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Individualisation of training based on metabolic measures
Abstract
Top performances are a matter of talent but even more of “training efficiency”. Every athlete has his own limits of taking training load and responding to it. Therefore individualisation of training is necessary. This can be achieved if the coach knows (1) what his athlete needs most to improve and, according to the athlete’s characteristics, (2) which exercise is most appropriate and (3) how often, when and how long the exercise needs to be programmed. Thus, to set up an effective and individual conditioning program, it is essential to establish an accurate metabolic profile. But, this is rarely the case when using lactate and oxygen uptake measures in a classic way. We therefore developed a new methodology that enables to trace back the origin of lactate values in order to define the underlying aerobic and anaerobic capacities. Moreover, a platform to link the terminology of the coach with the researcher’s is presented. Finally a control procedure must be built in training in order to quantify how good training objectives are achieved.
Supplementary resource (1)
... The VLa max has been determined using short maximal exercise tests in cycling [16,[19][20][21], hand cycling [21], running [8,20], and swimming [22,23]. It is believed that athletes with higher VLa max values have increased lactate synthesis at both low and high power outputs [17]. ...
We examined the blood lactate response, in terms of the maximal post-exercise concentration (La max), time to reach La max , and maximal lactate accumulation rate (VLa max), to swimming sprints of 25, 35, and 50 m. A total of 14 highly trained and elite swimmers (8 male and 6 female), aged 14-32, completed the 3 sprints in their specialization stroke with 30 min of passive rest in between. The blood lactate was measured right before and continually (every minute) after each sprint to detect the La max. The VLa max , a potential index of anaerobic lactic power, was calculated. The blood lactate concentration, swimming speed, and VLa max differed between the sprints (p < 0.001). The La max was highest after 50 m (13.8 ± 2.6 mmol·L-1 , mean ± SD throughout), while the swimming speed and VLa max were highest at 25 m (2.16 ± 0.25 m·s-1 and 0.75 ± 0.18 mmol·L-1 ·s-1). The lactate peaked approximately 2 min after all the sprints. The VLa max in each sprint correlated positively with the speed and with each other. In conclusion, the correlation of the swimming speed with the VLa max suggests that the VLa max is an index of anaerobic lactic power and that it is possible to improve performance by augmenting the VLa max through appropriate training. To accurately measure the La max and, hence, the VLa max , we recommend starting blood sampling one minute after exercise.
... In swimming,VLa max is applied (1) to characterise the athletes' anaerobic capabilities, (2) to define individual training needs and (3) to design appropriate exercises for optimising improvements in performance. [23][24][25] It was shown thatVLa increased (+20.1%) after high-intensity interval training (HIIT) and decreased (−30.1%) after (moderate) high-volume training (HVT) in young swimmers. 26 Even though exercise trials in this study were far above recommendations (≈85 s instead of 10-15 s), this indicates that training-induced changes inVLa max depend on the applied training regime, which might be due to altered lactate transporters and/or glycolytic enzyme activity. ...
Objectives
The aim of this study was to examine the reliability of maximal lactate accumulation rate (V̇Lamax) and sprint performance parameters in running and assess different approaches to determine alactic time interval (talac).
Design
Sixteen competitive runners (female = 5; male = 11) performed three trials (T1, T2 and T3) of an all-out 100-m sprint test separated by 48 h.
Methods
Time to cover the 100 m was determined by using a photoelectric light-barrier (t100,LB) and a stop-watch (t100,SW). Throughout the sprints, velocity was measured using a laser velocity guard (LAVEG) to estimate maximal velocity (vmax) and power (Pmax). The talac was calculated as the time when power decreased by 3.5% (tpmax-3.5%) and interpolated based on the sprint time (tinter,LB and tinter,SW). Reliability was assessed using intraclass correlation coefficient (ICC), typical error (TE) and smallest worthwhile change (SWC).
Results
After initial familiarisation, t100, tinter, vmax, Pmax and V̇Lamax attained excellent reliability (ICC ≥ 0.90), whereas tpmax−3.5% attained moderate reliability (ICC = 0.518). The reliability of V̇Lamax was higher when tinter,LB or tinter,SW were used (ICC = 0.960) compared to using tpmax−3.5% (ICC = 0.928). At T1, V̇Lamax was significantly higher when stop-watch measurements were used. There was no difference between tpmax−3.5% and the interpolated time intervals and the associated V̇Lamax-estimates.
Conclusions
In running, V̇Lamax and sprint performance parameters can easily and high-reliably be measured using this sport-specific field test. Interpolating talac results in similar and more reliable values of V̇Lamax. To improve the reliability and accuracy of the stop-watch estimate, a familiarisation should be performed.
... Training evaluation has been of great importance for swimming coaches allowing to increase training efficiency and thus to enhance swimming performance (Smith et al., 2002; Olbrecht and Mader, 2006). Physiological ...
Critical swimming velocity is a non-invasive technique to determine swimmer’s functional aerobic capacity that has been progressively used by swimming coaches. The purpose of the current study was to determine anaerobic critical velocity and to relate this data to short distances events in young swimmers of
both genders. Twenty age group swimmers (twelve boys and eight girls) performed maximal 10, 15, 20 and 25 m trials in front crawl swimming to determine anaerobic critical velocity from the distance-time relationship. The 50, 100 and 200 m individual best performances of the season were used to compare with anaerobic critical velocity. The mean ± standard deviation values of anaerobic critical velocity in front crawl were 1.27 ± 0.16 m/s (overall sample), 1.33 ± 0.16 m/s (boys) and 1.18 ± 0.11 m/s (girls). The results showed a strong association between anaerobic critical velocity and swimming performance in 50, 100 and 200 m front crawl for both genders. Additionally, no differences were found between 200 m swimming event velocity and the anaerobic critical velocity. These findings suggest that anaerobic critical velocity could be an important technique, providing useful feedbacks on the young swimmers anaerobic “shape”, especially for the 200 m freestyle event.
In competitive swimming, as in other competitive sports, lactate tests are commonly applied not only to describe the current metabolic performance of the swimmer but also to define appropriate training goals, intensity and volume, to monitor metabolic adaptations to training and to adjust the training periodisation in order to increase the training efficiency. Mader ([42], [44]) argued in a mathematical model of metabolic energy supply that beside the aerobic activity the lactate production also strongly affects the lactate-speed relation. This finding can explain a lot of contradictory interpretations ([28]) and paradoxes between the evaluation of lactate tests and the performances in competition and/or in training, but it also stresses the importance of examining and considering both the aerobic and anaerobic metabolic components together in order to ensure a reliable implementation of lactate test results ([56]). In the last 20 years, more basic studies support this rather theoretical approach and provide better insight in different factors, other than O2-limitation for contraction, that affect blood lactate concentrations during exercise ([19], [20]). Beside its metabolic metamorphosis, being upgraded from a glycolitic waste product to an important intermediate that helps regulating the metabolic activity, lactate has newly been described as a signalling molecule ([62]) between respectively the metabolic and nervous system and the metabolic and gene expression system. However these finding certainly need more research before any evidence based application in training.
Background:
The assessment of energetic and mechanical parameters in swimming often requires the use of an intermittent incremental protocol, whose step lengths are corner stones for the efficiency of the evaluation procedures.
Purpose:
To analyze changes in swimming kinematics and interlimb coordination behavior in 3 variants, with different step lengths, of an intermittent incremental protocol.
Methods:
Twenty-two male swimmers performed n×di variants of an intermittent and incremental protocol (n≤7; d1=200 m, d2=300 m, and d3=400 m). Swimmers were videotaped in the sagittal plane for 2-dimensional kinematical analysis using a dual-media setup. Video images were digitized with a motion-capture system. Parameters that were assessed included the stroke kinematics, the segmental and anatomical landmark kinematics, and interlimb coordination. Movement efficiency was also estimated.
Results:
There were no significant variations in any of the selected variables according to the step lengths. A high to very high relationship was observed between step lengths. The bias was much reduced and the 95%CI fairly tight.
Conclusions:
Since there were no meaningful differences between the 3 protocol variants, the 1 with shortest step length (ie, 200 m) should be adopted for logistical reasons.
Recent studies explored a new trend of critical velocity as a parameter to evaluate and monitor anaerobic training. The aim of this study was to analyse the relationship between anaerobic critical velocity and short distances performances in the four swimming techniques, in young swimmers. 12 male and 8 female swimmers (mean ±SD; age 12.10 ± 0.72 years old) performed maximal 10, 15, 20 and 25 m in the four conventional swimming techniques to determine critical velocity from the distance-time relationship. 50, 100 and 200 m individual best performances of the season were used to compare with the critical velocity assessed. The mean ± SD values of anaerobic critical velocity (m.s-1) were 1.10 ± 0.22, 1.07 ± 0.10, 0.89 ± 0.16 and 1.27 ± 0.16, for butterfly, backstroke, breaststroke and front crawl, respectively. Anaerobic critical velocity was correlated with the 50 and 100 m swimming event velocities in backstroke (r = 0.85; r = 0.86), breaststroke (r = 0.92; r = 0.90) and front crawl (r = 0.85; r = 0.91). Considering the 200 m swimming performance, relationships were found in front crawl (r = 0.90) and in breaststroke (r = 0.89). Differences (p<0.05) between anaerobic critical velocity and swimming performance were observed in all swimming techniques for the 50 m and in breaststroke, front crawl and backstroke for the 100m. There were no differences regarding the 200 m swimming performance. These findings suggest that anaerobic critical velocity may be managed as a control parameter and even to prescribe training for young swimmers.
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