Philippe Hellard

Modeling the Training-Performance Relationship Using a Mixed Model in Elite Swimmers

PURPOSE The aim of this study was to model the relationship between training and performance in 13 competitive swimmers, over three seasons, and to identify individual and group responses to training. METHODS A linear mixed model was used as an alternative to the Banister model. Training effect on performance was studied over three training periods: short-term, the average of training load accomplished during the 2 wk preceding each performance of the studied period; mid-term, the average of training load accomplished during weeks 3, 4, and 5 before each performance; and long-term, weeks 6, 7, and 8. RESULTS Cluster analysis identified four groups of subjects according to their reactions to training. The first group corresponded to the subjects who responded well to the long-term training period, the second group to the long- and mid-term periods, the third to the short- and mid-term periods, and the fourth to the combined periods. In the model, the intersubject differences and the evolution over the three seasons were statistically significant for the identified groups of swimmers. Influence of short-term training was negative on performance in the four groups, whereas mid- and long-term training had, on the average, a positive effect in three groups out of four. Between seasons 1 and 3, the effect of mid-term training declined, whereas the effect of long-term training increased. The fit between real and modeled performances was significant for all swimmers (0.15 </= r2 </= 0.65; P </= 0.01). CONCLUSION The mixed model described a significant relationship between training and performance both for individuals and for groups of swimmers. This relationship was different over the 3 yr. Personalized training schedules could be prescribed on the basis of the model results.

Assessing the limitations of the Banister model in monitoring training.

Abstract The aim of this study was to carry out a statistical analysis of the Banister model to verify how useful it is in monitoring the training programmes of elite swimmers. The accuracy, the ill-conditioning and the stability of this model were thus investigated. The training loads of nine elite swimmers, measured over one season, were related to performances with the Banister model. First, to assess accuracy, the 95% bootstrap confidence interval (95% CI) of parameter estimates and modelled performances were calculated. Second, to study ill-conditioning, the correlation matrix of parameter estimates was computed. Finally, to analyse stability, iterative computation was performed with the same data but minus one performance, chosen at random. Performances were related to training loads for all participants (R 2 = 0.79 ± 0.13, P < 0.05) and the estimation procedure seemed to be stable. Nevertheless, the range of 95% CI values of the most useful parameters for monitoring training was wide: τ a = 38 (17, 59), τ f = 19 (6, 32), tn = 19 (7, 35), tg = 43 (25, 61). Furthermore, some parameters were highly correlated, making their interpretation worthless. We suggest possible ways to deal with these problems and review alternative methods to model the training – performance relationships.

Kinematic measures and stroke rate variability in elite female 200-m swimmers in the four swimming techniques: Athens 2004 Olympic semi-finalists and French National 2004 Championship semi-finalists

Abstract The aim of this study was to assess stroke rate variability in elite female swimmers (200-m events, all four techniques) by comparing the semi-finalists at the Athens 2004 Olympic Games (n = 64) and semi-finalists at the French National 2004 Championship (n = 64). Since swimming speed (V) is the product of stroke rate (SR) and stroke length (SL), these three variables and the coefficient of variation of stroke rate (CVSR) of the first and second 100 m were determined (V1, V2; SR1, SR2; SL1, SL2; CVSR1, CVSR2) and differences between the two parts of the events were calculated (ΔV; ΔSR; ΔSL; ΔCVSR). When the results for the four 200-m events were analysed together, SR1, SR2, SL1, and SL2 were higher (α = 0.05, P < 0.001) and ΔV, ΔSR, and ΔCVSR were lower (P < 0.01) in the Olympic group than in the National group. The Olympic-standard swimmers exhibited faster backstrokes and longer freestyle strokes (P < 0.05). Both CVSR1 and CVSR2 were lower for freestyle and backstroke races in the Olympic group than in the National group (P < 0.001). Our results suggest that stroke rate variability is dependent on an interaction between the biomechanical requisites of the task (techniques) and the standard of the swimmer.

Physiological responses during submaximal interval swimming training: Effects of interval duration

The aim of the present study was to determine the time sustained near VO2max in two interval training (IT) swimming sessions comprising 4x400 m (IT(4x400)) or 16x100 (IT(16xl00)). Elite swimmers (Mean+/-SD age 18+/-2 yrs; body mass 66.9+/-6.5 kg: swim VO2max 55.7+/-5.8 ml.kg(-1).min(-1)) completed three experimental sessions at a 50-m indoor pool over a one week period. The first test comprised a 5 x 200-m incremental test to exhaustion for determination of the pulmonary ventilation threshold (VT, m.s(-1)), VO2max, the velocity associated with VO2max (VO2max, m(s(-1)) and maximum heart rate (HR(max), b.min(-1)). The remaining two tests involved the IT(4x400) and IT(16xl00) performed in a randomised order. The two IT sessions where completed at a velocity representing 25% of the difference between the VT and the VO2max (delta25%) and in the same work to rest ratio. During the IT sessions VO2 as well as HR were measured. The duration (s) >90% VO2max, also the duration (s) >90% HR(max), were not significantly different in the IT(16x100) and IT(4x400). However, limits of agreement (LIM(AG)) analysis demonstrated considerable individual variation in the time >90% VO2max (mean difference +/-2SD = 222+/-819 s) and the time >90% HRmax (mean difference +/-2SD = 61+/-758 s) between the two IT sessions. This factor deserves further research to establish the characteristics of those athletes which influence the physiological responses in IT of short or longer duration repetitions.

Training-related risk of common illnesses in elite swimmers over a 4-yr period.

PURPOSE The objective of this study is to investigate the relation between sport training and the risk of common illnesses: upper respiratory tract and pulmonary infections (URTPI), muscular affections (MA), and all-type pathologies in highly trained swimmers. METHODS Twenty-eight French professional swimmers were monitored weekly for 4 yr. Training variables included 1) in-water and dryland intensity levels: low-load, high-load, resistance, maximal strength, and general conditioning training (expressed as the percentage of the maximal load performed by each subject, at each intensity level over the study period); and 2) training periods: moderate, intensive, taper, competition, and postcompetition. Illnesses were diagnosed by a sports physician using a standardized questionnaire. Mixed-effects logistic regression analyses were used to model odds ratios for the association between common illnesses and training variables, adjusted for sport season, semiseason (summer or winter), age, competition level, sex, and history of recent events, whereas controlling for heterogeneity among swimmers. RESULTS The risk of common illnesses was significantly higher in winter months, for national swimmers (for URTPI), and in cases of history of recent event (notably for MA). The odds of URTPI increased 1.08 (95% CI, 1.01-1.16) and 1.10 (95% CI, 1.01-1.19) times for every 10% increase in resistance and high-load trainings, respectively. The odds of MA increased by 1.49 (95% CI, 1.14-1.96) and 1.63 (95% CI, 1.20-2.21) for each 10% increase in high load and general conditioning training, respectively. The odds of illnesses were 50%-70% significantly higher during intensive training periods. CONCLUSION Particular attention must be paid to illness prevention strategies during periods of intensive training, particularly in the winter months or in case of the recent medical episode.

Whole-Body Cryostimulation Limits Overreaching in Elite Synchronized Swimmers

INTRODUCTION Elite athletes frequently undergo periods of intensified training (IT) within their normal training program. These periods can lead athletes into functional overreaching, characterized by high perceived fatigue, impaired sleep, and performance. Because whole-body cryostimulation (WBC) has been proven to be an effective recovery method in the short term (<76 h), we investigated whether daily WBC sessions during IT could prevent exercise and sleep-related signs of overreaching. METHODS After a normal training week (BASE), 10 elite synchronized swimmers performed two 2-wk IT periods in a randomized crossover fashion using WBC daily (ITWBC) or not (ITCON), separated by 9 d of light training. Swim time trials (400 m) were performed at BASE and after each IT to quantify blood lactate ([La]B), HR (HR400), salivary alpha amylase ([α-amylase]s400), and cortisol ([cortisol]s400) responses. Swimmers wore a wrist actigraph nightly to monitor sleep patterns. RESULTS Swim speed (400 m), [La]B400, and [α-amylase]s400 decreased from BASE to ITCON, although no significant changes were found after ITWBC. Decreased swim speed was correlated to decreased HR400 and [cortisol]s400. During ITCON, significant decreases in actual sleep duration (-21 ± 7 min) and sleep efficiency (-1.9% ± 0.8%) were observed, with increased sleep latency (+11 ± 5 min) and fatigue compared with BASE, although these variables did not change during ITWBC. Using a qualitative statistical analysis, we observed that daily WBC use resulted in a 98%, 59%, 66%, and 78% chance of preserving these respective variables compared with ITCON. CONCLUSION WBC use during IT helped mitigate the signs of functional overreaching observed during ITCON, such as reduced sleep quantity, increased fatigue, and impaired exercise capacity. These results support the daily use of WBC by athletes seeking to avoid functional overreaching during key periods of competition preparation.

Is it more effective for highly trained swimmers to live and train at 1200 m than at 1850 m in terms of performance and haematological benefits

Objectives: The effects of living and training have not been compared at different altitudes in well trained subjects. Methods: Nine international swimmers lived and trained for 13 days similarly at 1200 m (T1200) and 1850 m (T1850). The two altitude training periods were separated by six weeks of sea level training. Before and after each training trip, subjects performed, at an altitude of 1200 m, an incremental exercise test to exhaustion of 5 × 200 m swims and a maximal test over 2000 m. Results: There was no difference in V˙o2max after each training trip: the before values were 58.5 (5.6) and 60.4 (6.7) ml/kg/min and the after values were 56.2 (5.2) and 57.1 (4.7) ml/kg/min for T1200 and T1850 respectively. The 2000 m performance had improved during T1200 (1476 (34) to 1448 (45) seconds) but not during T1850 (1458 (35) v 1450 (33) seconds). Mean cell volume increased during T1850 (86.6 (2.8) to 88.7 (2.9) µm3) but did not change during T1200 (85.6 (2.9) v 85.7 (2.9) µm3). The proportion of reticulocytes decreased during T1200 (15.2 (3.8)% to 10.3 (3.4)%) and increased during T1850 (9.3 (1.6)% to 11.9 (3.5)%). Conclusions: The short term effects of 13 days of training at 1200 m on swimming performance appear to be greater than the same type of training for the same length of time at 1850 m. As mean cell volume and proportion of reticulocytes only increased during training at 1850 m, the benefits of training at this altitude may be delayed and appear later on.

Technology & swimming: 3 steps beyond physiology

The science of engineering materials and the development of materials science during human history have strongly evolved over the past two centuries 1,2. Other new technological fields such as particle physics, computer science, nanoscience also flourished 3 , all leading to innovations that impacted sport. Polymers and metal alloys such as carbon fibres are exemplars of materials now widely used in various disciplines 4. In 2008, polyurethane made its first appearance in swimming with the use of a new swimsuit generation. The result was a sudden improvement of performances, allowing athletes to go beyond physiological limits that have been nearly reached 5,6. This study aimed to quantify the gain provided by the three generations of swimsuits introduced in 1999, 2008, 2009 and to estimate the upcoming performance drop in 2010. Using a recently published methodology 7 , we analyzed the single best result each year for the worlds top ten swimmers from 1990 to 2009 in order to assess the sudden progression trends and quantify the total performance gain. Materials and methods We collected the best performance of the worlds top ten swimmers every year in 34 swimming events from 1963 to 2009 8-10. A total of 6790 individual performances were selected from the data spanning the 1990 – 2009 period as they present a complete measure each year. We focus here on the impact of material science in swimming by measuring the impact of the three successive generations of swimsuits on human performance and estimate the upcoming performance drop consecutive to the decision of the FINA to suspend their use. We investigate the recent evolutions of the best performers over the 1990 – 2009 period and demonstrate that three bursts of performances occurred in 2000, 2008 and 2009. The overall observed gains of these bursts exceed 2.0% for both sexes. The drop in performance that may result from this rule change may return to similar levels as seen in 1999.

Modeling the residual effects and threshold saturation of training: a case study of Olympic swimmers.

The aim of this study was to model the residual effects of training on the swimming performance and to compare a model that includes threshold saturation (MM) with the Banister model (BM). Seven Olympic swimmers were studied over a period of 4 ± 2 years. For 3 training loads (low-intensity wLIT, high-intensity wHIT, and strength training wST), 3 residual training effects were determined: short-term (STE) during the taper phase (i.e., 3 weeks before the performance [weeks 0, 1, and 2]), intermediate-term (ITE) during the intensity phase (weeks 3, 4, and 5), and long-term (LTE) during the volume phase (weeks 6, 7, and 8). ITE and LTE were positive for wHIT and wLIT, respectively (p < 0.05). Low-intensity training load during taper was related to performances by a parabolic relationship (p < 0.05). Different quality measures indicated that MM compares favorably with BM. Identifying individual training thresholds may help individualize the distribution of training loads.

Modelling of optimal training load patterns during the 11 weeks preceding major competition in elite swimmers

Periodization of swim training in the final training phases prior to competition and its effect on performance have been poorly described. We modeled the relationships between the final 11 weeks of training and competition performance in 138 elite sprint, middle-distance, and long-distance swimmers over 20 competitive seasons. Total training load (TTL), strength training (ST), and low- to medium-intensity and high-intensity training variables were monitored. Training loads were scaled as a percentage of the maximal volume measured at each intensity level. Four training periods (meso-cycles) were defined: the taper (weeks 1 to 2 before competition), short-term (weeks 3 to 5), medium-term (weeks 6 to 8), and long-term (weeks 9 to 11). Mixed-effects models were used to analyze the association between training loads in each training meso-cycle and end-of-season major competition performance. For sprinters, a 10% increase between ∼20% and 70% of the TTL in medium- and long-term meso-cycles was associated with 0.07 s and 0.20 s faster performance in the 50 m and 100 m events, respectively (p < 0.01). For middle-distance swimmers, a higher TTL in short-, medium-, and long-term training yielded faster competition performance (e.g., a 10% increase in TTL was associated with improvements of 0.1-1.0 s in 200 m events and 0.3-1.6 s in 400 m freestyle, p < 0.01). For sprinters, a 60%-70% maximal ST load 6-8 weeks before competition induced the largest positive effects on performance (p < 0.01). An increase in TTL during the medium- and long-term preparation (6-11 weeks to competition) was associated with improved performance. Periodization plans should be adapted to the specialty of swimmers.