CURRENT OPINION

Sports Med 2002; 32 (9): 539-554 0112-1642/02/0009-0539/$25.00/0 © Adis International Limited. All rights reserved.

Performance Evaluation of Swimmers Scientific Tools David J. Smith,1 Stephen R. Norris1 and John M. Hogg2 1 Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada 2 Faculty of Physical Education and Recreation, University of Alberta, Edmonton, Alberta, Canada

Abstract

The purpose of this article is to provide a critical commentary of the physiological and psychological tools used in the evaluation of swimmers. The firstlevel evaluation should be the competitive performance itself, since it is at this juncture that all elements interplay and provide the ‘highest form’ of assessment. Competition video analysis of major swimming events has progressed to the point where it has become an indispensable tool for coaches, athletes, sport scientists, equipment manufacturers, and even the media. The breakdown of each swimming performance at the individual level to its constituent parts allows for comparison with the predicted or sought after execution, as well as allowing for comparison with identified world competition levels. The use of other ‘on-going’ monitoring protocols to evaluate training efficacy typically involves criterion ‘effort’ swims and specific training sets where certain aspects are scrutinised in depth. Physiological parameters that are often examined alongside swimming speed and technical aspects include oxygen uptake, heart rate, blood lactate concentration, blood lactate accumulation and clearance rates. Simple and more complex procedures are available for in-training examination of technical issues. Strength and power may be quantified via several modalities although, typically, tethered swimming and dry-land isokinetic devices are used. The availability of a ‘swimming flume’ does afford coaches and sport scientists a higher degree of flexibility in the type of monitoring and evaluation that can be undertaken. There is convincing evidence that athletes can be distinguished on the basis of their psychological skills and emotional competencies and that these differences become further accentuated as the athlete improves. No matter what test format is used (physiological, biomechanical or psychological), similar criteria of validity must be ensured so that the test provides useful and associative information concerning current or future performance. The practical worth of any proposed testing or monitoring protocol should be carefully evaluated. In addition, the developmental stage of the athlete(s) in question should be reflected in the testing/monitoring programme. Finally, increasing technological innovations will bring to the pool deck or dry-land training area simple, fast and advanced diagnostic tools, particularly in the areas of blood-borne markers of training response and neuromuscular excitability.

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Successful competitive swimming performance requires that a talented swimmer has developed his/her technique and physical conditioning to a high level and that the competition performance is reliable (consistent high-quality swimming) through the heats, semi-finals (when necessary) and finals. Technique and conditioning are supported by a strong psychological platform, appropriate tactical awareness and a healthy body. The road to success at Olympic and World level competitions may take between 6 to 16 years of structured training, training developed by a coach who utilises intuition, experience and scientific knowledge. The key to success does not lie in training hard, but in training purposely and carefully.[1] This requires that a swimmer’s training is planned and monitored and that competition performance is evaluated with respect not only to final time but also to technical components and strategy. Components affecting swimming performance include basic speed, stroke mechanics, starts and turning ability; the physiological factors of basic and specific endurance, anaerobic power and capacity, muscle power and flexibility; and finally the psychological factors of motivation and stress management. Evaluation of these components together with analysed training and competition data should subsequently be used for improving the training prescription, the aim being enhanced competitive performance. The purpose of this article is to provide a critical commentary of scientific tools used in physiological and psychological disciplines as they are utilised in the evaluation of swimmers. 1. Competition Performance Analysis Competitive swimming performances have been divided into three main elements: starting, turning and clean swimming,[2] and finishing speed in the last 5 to 20m of a race is considered as a fourth element. In 1988, partitioning of these technical elements was used to analyse the Japanese Olympic Trials,[3] and stroke rate, stroke length and mid-pool swimming speed was analysed at the Seoul Olympic Games.[4-6] The idea of competition analysis started before 1980, but it was not until the  Adis International Limited. All rights reserved.

Smith et al.

European Championship in Bonn, 1989, that performance analysis in its current form became international. Research in the USSR and East Germany, identified through film and video analysis that presented specific objective data of the technical components of a race was critical to coaches and swimmers for enhancing training and competition performance.[7] 1.1 Methodology of Competition Analysis

In order to perform a race analysis, video footage is recorded from several video cameras operating from a central control panel or as separate video recordings. The videotape includes encoded time displayed on the video picture and the video system is linked to the electronic timing system of the pool, which is activated by the starter’s signal. The first analysis, performed at the European Championships in Bonn, 1989,[7] used cameras placed high up in the stands, located at measured distances of 10m (start distance), 25m, 42.5m (turn distance 7.5m in 7.5m out), 90m (finishing distance) and 92.5m (turn distance for an event longer than 100m). On playback, when a swimmer’s head touches a digital line superimposed on a video monitor at the above distances, the encoded time or frame number is recorded in a computer. Split and final times from the electronic timing system are also captured and incorporated into an individual swimmer’s competition analysis report. The start distance of 10m and turn distance of 7.5m in and out was initially used based on measurements of over 400 Soviet swimmers. The majority ended gliding at 10m after the start and engaged in swimming motion and similarly after a turn, had finished gliding by 7.5m. However, in January 1991 La Federation Internationale de Natation (FINA: the international governing body for competitive swimming) adapted new rules for the backstroke events allowing a swimmer to be completely submerged during a turn and for a distance of not more than 15m after the start and each turn. Thus, for the backstroke events the start distance for video recording increased from 10 to 15m and the turn to 10m since most swimmers emerged by that distance. The current format Sports Med 2002; 32 (9)

Performance Evaluation of Swimmers

used by Ligue Europeenne de Natation (LEN: European Swimming Federation) is a 15m start and a turn distance of 5m in and 10m out and a final finish distance of 5m from the wall for all events.[8] The calculation of the finish speed uses the time difference from when the swimmers head touches the 5m superimposed line to touching the wall with a hand but is divided by 4.5m rather than 5m, because the arm reach to the wall is estimated to be 0.5m. 1.2 Stroke Rate, Stroke Length and Efficiency Index

A swimmer’s average speed during clean swimming (the portion of a race that excludes the start, turns and 5m finish) is equal to the product of stroke rate and length. Early investigations on the relationships of these two variables in competitive swimming[9-11] overestimated stroke length because it was calculated from the assumption that stroke length equalled swimming speed divided by stroke rate, where the calculation of swimming speed was based on event distance divided by finishing time. This meant that the calculation did not account for the dive start, or any variation in midpool swimming speed and turning times.[12] However, with video and computer analysis techniques, stroke rate and length are currently calculated for every 25m section of a race up to a race distance of 200m and every 50m for 400m upwards. The clean swimming speed and subsequent stroke rate and length are determined between distances after a 15m start, mid-pool, and pre- and post-turn (either 5 or 10m) and a finish distance from the wall of 5m. Stroke rate is measured as the number of seconds or frames required to complete 1 or 2 stroke cycles and stroke length is calculated using the formula: stroke length (m) = swimming speed (m/sec) divided by stroke rate (cycles/sec). Swimmers normally increase their swimming speed by a combination of increasing stroke length and/or stroke rate. Of these two speed components, it has been concluded that stroke length is the most critical factor in achieving success in competition.[5,10,13] A stroke efficiency index can be calcu Adis International Limited. All rights reserved.

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lated by multiplying swimming speed by stroke length. This index assumes that at a given speed, the swimmer who moves the greatest distance per stroke has the most effective swimming technique.[14] Generally, fast swimmers have a longer stroke length and higher efficiency index, but at the elite level there are some variations based on individual technique and feel for the water. As a race progresses, there is a progressive reduction in a swimmer’s efficiency index and comparison between race efforts for an individual swimmer could be a useful marker of training effectiveness. To increase speed in the short-term (within a race) a swimmer should strive to increase stroke rate while maintaining stroke length and in the longterm (over the course of a season), the swimmer should increase stroke length while maintaining any decrease in stroke rate.[15] 1.3 Practical Use of Competition Analysis

The information obtained in competition analysis is collected in a scientific manner to reduce error of measurement so that accurate data can be used by a coach within a swimming meet or between numerous international events. During a meet, sport scientists endeavour to provide the coach with both individual results and summary results from all swimmers participating in an event before the next session begins (i.e. heat results before semi-finals/finals). An example of an individual swimmer report is presented in table I. The analysis allows a coach to find weak and strong points in the temporal aspects of a race and check that race strategy and target stroke rates were executed according to a race plan. It also permits comparison with performance variables of opponents so that the information can be applied to developing technical improvements in training. A history of the best technical components (start, turn, clean swimming speeds and finishing time) achieved in recent international competitions can be found at www.swim.ee, the website of Dr R. Haljand,[16] and an example of a comparison between swimmers is given in table II. The winner of any swimming race is not necessarily the swimmer Sports Med 2002; 32 (9)

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Table I. An example of a swimmer summary compiled after competition video analysis in the 100m freestyle final (John Doe: World Team, lane 4, 1st finisher)a Distance (m)

Time (sec)

25

10.83

50

23.86

75

35.93

100

49.19

Lap time (sec) 23.86 25.33

Clean speed Stroke (m/sec) rate (cycle/min) length (m)

Turn time index (m • m/s) (15 m) [sec]

2.06

49.3

2.45

5.06

1.98

48.0

2.48

4.91

1.93

46.2

2.51

4.84

1.89

49.3

2.30

4.34

7.20

Turn speed (m/sec) 2.08

Mean 24.59 1.97 48.2 2.43 4.79 a The time and speed for result, first half, second half and 15m start were 49.19 sec, 2.03 m/sec; 23.86 sec, 2.10 m/sec; 25.33 sec, 1.97 m/sec; 5.87 sec, 1.74 m/sec, respectively.

with the fastest clean swimming speed, but the one who executes all technical components well and swims fast enough. 2. Monitoring of Training and Performance Potential Via Specific Protocols The accurate analysis and assessment of various components of performance within the training context is an important process for coaches and sport scientists to include as an integral aspect of the training and competition programme of a swimmer.[17-21] Training and performance diagnostic protocols should provide the basis for an ability to: (i) analyse the effects and trends brought about through training; (ii) assess the quality, structure and preparedness for competition; (iii) predict future competitive performance; and (iv) provide recommendations for continued directional training.[17,22,23] In addition, the primary areas of interest are likely to be: (i) highest short-duration speed attainable (i.e. 25m); (ii) the speed at maximal aerobic power; (iii) the speed at ‘physiological steady state’; (iv) swimming economy; and (v) anaerobic capacity. Aspects of physiology and biomechanics are bound together in close concert when dealing with sport performance and, therefore, these two elements should be combined when examining the information gained from particular sport-specific monitoring protocols. Furthermore, swim coaches, in keeping with other coaches, often have a battery or repertoire of sport-specific ‘sets’ that they employ at particular times during the training format to gauge  Adis International Limited. All rights reserved.

the progress and capability of their athletes.[24,25] However, this ‘enthusiasm’ for data collection should be tempered by the realisation that ‘testing’ in and of itself is no guarantee of future improved performance and that it is critical that the practical worth (i.e. the association with performance and the relationship with other relevant factors) of any proposed testing or monitoring protocol is carefully evaluated to avoid the potential situation of gathering data that has little ‘real world’ use. In addition, it should also be understood that the testing/monitoring programme may well need to reflect the differences in requirements between fledgling, accomplished and elite performers and their respective future performance goals. Aside from the use of actual race performance data (arguably the ‘highest forms’ of training and monitoring), maximal effort swims (‘in training’ time trials) may be used to establish benchmark comparison points. In addition to direct cross-reference to competition speed, it is also possible to derive an individualised swimming speed versus time performance ‘curve’ based upon a series of criterion efforts as shown in figure 1.[3,26,27] A few prominent research groups have built upon the ‘critical power’ concept described by Monod and Scherrer[28] to establish protocols to examine current training status and potential performance capability, as well as recommendations for training design, via various linear and non-linear methodologies.[3,26,27,29-31] The review by Hill[32] provides a complete synopsis of the mathematical models applicable to this concept. In general, alSports Med 2002; 32 (9)

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543

though few world class swimmers actually ‘swim the curve’ in terms of events, a basic goal for a swimmer is to move his/her global swimming speed versus time performance curve upwards and to the right as shown in figure 2. An interpretation of this shift is unlikely to be definitive without other information to include or exclude possible contributors (biomechanical, physiological and psychological). However, the overall result is an improved ability to sustain a particular (attainable) swimming speed. Several other non-invasive swimming tests have been discussed in the literature such as the 30- and 60-minute swim tests (T30 and T60)[33,34] and the 2000[35] and 3000m swim tests,[36] all of which supposedly give some representation of aerobic endurance capacity. The T30 and T60 tests require the swimmer to cover the greatest distance that they can in the set time allowed, whereas the

2000 and 3000m swims require the stated distance to be completed in the shortest possible time. Despite the view that such tests give an indication of an extended performance capability/endurance capacity (at least beyond competitive pool swimming events, i.e. 1500m), typical average speeds (m/sec) resulting from these tests are unlikely to be uniform, thereby reflecting different levels of physiological intensity. That is, world class swimmers would cover the 2000m with the fastest average speed, the 3000m and the T30 with a somewhat similar speed and the T60 with the slowest average speed when comparing these tasks with each other. Such tests are based upon the interrelation. ship between oxygen consumption (VO2), blood lactate concentration (B[La–]), and swimming speed (see figure 3) and, in particular, the extensive body of work commenting upon the use of B[La–] as an indicator of the degree of effort by, or

Table II. An example of a comparison of swimmers: European Championships 2000, women’s 100m breaststroke (reproduced from Haljand,[16] with permission) Parameter

World best

Kovacs

Gerasch

Bondarenko

Result (min:sec)

1:06.99

1:08.38

1:09.28

1:09.81

Start time 15m (sec)

7.69

8.28

8.48

8.50

Start speed 15m (m/sec)

1.95

1.81

1.77

1.76

25m

14.48

15.12

15.64

15.84

75m

48.92

50.02

51.10

51.82

1st 25m

1.58

1.46

1.40

1.36

2nd 25m

1.46

1.46

1.40

1.36

3rd 25m

1.39

1.39

1.39

1.36

last 25m

1.36

1.34

1.35

1.35

1st 50m

49

47

52

37

2nd 50m

47

46

53

50

1st 50m

1.78

1.87

1.62

2.20

2nd 50m

1.75

1.74

1.54

1.62

Turn time 5m in + 10m out (sec)

9.86

10.36

10.36

10.28

Turn speed 5m in + 10m out (m/sec)

1.52

1.45

1.45

1.46

Finishing time last 5m (sec)

3.34

3.42

3.40

3.21

Finishing speed last 5m (m/sec)

1.35

1.32

1.32

1.40

Average swimming speed (m/sec)

1.45

1.41

1.38

1.36

Average frequency (cycles/min)

48

46

52

43

Average stroke length (m)

1.77

1.80

1.58

1.91

Lap time (sec)

Swim speed (m/sec)

Frequency (cycles/min)

Stroke length (m)

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Sports Med 2002; 32 (9)

Smith et al.

Swimming speed (m/sec)

544

25m 50m 100m 200m 400m 800m

1500m

3000m

Time (sec)

Fig. 1. Generic swimming speed versus time relationship.

impact upon, a swimmer during training and competition.[17,21,33,34,37] Various methodologies have evolved to examine B[La–] each with their own strengths, weaknesses and requirement for some degree of ‘expert’ interpretation that goes beyond purely the obvious rightward shift of the B[La–]/speed relationship. Usually some rationale is cited that suggests the ability to provide information on preferred training intensity(ies), endurance performance prediction and adaptation to training.[38-41] Although B[La–] testing protocols have been used in athletic settings for several decades, it is important for all those contemplating incorporating such methods and/or evaluating the results from such tests to understand that this is a highly controversial area, both at the basic and applied levels. Although there is a large body of peer-reviewed literature available concerning blood lactate and related topics, even a cursory examination of some of this material will reveal not only a significant number of cited testing methodologies, but also an over-abundance of terminology and jargon that may or may not be used interchangeably, and/or refer even to similar physiological occurrences. It should be apparent that the use of a single bloodborne parameter (in this case B[La–]) as a ‘stable’ indicator of events taking place at the muscle level under all conditions and possible methodologies should be viewed with a critical appreciation of the  Adis International Limited. All rights reserved.

myriad of underlying limitations. Aspects such as the temporal component, site of collection, and type of blood sample taken may all influence the resulting numeral representation, even before the ‘blood’ is presented for analysis by a particular instrument, which itself may also introduce another level of variability.[38,42-46] Further complications arise when one considers that factors such as an athlete’s nutritional status (i.e. degree of glycogen availability or dehydration) and the prevailing environmental conditions (i.e. hypoxia/altitude or high temperature/high humidity) may also have profound effects on the B[La–] results.[38,45,47] Despite the extensive list of potentially confounding factors, the use of blood lactate measures in training and competition situations continues to be undertaken and promoted as a ‘routine’ procedure. The basic premise is that, as intensity of effort increases (i.e. power output or swimming speed), the B[La–] rises as a reflection of the systems involved in the production of energy required to perform the task and is further modulated by the underlying mechanisms involved in dealing with lactate turnover. Therefore, the rate of accumulation of B[La–] depends upon the intensity level of the swim, while the magnitude of the B[La–] is determined by the duration of the event. A clear example of a swimming-specific methodology using B[La –]/speed is illustrated in the 2 × 400m ‘2-speed test’[48] and subsequent crossreference to longer duration swimming (e.g. the T30 and T60 protocols) and race performance.[34] It is important to realise that a mosaic of information may be gleaned from such a format of monitoring. In the case of the B[La–], particularly using methodologies such as Mader et al.,[48] Olbrecht et al.[34] and Pansold and Zinner,[17] information may be gathered concerning abilities to perform at particular swimming speeds (or variable B[La–] levels), fixed B[La–] (or variable swimming speeds), maximum swimming speed and peak B[La–]. This information may then be used to more accurately evaluate current performance capacities and design and control training programmes, as well as to predict future competitive performance outcome. Sports Med 2002; 32 (9)

Performance Evaluation of Swimmers

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this relationship may be used indirectly to quantify this economy and may further serve to indicate states of transient or longer lasting fatigue, as well as optimal states of preparedness (figure 5). In addition, even without attaining maximum heart rate, a prediction of the speed that a swimmer first attains maximum heart rate may be identified which may itself be used to approximate the swimming . . speed at maximal VO2 (VO2max). Such tests may also be combined with other simultaneous measures such as B[La–] evaluation.[1] 3. Oxygen Update and Swimming Economy Some investigators have examined swimming . economy based on the relationship between VO2 . and swimming speed.[53,54] VO2 measures during swimming date back to 1920,[55,56] and as research progressed, significant differences in the energy cost of swimming at various speeds between untrained, competitive and elite swimmers was reported by Holmer[57] and the regression slopes be. tween VO2 and swimming speed were also shown to be different for untrained, recreational and competitive swimmers.[53] A flatter economy slope could mean that swimmers have better physiolog-

Swimmer A Swimmer B Pre-training

Swimming speed (m/sec)

Overall, figure 4 illustrates the normal ‘desired’ training response of this measure, that is, a shift down and to the right of the B[La–]/speed relationship.[1,17,21] The kinetics of B[La–] may also be warranted for examination under conditions where a previously established high B[La–] is then assessed during either static or low-intensity dynamic recovery. This form of examination may provide specific information concerning the ability of a swimmer to ‘clear’ or remove lactate, something that has obvious benefits for endurance performance.[1,49,50] As with any measurement tool, the process of undertaking the protocol and the conditions surrounding it must be carefully controlled, together with a thorough understanding of potentially confounding issues. As Goldsmith[51] remarked: “Physiological variables, biomechanical variables, state of relative rest/fatigue, nutrition status, state of dehydration/rehydration will all need to be determined and accurately measured to ensure a reliable test is carried out”. Recently, Olbrecht[1] has produced a comprehensive review of the training and performance literature to illustrate the potential use of examining B[La–] and heart responses in swimmers in relation to swimming speed. The technical limitations of the routine meas. urement of VO2 in the majority of swimming training situations has led to the development and evolution of a number of ‘field’ tests where heart rate is determined at particular swimming speeds thereby providing coaches with a more easily obtained physiological/performance relationship (figure 5). This use of simple heart rate versus swimming speedbased protocols has widespread use in swimming programmes based on Treffene[52] with the Canadian 5 × 200m ‘descending’ set (Johnson D, personal communication) and the Australian 7 × 200m test[21] being prime examples. These tests are basically identical and allow the coach and sport scientist to examine a number of variables and constructs. The overall relationship may be used as an indirect marker of the economy of the swimmer’s ability to effectively use his/her usable heart rate range as swimming speed increases. The ‘slope’ of

545

Time (sec)

Fig. 2. Fundamental desire involves shifting the ‘curve’ up and

to the right. The figure illustrates the potential for the relationship between swimming speed and time to be improved over a time period and reflect the possible bias of training and the plasticity of a given swimmer’s adaptability.

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B[La−] peak*

B[La−]

• VO2 at MSS**

• VO2 (L/min)

B[La−] at MSS**

• VO2max

Swimming speed (m/sec)

Fig. 3. Swimming versus blood lactate concentration (B[La–] . . mmol/L) and oxygen consumption (V O2). VO2max = maximal oxygen uptake; * peak typically seen post-200m race performance; ** some arbitrarily defined maximal steady state (MSS).

ical adaptation, or that they have lower active . drag.[58] However, since VO2 is linearly related to . the intensity of effort at less than 100% VO2max,[59] estimates of energy expenditure apply only to slower swimming than competition speeds. Thus, . there is doubt that measurements of VO2 have any relevance to economy during competition.[14] Nevertheless, these estimates may provide an evaluation of improvements in swimming technique and assessment of aerobic power. Propelling efficiency in front crawl swimming is related to the amount of mechanical power partitioned into overcoming drag forces.[54] Furthermore, metabolic power output in front crawl swimming is related to speed cubed.[54] Significant positive . correlations have been reported between VO2 and . swimming speed cubed (r = 0.96 to 0.99) and VO2 and stroke rate (r = 0.92 to 0.99).[59] Furthermore, it was found that the slopes of the regression lines . between VO2 and swimming speed cubed and between oxygen demand and stroke rate were significantly negatively related to swimming perfor. mance (speed at 100% peak VO2). Better performers . were highlighted with lower VO2–stroke-rate slope values and attained a significantly lower stroke rate and longer stroke length at specified speeds.[59] The finding supported previous results by Costill et al.,[60] and Craig and Pendergast[10] who demonstrated that advanced swimmers were able to swim  Adis International Limited. All rights reserved.

a greater distance per stroke at a given speed than poorer swimmers. Thus, it is suggested that the swimmer who covers a greater distance per stroke at a given speed, spends less metabolic power in giving masses of water kinetic energy change (wasted power) and more into overcoming drag (useful power).[61] To increase maximal swimming speed and stroke length, swimmers must: (i) maximise propulsion and propelling efficiency; and (ii) reduce active drag from the water.[62] With this in mind, training studies have demonstrated improvement in technical proficiency and a consequent reduction in metabolic cost of swimming at a given speed after training.[63] Furthermore, the slope of the swimming economy regression equation has been shown to decrease significantly following training.[64] 4. Anaerobic Power and Strength Evaluation The effective assessment of anaerobic performance from both a power and capacity point of view is another important aspect of a swimmer’s evaluation. However, tests examining anaerobic capabilities are not as well developed as those for supposed aerobic qualities and may require specialist equipment (i.e. metabolic measurement apparatus) and involved protocols. An example of which is the anaerobic capacity method of Medbø et al.,[65] based on the theory behind an accumulated oxygen deficit. Currently, the use of explosive tests or short-duration sprints serve to provide some information regarding anaerobic power and peak B[La–] levels post-race may also aid the coach with regard to anaerobic capacity assessment dependent upon interpretation. These tests need relatively little equipment other than a swimming pool, stopwatch, and relatively inexpensive micro-sample blood lactate analysers. In fact, the knowledgeable design of specific swimming sets and subsequent execution can provide a great deal of appropriate information regarding anaerobic performance concerning power, capacity, and the physiological/psychological mix of dealing with an encroaching transient metabolic acidosis (lacSports Med 2002; 32 (9)

Performance Evaluation of Swimmers

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a Cybex ergometer. A recent study examined the relationship between swimming power, intra-cyclic linear body speed fluctuations and sprint breaststroke performance using an adapted Cybex dynamometer to measure swimming power.[71] The correlation between swim power and breaststroke sprinting speed was r = 0.64 (p = 0.11) and 0.87 (p < 0.05) for males and females, respectively. However, the correlation between swimming power and breaststroke performance for 91.4 and 365.8m was r = 0.91 and r = 0.86, respectively (p < 0.05). The study illustrated that the ability to effectively generate power during a partially tethered sprint was a predictor of both sprint and endurance breaststroke performance. 5. Psychological Tests in Competitive Swimming There is convincing evidence that athletes can be distinguished on the basis of psychological skills and emotional competencies. These differences become obvious as the athlete improves. Successful performance is governed by core psychological factors that can positively or negatively affect outcomes, notably, anxiety, confidence, conPre-training Post-training Progression in swimming speed at two example B[La−]s B[La−] peak*

B[La−]

tate tolerance). A key aspect to bear in mind with such tests (indeed with any test) is the extent to which it is actually correlated with performance. Although muscular performance is determined principally by the amount of energy made available for muscular activity, and the rate with which energy can be used, sprinting speed cannot be traced back to a shortage of energy. In most cases it is attributed to strength, coordination and technique.[1] Various scientific methods have been developed to assess muscular power for starting and turning, and predict sprinting performance based on either strength in dry-land conditions or swimming speed under tethered conditions. A close association has been typically accepted between sprint swimming performance and vertical jumping height, and leg extension power measured under isokinetic conditions has been correlated with diving distance (r = 0.76).[66] Force and power production that simulate actions used in butterfly and freestyle swimming may be measured by the Biokinetic1 swim bench (Isokinetics, Richmond, California, USA). Although it cannot duplicate the arm and hand action used in the water, it does allow the swimmer to incorporate in one motion most of the muscle groups and mechanics required during sprint swimming.[14] Early studies demonstrated a strong relationship between upper body strength and sprint swimming (r = 0.93)[67] and sprint time for 25 yards in swimmers less than 16 years old.[68] However, since the best swimmers do not necessarily produce the highest swim bench scores, it has been suggested that maximal swimming speed and tethered swimming force could be used to evaluate the balance between the technical performance and the swimmer’s capacity for muscular production in the water.[69] Adaptation of a Biokinetic system for tethered swimming at cable velocities of 0.8 m/sec for female and 1.0 m/sec for males up to a maximum distance of 12 to 15m away from the apparatus have been developed.[70] Further modifications have been made to use the control mechanism from

547

B[La−] at MSS**

Pre-MSS Post-MSS Pre-peak

Post-peak

Swimming speed (m/sec)

Fig. 4. Swimming speed versus blood lactate concentration

(B[La–] mmol/L) before and after a specific training phase. * Peak typically seen post-200m race performance; ** some arbitrarily defined maximal steady state (MSS).

Sports Med 2002; 32 (9)

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* Denotes example 'slope' parameter range under various conditions Test 1 Test 2

Heart rate (beats/min)

HRmax

*

Test 1

Test 2

HRsubmax

*

Ssubmax 1

Ssubmax 2 Smax 1

Smax 2

Swimming speed (m/sec)

Fig. 5. Swimming speed versus heart rate. HRmax = maximal heart rate; HRsubmax = submaximal heart rate; Smax = speed at maximal heart rate ; Ssubmax = speed at a given submaximal

heart rate.

centration and motivation.[72] The use of valid and reliable psychometric tests is one way to identify a swimmer’s mental strengths and weaknesses and the information can be used to better understand, monitor, and develop efficient training and competitive protocols to ensure successful performance. Collecting psychometric data is not without controversy and applied sport psychologists have generally found that athletes dislike taking trait and state tests primarily because they are viewed with mistrust and test results alone have never proved to be accurate predictors of success. However, it is important to recognise that scientific knowledge can be based on valid and reliable tests as well as on observational approaches provided certain precautions are in place. Psychometric tests are derived in the first instance from the general field of psychology, and should be systematically developed for validity and reliability, before being adapted to suit specific sport environments, levels of ability and age groups. The selected constructs should bear direct relevance to the sport, for example, anxiety and competitive swimming.[73] It is likely best to collect trait measures reflecting personality tendencies  Adis International Limited. All rights reserved.

first, for example, competitive trait anxiety,[74] before intruding with state measures reflecting conditions immediately before competition, for example, competitive state anxiety.[75] State measures can be taken once the practitioner is familiar with the swimmers and has been unreservedly accepted by them. Tests can be used to tease out personality characteristics and dispositions, to create personal profiles, to assess current psychological states and cognitive coping skills, to identify problems and appropriate interventions. Psychometric tests require a quantitative approach to analyse the data accurately and the resultant statistics require meaningful interpretation. Repeated measures should be taken over time with the swimmer. Hannin[76] suggested that scores be recorded in conjunction with performance results to identify an optimal zone of functioning (IZOF). With the careful collection of state scores patterns of behaviour may emerge that can be adjusted or changed to produce best performances. Popular tests have addressed personality factors, the measurement of select constructs, mood disturbances, sport orientations, team cohesion, and so on, and generally as a construct emerges from the psychology literature that has practical application in the sport-specific context it will be utilised. Personology tests that aim to establish a relationship between personality traits and performance outcome have enjoyed believers as well as sceptics.[77] However, only those versatile tests whose items are relevant to the sport will yield useful information. Table III provides a selection of inventories that have been used with competitive swimmers. A resource of tests/interventions has been compiled by Ostrow.[78] State measures can be difficult to obtain but where there are shortened versions of tests that require minimal time and intrusion, then these might be more apt, for example, the Mental Readiness Form (MRF) and Profile of Mood States (POMS). Optimal mood profiles need to be sport specific.[104] Multidimensional constructs of importance to a competitive swimmer’s performance have been addressed elsewhere,[88,105] and research has been conducted that supports the usefulness of specific Sports Med 2002; 32 (9)

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measures to create meaningful psychological profiles and helpful strategies.[106-109] There are new areas of research focus, such as body image, per-

fectionism, and learning styles; however, Jones and Swain,[110,111] in relation to anxiety, have pointed to the increasing need to examine the intensity and

Table III. Summary of select psychological inventories and tests used in competitive swimming Constructs to be measured

Test (acronym)

Reference

Anxiety Competitive trait anxiety

The Sport Competition Anxiety Test (SCAT)

74

Competitive state anxiety (cognitive anxiety; somatic anxiety; confidence)

The Competitive State Anxiety Inventory (CSAI2)

75

Competitive trait anxiety (cognitive anxiety; somatic anxiety and concentration)

The Sport Anxiety Scale (SAS)

79

Stress/recovery

Recovery-Stress Questionnaire for Athletes (REST-Q)

80

Attention

Test of Attentional and Interpersonal Style (TAIS)

81

mood states (tension; depression; anger; vigour; fatigue; confusion)

Profile of Mood States (POMS)

82

Mood states (tension; depression; anger; vigour; fatigue; confusion and confidence)

Modified POMS

83

Mood states

mental health (swimmers) [emotional stability; self-confidence; dominance; self-knowledge; affiliation] Sport confidence Sources of confidence

84 The Strait-State Confidence Inventory (TSCI)

85

Sources of Sport-confidence Questionnaire (SSCQ)

86

The Athletic Coping Skills Inventory-28 (ACSI)

79

The Psychological Skills Inventory for Sport (PSIS)

87

Mental coping skills Mental coping skills (concentration; anxiety; management; mental preparation; motivation; team emphasis) Mental skills Coping strategies

The Mental Skills for Swimmers Questionnaire

88

Controlling emotions; Organizing input; Planning the subsequent response; and Executing the appropriate actions (COPE)

89

Mental readiness

The Mental Readiness Form (MRF)

90

Performance evaluation

Mental States of Readiness and Satisfaction (MSRS)

91

Evaluation of strategies

The Self-regulation Questionnaire (SRQ)

92

Attribution

The Sport Attributional Style Scale (SASS)

93

approach-avoidance

Approach-avoidance Motivation Scale for Sports (AMSS)

94

task-ego orientation

Task and Ego Orientation in Sport Questionnaire (TEOSQ)

95

assessment

Motives for Competition Scale (MCS)

96

Specialisation

Sport Socialisation Questionnaire (SSQ)

97

Distractions/demands

Daily Analyses of Life Demands for Athletes (DALDA)

98

Team cohesion

The Group Environment Questionnaire (GEQ)

99

Sport orientation (competitiveness; desire to win; desire to fulfil personal goals)

The Sport Orientation Questionnaire (SOQ)

100

Personality (extraversion; agreeableness; neuroticism; conscientiousness; openness to experience)

The Neuroticism, Extraversion and Openness (NEO) Personality Inventory (NEO-PI)

101

Self-concept

The General Sports Orientation Questionnaire (CSOQ)

102

Perfectionism

The Multidimensional Perfectionism Scale (MPS)

103

Motivation

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direction of competitive state anxiety, while Vealey et al.[86] suggested that examining self-confidence in athletes should include a closer look at the specific causes and consequences. An alternative methodology to measurement in swimming is a qualitative approach that seeks to establish the experiences of the swimmer in determining his or her mental competencies, response patterns and immediate needs in order to cope with anxieties, losses of concentration, confidence and motivation. This information is more specific and encourages the swimmer to make intra-individual comparisons rather than against established norms, that is, how the swimmer is feeling relative to how he or she normally feels in this situation. Butler and Hardy[112] introduced performance profiling which has been used in many sports including swimming,[105] and other approaches include selfrecording, check listing,[108,113] assessing mental skill abilities,[88] self-reflective exercises that evaluate performance states of readiness and satisfaction,[91,114] monitoring tools for stress-recovery,[114] and the consistency of coping responses of young swimmers in competition and training.[115] Motivational interviewing can identify specific competitive preparations[116] as well as monitor and assess the effectiveness of cognitive techniques, for example, goal setting[117] or problem solving on issues that are dysfunctional to performance. The American Psychological Association,[118] as well as applied sport psychologists,[119,120] have pointed to the need to safeguard ethical principles (notably privacy and confidentiality) and to follow an established code of conduct when using inventories. Practitioners need to be aware of any methodological shortcomings of tests, to follow procedures accurately, to recognise any personal limitations in test administration or interpretation and to be conservative in their feedback with the athletes. The information gathered should not be used on its own – and certainly not for selection purposes – but rather in conjunction with keen observation, discussion, explanation and attentive listening. Few tests are entirely free from the contamination of measurement error and it may be better to be a healthy sceptic  Adis International Limited. All rights reserved.

Smith et al.

than to unreservedly embrace suspect results and make false promises. Finally, there is always the x-factor or compensatory competencies or alternative hypotheses in performance to consider. Tests are not a means to identifying elite performers, but can help provide additional knowledge to enhance swimming performance provided these insights are used in an ethical fashion. 6. Conclusion In summary, competition video analysis provides the most comprehensive evaluation of a swimmer’s true state of preparedness. The factors of technique, conditioning, motivation and stress management together with tactics and health are integrated into a single measurable performance. Teasing out of the factors by separate evaluation tools is necessary to analyse these underlying components to assess the strengths and weakness of the swimming performance and identify that the components are at a level that they are assumed to be. Since some evaluation protocols are more practical than others, the timing and selection of tests should always be considered. It should be clearly recognised by all concerned (coaches, swimmers and sport scientists) that for monitoring or evaluative protocols to be effective, they must be incorporated into the training and competition programme in an integrated and seamless manner. The future for on-going monitoring in swimming, indeed with all human performance endeavours, is an exciting one as increases in technology and the migration of equipment and techniques from research and the medical sciences bring to the pool deck or dry-land training area simple, fast and advanced diagnostic tools, particularly in the areas of blood-borne markers of training intensity and neuromuscular excitability. References 1. Olbrecht J. The science of winning: planing, periodization and optimizing swim training. Luton: Swimshop, 2000 2. Hay JG, Guimares ACS. A quantitative look at swimming biomechanics. Swimming Tech 1983; 20: 11-7 3. Wakayoshi K, Nomura T, Takahashi G, et al. Analysis of swimming races in 1989 Pan Pacific Swimming Championships and 1988 Japanese Olympic trials. In: MacLaren D, Reilly T,

Sports Med 2002; 32 (9)

Performance Evaluation of Swimmers

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14. 15.

16.

17.

18.

19.

20.

Lees A, editors. Biomechanics and medicine in swimming. Swimming science VI. London: E & FN Spon, 1992: 135-41 Nelson RC, Brown PL, Kennedy PW, et al. An analysis of Olympic swimmers in the 1988 Summer Games. State College (PA): Pennsylvania State University, 1990 Kennedy P, Brown P, Chengalur SN, et al. Analysis of male and female Olympic swimmers in the 100-meter events. Int J Sport Biomech 1990; 6: 187-97 Chengalur SN, Brown PL. An analysis of male and female Olympic swimmers in the 200-meter events. Can J Sport Sci 1992; 17: 104-9 Absalymov T, Shircovets E, Lipsky E. Analyses of competitive activities [handout]. LEN Swimming Committee, 19th European Swimming Championships; 1989 Aug 13-19; Bonn Haljand R. Technical and tactical parameters of competition performances. Rein Haljand [online]. Avaiable from URL: http://www.swim.ee [Accessed 2002 Jun 14] East DJ. Swimming: an analysis of stroke frequency, stroke length and performance. NZ J Health Phys Ed Recreation 1970; 3: 16-7 Craig AB, Pendergast DR. Relationships of stroke rate, distance per stroke, and velocity in competitive swimming. Med Sci Sports Exerc 1979; 11: 278-83 Craig AB, Skehan PL, Pawelczyk JA, et al. Velocity, stroke rate and distance per stroke during elite swimming competition. Med Sci Sports Exerc 1985; 17: 625-34 Thompson KG, Haljand R, MacLaren DP. An analysis of selected kinematic variables in national and elite and female 100 m and 200 m breaststroke swimmers. J Sports Sci 2000; 18: 421-31 Arellano R, Brown P, Cappaert J, et al. Analysis of 50-, 100-, and 200-m freestyle swimmers at the 1992 Olympic Games. J Appl Biomech 1994; 10: 189-99 Costill DL, Maglischo EW, Richardson AB. Swimming. London: Blackwell Scientific Publications. 1992 Ungerechts BE, Wilke K, Reischle K et al. The status of research on the biomechanics of swimming. In: Ungerechts BE, Wilke K, Reischle K, editors. Swimming science V: proceedings of the 5th international symposium of biomechanics and medicine in swimming; 1986 Jul 27-31; Bielefeld. Champaign (IL): Human Kinetics Books, 1988: 3-14 Haljand R. LEN swimming competition analysis. European Championships Helsinki 2000: Women’s 100m breaststroke. Rein Haljand [online]. Available from URL: www.swim.ee [Accessed 2002 May 8] Pansold B, Zinner J. Selection, analysis and validity of sportspecific and ergometric incremental test programmes. In: Bachl N, Graham TE, Löllgen H, editors. Advances in ergometry. Berlin: Springer-Verlag, 1991: 180-214 Neumann G. Comparison between ergometric methods of investigation and field tests. In: Bachl N, Graham TE, Löllgen H, editors. Advances in ergometry. Berlin: Springer-Verlag, 1991: 215-27 Treffene RJ, Alloway J, Jull J. Use of a heart rate meter in swimming and athletic performance measurement. In: Terauds J, Bedingfield W, editors. Swimming III. Baltimore (MD): University Park Press, 1979: 275-80 Troup JP. Setting up a season using scientific training. Swimming Tech 1986 May-Jul; 23 (1): 8-16

 Adis International Limited. All rights reserved.

551

21. Pyne D, Maw G, Goldsmith W. Protocols for the physiological assessment of swimmers. In: Gore C, editor. Physiological tests for elite athletes. Champaign (IL): Human Kinetics, 2000: 372-82 22. Smith DJ. Periodization for swimming. In: Proceedings of the Sport Science Seminar, Great Britain High Performance Swim Coaching Group, Amateur Swimming Association of Great Britain; 1998 Oct 1-4; Coventry 23. Norris SR, Smith DJ. Monitoring performance. In: Proceedings of Swim Alberta Coaches Conference, World Cup Edmonton; 2001 Nov 23; Edmonton 24. Atkinson JD, Sweetenham WF. Bill Sweetenham’s test sets for age and youth level swimmers. Albury (NSW): Australian Swimming Coaches and Teachers Association, 1999 25. Maglischo EW. Swimming even faster. Mountain View (CA): Mayfield Publishing Company, 1993 26. Wakayoshi K, Ikuta K, Yoshida T, et al. Determination and validity of critical velocity as an index of swimming performance in the competitive swimmer. Eur J Appl Physiol 1992; 64: 153-7 27. Wright B, Smith DJ. A protocol for the determination of critical speed as an index of swimming endurance performance. In: Miyashita M, Mutoh Y, Richardson A, editors. Medicine and science in aquatic sports. Basel: Karger, 1994: 55-9 28. Monod H, Scherrer J. The work capacity of a synergic muscular group. Ergonomics 1965; 8: 329-38 29. MacLaren DPM, Coulson M. Critical swim speed can be used to determine changes in training status. In: Keskinen KL, Komi PV, Hollander AP, editors. Biomechanics and medicine in swimming VIII: proceedings of the VIII International Symposium on Biomechanics and Medicine in Swimming; 1998 Jun 28-Jul 2; Jyväskylä. Jyväskylä: Gummerus Printing, 1999: 227-32 30. Fernandes R, Vilas-Boas JP. Critical velocity as a criterion for estimating aerobic training pace in juvenile swimmers. In: Keskinen KL, Komi PV, Hollander AP, editors. Biomechanics and medicine in swimming VIII: proceedings of the VIII International Symposium on Biomechanics and Medicine in Swimming; 1998 Jun 28-Jul 2; Jyväskylä. Jyväskylä: Gummerus Printing, 1999: 233-8 31. Matsunami M, Taguchi M, Taimura A, et al. Comparison of swimming speed and exercise intensity during non-invasive test and invasive test in competitive swimming. In: Keskinen KL, Komi PV, Hollander AP, editors. Biomechanics and medicine in swimming VIII: proceedings of the VIII International Symposium on Biomechanics and Medicine in Swimming; 1998 Jun 28-Jul 2; Jyväskylä. Jyväskylä: Gummerus Printing, 1999: 239-44 32. Hill DW. The critical power concept: a review. Sport Med 1993; 16: 237-54 33. Olbrecht J, Madsen Ø, Mader A, et al. Relationship between swimming velocity and lactic concentration during continuous and intermittent training exercises. Int J Sports Med 1985; 6: 74-7 34. Olbrecht J, Mader A, Madsen Ø, et al. The relationship of lactic acid to long-distance swimming and the 2 × 400m ‘twospeed-test’ and the implications for adjusting training intensities. In: Ungerechts BE, Wilke K, Reischle K, editors.

Sports Med 2002; 32 (9)

552

35. 36. 37.

38. 39.

40. 41.

42.

43.

44. 45. 46.

47.

48.

49.

50.

51. 52.

53.

Smith et al.

Swimming science V. Champaign (IL): Human Kinetics, 1988: 261-7 Touretski G. 1993 Japan official swimming coach clinic. Tokyo: Japan Amateur Swimming Federation, 1994 Madsen O. Aerobic training: not so fast, there. Swimming Tech 1982; 19 (3): 13-8 Kindermann WG, Simon G, Keul J. The significance of the aerobic-anaerobic transition for the determination of work load intensities during endurance training. Eur J Appl Physiol 1979; 42: 24-34 Jacobs I. Blood lactate: implications for training and sports performance. Sports Med 1986; 3: 10-25 MacRae HSH, Dennis SC, Bosch AN, et al. Effects of training on lactate production and removal during progressive exercise in humans. J Appl Physiol 1992; 72: 1649-56 Sjodin B, Svendenhag J. Applied physiology of swimming. Sports Med 1985; 2: 83-99 Yoshida T, Childa M, Ichioka M, et al. Blood lactate parameters related to aerobic capacity and endurance performance. Eur J Appl Physiol 1987; 56: 7-11 Foxdal P, Sjodin A, Ostman B, et al. The effect of different blood sampling sites and analyses on the relationship between exercise intensity and 4.0 mmol/L blood lactate concentration. Eur J Appl Physiol 1991; 63: 52-4 Foxdal P, Sjodin A, Sjodin B. Comparison of blood lactate concentrations obtained during incremental and constant intensity exercise. Int J Sports Med 1996; 17: 360-5 Telford R. Lactic acid measurements: are they useful? Sports Sci Med Q 1984; 1: 2-7 Weltman A. The blood lactate response to exercise. Champaign (IL): Human Kinetics, 1995 Yoshida T, Suda Y, Takeuchi N. Endurance training regimen based upon arterial blood lactate: effects on anaerobic threshold. J Appl Physiol 1982; 49: 223-30 Maassen N, Busse MW. The relationship between lactic acid and work load: a measure for endurance capacity or an indicator of carbohydrate deficiency? Eur J Appl Physiol 1989; 58: 728-37 Mader A, Madsen Ø, Hollmann W. The evaluation of the anaerobic energy supply with regard to the performances in training and competition in swimming [in German]. Leistungssport 1980; 10: 263-79 Mader J, Heck H, Hollmann W. Leistung und leistungsbegrenzung des menschlichen organismus interpretiert am modell thermodynamisch offener system. Ein Beitrag zur kiskussion biologischer leistungsgrenzen im hochleistungssport. In: Riecker H, editor. Sport an der grenze der menschlichen leistungsfähigkeit. Berlin: Springer, 1981: 69-93 Norris SR, Smith DJ. Swimming monitoring tools in ‘Future Splash ‘95’: Canadian Swim Coaches Association Conference; 1995 Oct 16-21; Toronto Goldsmith W. Measure what’s measurable. Swimming Tech 1998 Jul-Sep; 35 (2): 29-30 Treffene RJ. Swimming performance test: a method of training and performance time selection. Swimming Tech 1978; 15: 120-4 Costill DL, King DS, Thomas R, et al. Effects of reduced training on muscular power in swimmers. Physician Sportsmed 1985; 13: 94-101

 Adis International Limited. All rights reserved.

54. Toussaint HM, Beelen A, Rodenburg A, et al. Propelling efficiency of front-crawl swimming. J Appl Physiol 1988; 65: 2506-12 55. Liljestrand G, Lindhard J. Über das minutenvolumen des herzens beim schwimmen. Skand Arch Physiol 1920; 39: 63-77 56. Liljestrand G, Stenström N. Studien über die physiologie des schwimmens. Skand Arch Physiol 1920; 39: 1-63 57. Holmer I. Oxygen uptake during swimming in man. J Appl Physiol 1972; 33: 502-9 58. Di Pampero PE, Pendergast DR, Wilson DR, et al. Energetics of swimming man. J Appl Physiol 1974; 37: 1-5 59. Wakayoshi K, D’Acquisto LJ, Cappaert JM, et al. Relationship between oxygen uptake, stroke rate, and swimming velocity in competitive swimming. Int J Sports Med 1995; 16: 19-23 60. Costill D, Kovaleski J, Porter D, et al. Energy expenditure during front crawl swimming: predicting success in middledistance events. Int J Sports Med 1985; 6: 266-70 61. Toussaint HM. Differences in propelling efficiency between competitive and triathlon swimmers. Med Sci Sports Exerc 1990; 22: 409-15 62. Cappaert JM. Biomechanics of swimming analyzed by threedimensional techniques. In: Keskinen KL, Komi PV, Hollander AP, editors. Biomechanics and medicine in swimming VIII: proceedings of the VIII International Symposium on Biomechanics and Medicine in Swimming; 1998 Jun 28-Jul 2; Jyväskylä. Jyväskylä: Gummerus Printing, 1999: 141-5 63. Wakayoshi K, Yoshida T, Ikuta Y, et al. Adaptations to six months of aerobic swim training: changes in velocity, stroke rate, stroke length and blood lactate. Int J Sports Med 1993; 14: 368-72 64. D’Acquisto LJ, Barzdukas AP, Dursthoff P, et al. Physiological adaptations to 60 vs 20 minutes of swim training at 76% . V O2max. In: Maclaren D, Reilly T, Lees A, editors. Biomechanics and medicine in swimming. Swimming science VI. London: E & FN SPON, 1992: 195-9 65. Medbø JJ, Mohn A-C, Tabata I, et al. Anaerobic capacity determined by maximal accumulated O2 deficit. J Appl Physiol 1988; 64: 50-60 66. Miyashita M, Takahashi S, Troup J, et al. Leg extension power of elite swimmers. In: Maclaren D, Reilly T, Lees A, editors. Biomechanics and medicine in swimming. Swimming science VI. London: E & FN SPON, 1992: 295- 9 67. Costill DL, King DS, Holdren A, et al. Sprint speed vs swimming power. Swimming Tech 1983; 20 (1): 20-2 68. Sharp RL, Troup JP, Costill DL. Relationship between power and sprint freestyle swimming. Med Sci Sports Exerc 1982; 14: 53-6 69. Keskinen KL. Measurement of technique in front crawl swimming. Med Sport Sci 1994; 39: 117-25 70. Costill DL. Inside running: basics of sports physiology. Indianapolis (IN): Benchmark Press, 1986 71. D’Acquisto LJ, Costill DL. Relationship between intracyclic linear body velocity fluctuations, power and sprint breaststroke performance. J Swimming Res 1998; 13: 8-14 72. Mahoney MJ, Avener M. Psychology of the elite athlete: an exploratory study. Cognit Ther Res 1977; 1: 135-41

Sports Med 2002; 32 (9)

Performance Evaluation of Swimmers

73. Burton D. Do anxious swimmers swim slower? Re-examining the elusive anxiety-performance relationship. J Sport Exerc Psychol 1988; 10: 45-61 74. Martens R. Sport competition anxiety test. Champaign (IL): Human Kinetics, 1977 75. Martens R, Burton D, Vealey RS, et al. Cognitive and somatic dimensions of competitive anxiety CSAI-2. In: Bump LA, Smitt DE, editors. NASPSPA Conference; 1982 Jun 10-12; College Park (MD) 76. Hannin YL. Individual zones of optimal functioning (IZOF model: an ideographic approach to performance anxiety). In: Henschen KP, Straub WF, editors. Sport psychology: an analysis of behavior. Longmeadow (MA): Movement Publications, 1995: 103-19 77. Morgan WP. The trait psychology controversy. Res Q Exerc Sport 1980; 51: 50-76 78. Ostrow AC. Directory of psychological tests in the sport and exercise sciences. 2nd Ed. Morgantown (WV): Fitness Information Technology Inc., 1996 79. Smith RE, Schutz RW, Smoll FL, et al. Development and validation of a multidimensional measure of sport specific psychological skills: the Athletic Coping Skills Inventory – 28. J Sport Exerc 1995; 17 (4): 379-415 80. Kellmann M, Kallus KW. Recovery-stress questionnaire for athletes. Champaign (IL): Human Kinetics, 2001 81. Nideffer R. Test of attentional and interpersonal style. J Pers Soc Psychol 1976; 34: 394-404 82. McNair D, Lorr M, Droppleman L. Profile of mood states manual. San Diego (CA): Educational and Testing Service, 1971 83. Grove JR, Prapavessis H. Reliability and validity data for an abbreviated version of the Profile of Mood States. Int J Sport Psychol 1992; 23: 93-109 84. Watson GG, Blanksby BA, Bloomfield J. Mental health components of performance among elite junior swimmers. Aust J Sports Med Exerc Sci 1982; 15 (2): 42-55 85. Vealey R. Conceptualization of sport-confidence and competitive orientation: preliminary investigation and instrument development. J Sport Psychol 1986; 8: 221-46 86. Vealey RS, Walter-Hayashi S, Garner-Holman M, et al. Sources of sport confidence: conceptualization and instrument measurement. J Sport Exerc Psychol 1998; 20: 54-80 87. Mahoney MJ, Gabriel TJ, Perkins TS. Psychological skills and exceptional athletic performance. Sport Psychol 1987; 1: 181-99 88. Hogg JM. Mental skills for competitive swimmers. 2nd ed. Edmonton (AB): Sport Excel Publishing Inc., 2000 89. Anshell MH. Towards validation of a model for coping with acute stress in sport. Int J Sports Psychol 1990; 21: 58-83 90. Murphy SM, Greenspan M, Jowdy D, et al. Development of a brief rating instrument of competitive anxiety: comparisons with the Competitive State Anxiety Inventory – 2. In: Proceedings of the Association for the Advancement of Applied Sport Psychology; 1989 Sep 27-30; Seattle (WA) 91. Hogg JM. The process of debriefing: a means to increasing recovery and subsequent performance. In: Kellman M, editor. Optimal recovery: preventing underperformance in athletes. Champaign (IL): Human Kinetics, 2002: 181-98

 Adis International Limited. All rights reserved.

553

92. Anshel MH. An examination of self-regulatory cognitivebehavioral strategies of Australian elite and non-elite competitive male swimmers. Aust Psychol 1995; 30: 78-83 93. Hanrahan SJ, Grove JR. Further examination of the psychometric properties of the Sport Attributional Style Scale. J Sport Behav 1990; 13: 183-93 94. Rushall BS, Fox RG. An approach-avoidance motivation scale for sports. Can J of Appl Sport Sci 1980; 5: 39-43 95. Duda JL. Relationship between task and ego orientation and the perceived purpose of sport among high school athletes. J Sport Exerc Psychol 1989; 11: 318-35 96. Youngblood D, Suinn RM. A behavior assessment of motivation. In: Suinn RM, editor. Psychology in sports. Minneapolis (MN): Burgess Publishing Company, 1980: 73-7 97. Power TG, Woolger C. Parenting practices and age group swimming: a correlational study. Res Q Exerc Sport 1994; 65: 59-66 98. Rushall BS. A tool for measuring stress tolerance in elite athletes. J Appl Sport Psychol 1990; 2: 51-66 99. Brawley L, Carron A, Widmeyer W. Assessing the cohesion of teams: validity of the Group Environment Questionnaire. J Sport Psychol 1987; 9: 275-94 100. Gill DL, Deeter TE. Development of the Sport Orientation Questionnaire. Res Q Exerc Sport 1988; 59: 191-202 101. Costa PT, McCrae RR. The NEO personality inventory manual. Odessa (FL): Psychological Assessment Resources, 1985 102. Frost RO, Henderson KJ. Perfectionism and reactions to athletic competition. J Sport Exerc Psychol 1991; 13: 323-335 103. Frost RO, Marten P, Lahart C, et al. The dimensions of perfectionism. Cognit Ther Res 1990; 14 (6): 449-68 104. Terry P. The efficacy of mood state profiling with elite performers: a review and synthesis. Sport Psychol 1995; 9: 309-24 105. Hogg JM. Mental skills for swim coaches. Edmonton (AB): Sport Excel Publishing Inc., 1995 106. Hanlon S, Jones G. The acquisition and development of cognitive skills and strategies. I: making the butterflies fly in formation. Sport Psychol 1999; 13: 1-21 107. Hanlon S, Jones G. The effect of a multimodal intervention program on performers. II: training the butterflies to fly in formation. Sport Psychol 1999; 13: 22-41 108. McKenzie TL, Rushall BS. Effects of self-recording on attendance and performance in a competitive swimming training environment. J Appl Behav Anal 1974; 7: 199-206 109. Raglin JS, Stager JM, Koceja DM, et al. Changes in mood state, neuro muscular function, and performance during a season of training in female collegiate swimmers. Med Sci Sport Exerc 1996; 28: 372-7 110. Jones G, Swain A. Intensity and direction as dimensions of competitive state anxiety and relationships with competitiveness. Percept Mot Skills 1992; 74: 467-72 111. Jones G, Swain A. Predisposition to experience debilitative and facilitative anxiety in elite and non-elite performers. Sport Psychol 1995; 9: 201-11 112. Butler RJ, Hardy L. The performance profile: theory and application. Sport Psychol 1992; 6: 253-64 113. Rushall BS, Sherman CA. A definition and measurement of pressure in sport. J Appl Res Coaching Athletics 1987; 2: 1-23

Sports Med 2002; 32 (9)

554

114. Hogg JM. Post performance debriefing. Am Swimming Mag 1998; 8 (6): 4-10 115. Crocker PRE, Isaak K. Coping during competitions and training sessions: are young swimmers consistent? Int J Sport Psychol 1997; 28: 335-8 116. Ripol W. The psychology of the swimming taper. Contemp Psychol Perform Enhancement 1993; 2: 22-64 117. Burton D. Winning isn’t everything: examining the impact of performance goals on collegiate swimmers’ cognitions and performance. Sport Psychol 1989; 3: 105-32 118. The American Psychological Association. Ethical principles of psychologists and code of conduct. Am Psychol 1992; 47: 1597-611

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Smith et al.

119. Nideffer R. The ethics and practice of applied sport psychology. Ithaca (NY): Movement Publications, 1981 120. Ogilvie BC. The value in collecting psychometric data. In: Sport psychology: an analysis of athlete behavior. Henschen KP, Straub WF, editors. Longmeadow (MA): Movement Publications, 1995: 277-86

Correspondence and offprints: David J. Smith, Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, 2500 University Drive N.W., Calgary, AB T2N 1N4, Canada.

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