load and the performance variations (B) (29).

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7. PERFORMANCE PROGRESSION AND VARIABILITY International competitive swimming has become essentially a year-round competitive sport. Indeed, there is really little (if any) off-season as competitions (either short course or long course) have sprung up around the world. In addition, the current format of heats, semifinals, and finals is relatively recent. It was not that long ago when the top eight swimmers progressed direct from heat swims to a final, with those ranked 9 through 16 from the heats entering the ‘B’ final. These relatively recent changes within the sport have placed a considerably different requirement on swimmers’ preparation to such an extent that progression through the various qualifying swims within a competition and consistency of performance between competitions has now become the subject of research focus. Pyne et al. (37), Stewart and Hopkins (43), and Trewin et al. (46) have conducted studies that investigated the relationships between performance and rankings within and between competitions for swimmers ranging in ability from junior age-group through to Olympic-level athletes. These studies have stemmed from work by Hopkins (20) and Hopkins et al. (21) in which it was found that the smallest worthwhile enhancement in performance that would affect an athlete’s chance of winning a medal was approximately 0.5 of the within-athlete coefficient of variation (CV), the percent random variation in performance. It is not surprising to note that the more experienced international swimmers are more consistent in their performances (37, 46) than their junior national-level counterparts (43), but within a major competition such as an Olympic final there appears to be negligible difference in consistency between swimmers. Another interesting finding is that consistency of performance between events within the same competition is greater for the more-experienced swimmer. The authors of these studies (37, 43, and 46) conclude that while junior national-level swimmers appear to cope better with the physiological challenge of a different distance (for a given stroke) rather than the technical challenge of a different stroke (for a given distance), top international swimmers (such as Olympians) are equally adept at alternating between events differing in distance and stroke. Such a reality then presents a different challenge to the swimmer and coach in terms of deciding which events to enter in any given competition and therefore how to base their preparation in the season(s) leading into that particular ‘swim meet’. The phenomenal achievement of Michael Phelps at the 2008 Olympic Games is testimony to such practice.

8. PRACTICAL APPLICATIONS This chapter has discussed in depth many factors relating to training load and performance in swimmers. From all the issues presented, there is overwhelming evidence to indicate that workouts need to be structured in such a way as to train only the power systems or skills required for a swimmer’s specialty event(s) throughout the season. In light of this evidence, several authors have suggested alternate and more-specific periodized training regimes than have previously been utilized (23, 44). In the model proposed by Issurin et al. (23), block periodization is suggested whereby specialized meso-cycles are designed in sequence during which training is highly-concentrated and athletes focus on only a few technical skills in any given cycle. The key difference from the block approach is that

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physical attributes required for competition are developed sequentially as opposed to simultaneously, which leads to superimposed training effects focussing on a singular competition at the end of a given cycle rather than over a competition period. Stewart et al. (44) have suggested that swimmers should be prepared close to the point of over-reaching during a build-up phase. The training load during this phase should be such that swimmers recover on a day-to-basis and there would be small gains in performance (which could be measured in regular training sets) from week to week. Following this initial phase there should be a short phase (one to two weeks) to overload the swimmers. During this phase there would likely be a brief improvement in performance in the first few days, but the continuation of such training over another week or two would eventually lead to a downturn in performance (as measured by decrements in training set times and a change in mood states of swimmers). During this overload phase, the focus is improving the relative fitness of the swimmers, but such improvements are masked by the fatigue effects of the additional training load. When such detrimental effects appear, swimmers should start tapering, through a reduction in overall training load. Such a reduction should focus on a reduction in training volume, not so much a reduction in intensity of workouts. To accommodate the practicalities of such a shift in training philosophy, it is suggested that coaches look for areas in their prescription where ‘filler mileage’ could be reduced and focus more on the specific event (stroke and distance) for which the swimmer is aiming to peak.

CONCLUSION In swimming, scientific data indicate that in highly trained swimmers training intensity becomes the key parameter to optimize performance rather than training volume. However, the individual response to training depends, to a great extent, on the level of fitness and practice of the individuals. This response can be calculated with the help of simple observation, regression analysis, or a systems model, as a useful tool to establish individualized training programs.

ACKNOWLEDGMENTS Authors wish to thank the swimming coaches Lucien Lacoste, Frédéric Barale, Jacqueline Legrand, and Michel Paulin for their co-operation and for making valuable suggestions.

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