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  • Author: Argyris G. Toubekis x
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Petros G. Botonis, Ioannis Malliaros, Gavriil G. Arsoniadis, Theodoros I. Platanou and Argyris G. Toubekis

Purpose: To examine the acute physiological responses and internal training load of long-interval swimming and water polo–specific drills in high-level water polo players. Methods: A total of 10 water polo players performed both a high-intensity swimming without ball (SW) with intensity corresponding to 90% of their maximum speed previously attained during a 300-m swimming test or a counterattack ball drill (CA). Both SW and CA conditions were designed to provide equal time exposure. Thus, 3 bouts of 4 minutes duration and a 3-minute passive rest were performed in each condition. The players’ physiological responses were assessed by continuous monitoring heart rate (HR) during CA and SW as well as by measuring blood lactate at the end of each condition. Rating of perceived exertion was recorded at the end of each bout. The Edwards summated HR zones were used to measure internal training load. Results: Both peak and mean HR were similar between SW and CA, and no difference was detected between conditions in the percentage time spent at 90% to 100% of HRpeak. Postexercise blood lactate (8.5 [4.1] vs 11.5 [1.9] mmol·L−1) and rating of perceived exertion (8.1 [0.8] vs 8.7 [0.5] a.u.) values were lower in CA compared with SW (P < .05). Conclusions: SW compared with CA showed similar cardiac stress but increased anaerobic metabolism activation and higher rating of perceived exertion. Either CA or SW may be both used in training practice as a means to effectively train physical conditioning of water polo players, whereas CA may also facilitate tactical preparation.

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Gavriil G. Arsoniadis, Gregory C. Bogdanis, Gerasimos Terzis and Argyris G. Toubekis

Purpose: To examine the acute effect of dry-land strength training on physiological and biomechanical parameters in a subsequent swim training session. Methods: Twelve male swimmers (age: 19.0 [2.2] y, peak oxygen uptake: 65.5 [11.4] mL·kg−1·min−1) performed a 5 × 200-m test with progressively increasing intensity. Blood lactate (BL) concentration was measured after each 200-m bout, and the speed corresponding to 4 mmol·L−1 (V4) was calculated. In the experimental (EXP) and control (CON) conditions, swimmers participated in a swim training session consisting of 1000-m warm-up, a bout of 10-second tethered swimming sprint, and 5 × 400 m at V4. In EXP condition, swimmers completed a dry-land strength training session (load: 85% of 1-repetition maximum) 15 minutes before the swimming session. In CON condition, swimmers performed the swimming session only. Oxygen uptake, BL concentration, arm-stroke rate, arm-stroke length, and arm-stroke efficiency were measured during the 5 × 400 m. Results: Force in the 10-second sprint was not different between conditions (P = .61), but fatigue index was higher in the EXP condition (P = .03). BL concentration was higher in EXP condition and showed large effect size at the fifth 400-m repetition compared with CON condition (6.4 [2.7] vs 4.6 [2.8] mmol·L−1, d = 0.63). During the 5 × 400 m, arm-stroke efficiency remained unchanged, arm-stroke length was decreased from the third repetition onward (P = .01), and arm-stroke rate showed a medium increment in EXP condition (d = 0.23). Conclusions: Strength training completed 15 minutes before a swim training session caused moderate changes in biomechanical parameters and increased BL concentration during swimming. Despite these changes, swimmers were able to maintain force and submaximal speed during the endurance training session.

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Argyris G. Toubekis, Argiro Tsolaki, Ilias Smilios, Helen T. Douda, Thomas Kourtesis and Savvas P. Tokmakidis

Purpose:

To examine the effects of active and passive recovery of various durations after a 100-m swimming test performed at maximal effort.

Methods:

Eleven competitive swimmers (5 males, 6 females, age: 17.3 ± 0.6 y) completed two 100-m tests with a 15-min interval at a maximum swimming effort under three experimental conditions. The recovery between tests was 15 min passive (PAS), 5 min active, and 10 min passive (5ACT) or 10 min active and 5 min passive (10ACT). Self-selected active recovery started immediately after the first test, corresponding to 60 ± 5% of the 100-m time. Blood samples were taken at rest, 5, 10, and 15 min after the first as well as 5 min after the second 100-m test for blood lactate determination. Heart rate was also recorded during the corresponding periods.

Results:

Performance time of the first 100 m was not different between conditions (P > .05). The second 100-m test after the 5ACT (64.49 ± 3.85 s) condition was faster than 10ACT (65.49 ± 4.63 s) and PAS (65.89 ± 4.55 s) conditions (P < .05). Blood lactate during the 15-min recovery period between the 100-m efforts was lower in both active recovery conditions compared with passive recovery (P < .05). Heart rate was higher during the 5ACT and 10ACT conditions compared with PAS during the 15-min recovery period (P < .05).

Conclusion:

Five minutes of active recovery during a 15-min interval period is adequate to facilitate blood lactate removal and enhance performance in swimmers. Passive recovery and/or 10 min of active recovery is not recommended.

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Helen T. Douda, Argyris G. Toubekis, Alexandra A. Avloniti and Savvas P. Tokmakidis

Purpose:

To identify the physiological and anthropometric predictors of rhythmic gymnastics performance, which was defined from the total ranking score of each athlete in a national competition.

Methods:

Thirty-four rhythmic gymnasts were divided into 2 groups, elite (n = 15) and nonelite (n = 19), and they underwent a battery of anthropometric, physical fitness, and physiological measurements. The principal-components analysis extracted 6 components: anthropometric, flexibility, explosive strength, aerobic capacity, body dimensions, and anaerobic metabolism. These were used in a simultaneous multiple-regression procedure to determine which best explain the variance in rhythmic gymnastics performance.

Results:

Based on the principal-component analysis, the anthropometric component explained 45% of the total variance, flexibility 12.1%, explosive strength 9.2%, aerobic capacity 7.4%, body dimensions 6.8%, and anaerobic metabolism 4.6%. Components of anthropometric (r = .50) and aerobic capacity (r = .49) were significantly correlated with performance (P < .01). When the multiple-regression model—y = 10.708 + (0.0005121 × VO2 max) + (0.157 × arm span) + (0.814 × midthigh circumference) - (0.293 × body mass)—was applied to elite gymnasts, 92.5% of the variation was explained by VO2max (58.9%), arm span (12%), midthigh circumference (13.1%), and body mass (8.5%).

Conclusion:

Selected anthropometric characteristics, aerobic power, flexibility, and explosive strength are important determinants of successful performance. These findings might have practical implications for both training and talent identification in rhythmic gymnastics.

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João Ribeiro, Argyris G. Toubekis, Pedro Figueiredo, Kelly de Jesus, Huub M. Toussaint, Francisco Alves, João P. Vilas-Boas and Ricardo J. Fernandes

Purpose:

To conduct a biophysical analysis of the factors associated with front-crawl performance at moderate and severe swimming intensities, represented by anaerobic-threshold (vAnT) and maximal-oxygen-uptake (vV̇O2max) velocities.

Methods:

Ten high-level swimmers performed 2 intermittent incremental tests of 7 × 200 and 12 × 25 m (through a system of underwater push-off pads) to assess vAnT, and vV̇O2max, and power output. The 1st protocol was videotaped (3D reconstruction) for kinematic analysis to assess stroke frequency (SF), stroke length (SL), propelling efficiency (η P), and index of coordination (IdC). V̇O2 was measured and capillary blood samples (lactate concentrations) were collected, enabling computation of metabolic power. The 2nd protocol allowed calculating mechanical power and performance efficiency from the ratio of mechanical to metabolic power.

Results:

Neither vAnT nor vV̇O2max was explained by SF (0.56 ± 0.06 vs 0.68 ± 0.06 Hz), SL (2.29 ± 0.21 vs 2.06 ± 0.20 m), η P (0.38 ± 0.02 vs 0.36± 0.03), IdC (–12.14 ± 5.24 vs –9.61 ± 5.49), or metabolic-power (1063.00 ± 122.90 vs 1338.18 ± 127.40 W) variability. vV̇O2max was explained by power to overcome drag (r = .77, P ≤ .05) and η P (r = .72, P ≤ .05), in contrast with the nonassociation between these parameters and vAnT; both velocities were well related (r = .62, P ≤ .05).

Conclusions:

The biomechanical parameters, coordination, and metabolic power seemed not to be performance discriminative at either intensity. However, the increase in power to overcome drag, for the less metabolic input, should be the focus of any intervention that aims to improve performance at severe swimming intensity. This is also true for moderate intensities, as vAnT and vV˙O2max are proportional to each other.