TRAINING LOAD AND PERFORMANCE IN SWIMMING
0JEAN-CLAUDE CHATARD, 2)INIGO MUJIKA l)Laboratoire de Physiologie, GIP Exercice, Faculte de Medecine, Saint-Etienne, France
2)Departamento de Alto Rendirniento, IVEF, Vitoria-Gasteiz, Basque County, Spain
ABSTRACT
In swimming, training load is usually described as a combination of volume, intensity, frequency and dry land training. Swimmers have progressively increased their amounts of training up to 18 km -d-1, in 2 or 3 sessions per day. However, scientific data indicated that in highly trained swimmers, training volume lose his stimulation capacity beyond a training threshold, while training intensity becomes the key parameter. The individual response to training depends, to a great extent, on the level of fitness and practice of the subjects. This response can be calculated by means of regression analysis or with the help a systems model.
These analyses can be useful tools to establish individualized training programs.
Key words: Performance, exercise, training, over training, fatigue, fitness, taper, systems theory, mathematical model
INTRODUCTION
In swimming, training load is usually described as a combination of volume, intensity, frequency and dry land training (Mujika, et al. 1995). The aim of this key-notes lecture is to answer the question of which of these training components maximizes conditioning and enhances swimming performance. A second aim of this lecture is to indicate that training load and performance data can be useful tool for estimating individual adaptation profiles either by means of simple statistical analyses or systems model.
MEASUREMENT OF TRAINING LOAD
Elite swimmer's volume of training, expressed in km, reaches 10 km·d-1 or more, up to 18 km·d-1, in 2 or 3 sessions per day (Costill1985, Maglischo 1982, Van Handel, et al. 1988).
Training intensity, measured by the relationship velocity- blood lactate concentration, is usually defined by 5 levels (Mujika, et al. 1995): intensity I: swimming speed inferior to 4 mM; intensity II: speed close to 4 mM; intensity ill: speed close to 6 mM; intensity IV: highly lactic swimming (10 mJVI); 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 is empirically considered as equivalent to l km swum at intensity I, 0.5 km at intensity IV and 0.5 km at intensity V. A stress index scale of the training load was proposed by Mujika, et al. (1995), relating to the theoretical blood lactate accumulation levels aimed during the different training sets.
For a complete season of training, Mujika, et al. (1995) measured a mean± SD training volume of 1126 ± 222 km, training frequency 316 ± 44 half days of rest (range from 264 to
370), dry land training 1108 ± 828 min (range from 0 to 2415) in a group of 18 international
French swimmers. The percentages of the total distance covered over the season at each intensity level are presented in Fig. 1.
429

430
70
8]
V
(.)
15
I Speed< B.L.A.T.
II Speed= B.L.A.T. m Speed> B.L.A.T.
N Lactic swimming
V Sprint swimming
10
E
-~ s
.8
<.;...
0
~
5
0
I II m N V
Training Intensity
Figure 1. Mean
SD percentage of total swimming distance covered at each intensity level
(Mujika et al. 1995).
VOLUME OF TRAINING AND PERFORMANCE
In competitive swimming, it is generally assumed, though unsubstantiated, that improvements in strength and endurance during training are proportional to the volume of work performed during training (Costill, et al. 1991).
A recommended daily and weekly training volume for different age groups is presented in 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
It is a general belief that volume produce an adaptative response in the athlete's body, which should directly lead to an improvement in performance. Swimmers have therefore progressively increased their amounts of training. From 1968 to 1980, a regular increase of the training volume training from 1,300- 1,700 km per year to 1,900- 3,500 km was observed for elite swimmers (Platonov 1988).
In 1995, however, Mujika et al. found that training volume, ranging from 749 km to 1475 km for a season did not significantly correlate with performance in 18 international sprinter swimmers. These results, along with previously reported data concerning the influence of training volume on the adaptation to training in competitive swimmers (Costill 1985, Costill, et al. 1985, Costill, et al. 1988, Costill, et al. 1991, Kirwan, et al. 1988). Doubling training volume for a group of swimmers from 5 km·d-1 to 9.4 km·d-1 for 6 weeks, while another group continued to train normally, neither increases aerobic nor 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 V02max or blood lactate concentration after a standardized swim.

These authors suggest that, in highly trained swimmers, volume lose his stimulation capacity beyond a training threshold, while training intensity becomes the key parameter in order to produce a positive training response.
It might be erroneously concluded from the previous observations that low intensity training is not useful for short distance swimmers. A high volume of low intensity training could improve the recovery process and thus make high intensity training easier to tolerate
(Sharp 1993). Gliding ability in the water could also be developed with increased low intensity training, with a consequent reduction in the energy cost of swimming (Chatard, et al. 1990,
Sharp 1993).
After several weeks or months of high volume training a short period of rest, 2 - 4 weeks, called " taper", results in vastly improved performances (Costill 1985, Houmard and Johns
1994, Maglischo 1982, Mujika 1998). Mujika, et al. (1995) found that the reduction in training volume during taper was related with performance improvements (Figure 2). Banister and
Calvert (1980) indicate 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 peaking period improves the performance.
Tapering periods, from 4 to 28 days, may be progressive or by step (Houmard and Johns
1994, Mujika 1998). A 14-day taper consisting of a progressive reduction in swimming training volume from about 9 km 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 3.1 % (Costil1, et al. 1985). Improvements in muscular power("" 5 %) and performance ("" 3 %) after 2 to 4 weeks of reduced volume taper have also been reported in other studies concerning competitive swimmers (Cavanaugh and Musch 1989, Costill, et al.
1991, Johns, et al. 1992).
INTENSITY OF TRAINING AND PERFORMANCE
Mujika, et al. ( 1995) found that mean intensity of the training season was the major parameter influencing the improvement in performance throughout the season (Fig. 2B), in international sprinter swimmers.
<l)
()
§
....
2
<;.)
A..
::;
6
4
A
•
<l)
11
()
:::;
....
~
9
<l)
Q.;
B r=0.69
P<O.Ol
N= 18
•
•
•
•
•
~ i:i
;>
0
.....
0..
.§
0
•
•
• r = 0.()1
P<O.Ol n= 17
•
•
*
*
5 15 25 35 45 1.42 1.47 1.52 1.57 1.62
% reduction in training volume during taper
.5
7
<l) eo
@
..::; u
5
MITS (arbitrary units)
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 taper) during a 3-week taper. B - Relationship between the improvement in performance throughout the follow-up training season and the mean intensity of training, MITS (Mujika, et al.
1985).
431

This relationship is in accordance with previous reports indicating that the intensity of training is the key factor in producing a training effect in well-trained athletes (Acevedo and
Goldfarb 1989, Mikesell and Dudley 1984, Neary, et al. 1992, Rusko 1987)
It is questionable, however, whether this possibility could be extended to apply to swimmers of longer distances (e. g. 400, 800, 1500 m), since training volume could be much more important for those swimmers than for the short distance swimmers.
Different experimental results suggest that specific high intensity anaerobic training could be included in the training programs for short distance swimmers. When an exercise lasts between 1 and 2 rnin, which is the case in the 100 and 200 m swimming events, the relative part of anaerobic energy release varies approximately between 35 and 60 % (Medbf'} and Tabata
1989).
During taper, a maintenance of training intensity appears to be necessary to avoid detraining, provided that reductions in other training characteristics allow sufficient recovery to optimize performance (Mujika 1998). However, taper must not be considered the time to increase sprinting distance. As other types of training are reduced, the amount of sprinting must be reduced during the taper in order to provide time for recovery (Maglischo 1982).
V an Handel and eo-workers (1988) studied a group of elite swimmers during 60 days of long-course training and 20 days of taper. Training volume dropped from 11 km to 2.5 km ·day-
1 during taper, while training intensity was held constant or increased. They observed an absolute increase in V02max and a shift to the right of the blood lactate versus swimming velocity curve during training, with no further significant changes during 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 training intensity should 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.
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. (1995) found a highly significant correlation between the initial level of performance and the improvement in performance during the season (Figure 3A).
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 records (fast) than for the others (slow, Figure 3B).
11
N
0\
«}
9
(.) a}!: bJ)ro
~:;S aog
7
5
A
• r=0.90 p <0.001
N= 18
86 90 94
Initial performance 92
(% ofbest91)
98
0\ 105
*** «}
() a
100
.2
~
0..
-
95
<.;.... c
90
85
~
...
::::::.~--~
B
•• • fast o slow
Best 91 Initia192 Best 92
Figure 3. Relationship between the improvement in performance throughout a follow-up training season, the initial performance (A) and the best of the previous season (B) .
.
~o significant differences existed in training volume, intensity, frequency or dry land trammg between groups. From these results, it could be suggested that in spite of a good adaptation to training, the best performance achieved depended less on the effects of training
432

than on the effects of previous detraining. However, in the study the reason with some swimmers were more detrained than others was not explored.
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 a systems model.
By regression analysis, Mujika et al. (1996) indicated 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 sensitiveness to the training stimulus than the later. 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.
Systems model assume that performance can be estimated from the difference between a positive gain ascribed to the adaptation to exercise and a negative gain ascribed to the negative effects of the training load (Banister and Calvert 1980, Busso, et al. 1997, Mujika, et al. 1996,
Mujika, et al. 1996). Negative and positive influence may represent respectively fatigue and fitness accumulated in response to training. The main advantage of the mathematical model from a practical point of view is to evaluate the individual adaptation processes. For example, the time needed after an impulse training stimulus for the effect of fatigue to be dissipated may be calculated and the optimum duration of taper for each subject estimated. Ranged values between
12 and 32 days were reported (Mujika 1998).
An individual example of data analyzed by mean a systems model is given in Figure 4.
.....
Vl
15 105 A
'+-<
0
~
~
(.)
.: o:l
95 a
....
....
~
0..
85
0 15 30
Weeks of Training
45 0 15 30
Weeks of Training
45
Figure 4. Comparison between the actual and modelled performances (A). Positive and negative influence calculated by the systems model from the training load and the performance variations
(B) (Mujika, et al. 1996).
CONCLUSION
In swimming, scientific data indicated that in highly trained swimmers training intensity becomes the key parameter when compared to the 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 a systems model, useful tools to establish individualized training programs.
REFERENCES
1. Acevedo, E. 0. Goldfarb, A. H., (1989) Increased training intensity effects on plasma lactate, ventilatory threshold, and endurance. Medicine and Science in Sports and Exercise 21: 563-
568.
2. Banister, E. W. Calvert, T. W., (1980) Planning for future performance: implications for long term training. Canadian Journal of Applied Sport Sciences 5: 170-6.
433

3. Busso, T., Denis, C., Bonnefoy, R., Geyssant, A. Lacour, J. R., (1997) Modelling of adaptations to physical training by using recursive least squares algorithm. Journal of Applied Physiology
82: 1685-1693.
4. Cavanaugh, D. J. Musch, K. I., (1989) Arm and leg power of elite swimmers increase after taper as measured by biokinetic variable resistance machines. Journal of Swimming Research 5: 7-
10.
5. Chatard, J. C., Lavoie, J. M. Lacour, J. R., (1990) Analysis of determinants of swimming economy in front crawl. European Journal of Applied Physiology 61: 88-92.
6. Costill, D. L., (1985) Practical problems in exercise physiology research. Research Quarterly for
Exercise and Sport 56: 378-384.
7. Costill, D. L., Fink, W. J., Hargreaves, M., King, D. S., Thomas, R. Fielding, R., (1985)
Metabolic characteristics of skeletal muscle during detraining from competitive swimming.
Medicine and Science in Sports and Exercise 17: 339-343.
8. Costill, D. L., Flynn, M. G., Kirwan, J. P., Houmard, J. A., Mitchell, J. B., Thomas, R. Park, S.
H., (1988) Effects of repeated days of intensified training on muscle glycogen and swimming performance. Medicine and Science in Sports and Exercise 20: 249-54.
9. Costill, D. L., Thomas, R., Robergs, R. A., Pascoe, D., Lambert, C., Barr, S. Fink, W. J., (1991)
Adaptations to swimming training: influence of training volume. Medicine and Science in
Sports and Exercise 23: 371-7.
10. Houmard, J. A. Johns, R. A., (1994) Effects of taper on swim performance. Practical implications. Sports Medicine 17: 224-32.
11. Kirwan, J. P., Costill, D. L., Flynn, M. G., Mitchell, J. B., Fink, W. J., Neufer, P. D. Houmard, J.
A., (1988) Physiological responses to successive days of intense training in competitive swimmers. Medicine and Science in Sports and Exercise 20: 255-9.
12. Maglischo, E. (1982) Swimming faster. Mayfield Publishing Company, Palo Alto, California, 1-
472
13. Medb\1\, J. I. Tabata, I., (1989) Relative importance of aerobic and anaerobic energy release during short-lasting exhausting bicycle exercise. Journal of Applied Physiology 67: 1881-1886.
14. Mikesell, K. A. Dudley, G. A., (1984) Influence of intense endurance training on aerobic power of competitive distance runners. Medicine and Science in Sports and Exercise 16: 371-375.
15. Mujika, I., (1998) The influence of training characteristics and tapering on the adaptation in highly trained individuals: a review. International Journal of Sports Medicine 19: 1-8.
16. Mujika, I., Busso, T., Lacoste, L., Barale, F., Geyssant, A. Chatard, J. C., (1996) Modelled responses to training and taper in competitive swimmers. Medicine and Science in Sports and
Exercise 28: 251-8.
17. Mujika, I., Chatard, J. C., Busso, T., Geyssant, A., Barale, F. Lacoste, L., (1995) Effects of training on performance in competitive swimming. Canadian Journal of Applied Sport
Sciences 20: 395-406.
18. Mujika, I., Chatard, J. C., Busso, T., Geyssant, A., Lacoste, L. Barale, F., (1996) Use of swimtraining profiles and performance data to enhance training effectiveness. Journal of Swimming
Research ll: 23-29.
19. Neary, J. P., Martin, T. P., Reid, D. C., Burnham, R. Quinney, H. A., (1992) The effects of a reduced exercise duration taper programme on performance and muscle enzymes of endurance cyclists. European Journal of Applied Physiology 65: 30-36.
20. Platonov, V. N. (1988) L'entrainement sportif: theorie et methodologie. Revue EPS, Paris, 1-
289
21. Rusko, H., (1987) The effect of training on aerobic power characteristics of young cross-country skiers. Journal of Sports Sciences 5: 273-286.
22. Sharp, R. L., (1993) Prescribing and evaluating interval training sets in swimming: a proposed model. Journal of Swimming Research 9: 36-40.
23. Van Handel, P. J., Katz, A., Troup, J. P., Daniels, J. T. Bradley, P. W. (1988) Oxygen consumption and blood lactic acid response to training and taper. Human Kinetics Books,
Champaign, IL, 269-275
ACKNO~LEDGEMENTS
Authors wish to thank the swimming coaches Lucien Lacoste, Frederic Baral, Jacqueline
Legrand and Michel Paulin for their co-operation and for making valuable suggestions.
434