The main barrier to the wide use of maximal accumulated oxygen deficit (MAOD) is the considerable time required to apply several sub- and supra-maximal exercise sessions. The main question of this study was whether the determination of MAOD using a single supramaximal exercise session (MAODALT) is valid and reliable in running. We investigated the effects of the supramaximal exercise intensity (A) and the reliability of a single supramaximal exercise session (B) to assess MAOD in treadmill running. For this aim 29 subjects participated in A & B studies with single allocation "A" (n=15) and "B" (n=14). The conventional MAOD and 8 MAODALT were determined in exhaustive efforts varying between 100-150% at an intensity associated with maximal oxygen uptake (i+V˙O2MAX). In B study 2 supramaximal efforts were applied to analyze the test-retest reliability. Non-significant differences were found between MAOD and the 8 values of MAODALT. Despite the MAOD being statistically correlated with the MAODALT 100% i+V˙O2MAX (0.49
The aim was to verify the validity (i.e., study A) and reliability (i.e., study B) of the alternative maximal accumulated oxygen deficit determined using onlya supramaximal effort (MAODALT)to estimate anaerobic capacity [i.e., estimated by the gold standard maximal accumulated oxygen deficit method (MAOD)] during cycling. In study A, the effects of supramaximal intensities on MAODALT and the comparison with the MAOD were investigated in fourteen active subjects (26 ± 6 years). In study B, the test-retest reliability was investigated, where fourteen male amateur cyclists (29 ± 5 years) performed the MAODALT twice at 115% of the intensity associated to maximal oxygen uptake (). MAODALT determined at 130 and 150% of was lower than MAOD (p ≤ 0.048), but no differences between MAODALT determined at 100, 105, 110, 115, 120 and 140% of (3.58 ± 0.53L; 3.58 ± 0.59L; 3.53 ± 0.52L; 3.48 ± 0.72L; 3.52 ± 0.61L and 3.46 ± 0.69L, respectively) with MAOD (3.99 ± 0.64L). The MAODALT determined from the intensities between 110 and 120% of presented the better agreement and concordance with MAOD. In the test-retest, the MAODALT was not different (p > 0.05), showed high reproducibility when expressed in absolute values (ICC = 0.96, p < 0.01), and a good level of agreement in the Bland-Altman plot analysis (mean differences ± CI95%:−0.16 ± 0.53L). Thus, the MAODALT seems to be valid and reliable to assess anaerobic capacity in cycling.
The aim of the study was to investigate the effects of acute supplementation of sodium bicarbonate (NaHCO3) on maximal accumulated oxygen deficit (MAOD) determined by a single supramaximal effort (MAODALT) in running and the correlation with 200- and 400-m running performances. Fifteen healthy men (age, 23 ± 4 years; maximal oxygen uptake, 50.6 ± 6.1 mL·kg(-1)·min(-1)) underwent a maximal incremental exercise test and 2 supramaximal efforts at 110% of the intensity associated with maximal oxygen uptake, which was carried out after ingesting either 0.3 g·kg(-1) body weight NaHCO3 or a placebo (dextrose) and completing 200- and 400-m performance tests. The study design was double-blind, crossover, and placebo-controlled. Significant differences were found between the NaHCO3 and placebo conditions for MAODALT (p = 0.01) and the qualitative inference for substantial changes showed a very likely positive effect (98%). The lactic anaerobic contribution in the NaHCO3 ingestion condition was significantly higher (p < 0.01) and showed a very likely positive effect (99% chance), similar to that verified for peak blood lactate concentration (p < 0.01). No difference was found for time until exhaustion (p = 0.19) or alactic anaerobic contribution (p = 0.81). No significant correlations were observed between MAODALT and 200- and 400-m running performance tests. Therefore, we can conclude that both MAODALT and the anaerobic lactic metabolism are modified after acute NaHCO3 ingestion, but it is not correlated with running performance.
The purpose of the study was to investigate the sensitivity of an alternative maximal accumulated oxygen deficit (MAOD) method to discriminate the "anaerobic" capacity while comparing: least trained (LT) participants (n = 12), moderately trained (MT) participants (n = 12), endurance trained (ET) participants (n = 16), and rugby (RG) players (n = 11). Participants underwent a graded exercise test on a treadmill and a supramaximal effort for assessing MAOD. MAOD was calculated as the sum of oxygen equivalents from the phosphagen and glycolytic metabolic pathways. MAOD was significantly higher (P < 0.05) in RG (64.4 ± 12.1 mL · kg) than in ET (56.8 ± 5.4 mL · kg; effect size [ES] = 0.77; +13.5%), MT (53.8 ± 5.3 mL · kg; ES = 1.08; +19.8%), and LT (49.9 ± 4.5 mL · kg; ES = 1.50; +36.4%). In addition, the magnitude-based inference analysis revealed that MAOD was likely (LT vs. MT), very likely (MT vs. RG, and ET vs. RG) and most likely (LT vs. ET, and LT vs. RG) different between all groups, except for MT and ET, which presented an unclear difference. In conclusion, MAOD was sensitive enough to distinguish the "anaerobic" capacity in individuals with different training status, especially for RG players compared with LT participants and MT participants.
The aims of this study were: a) to investigate the game temporal structure in high-level table tennis competitions; b) to verify the influence of game evolution in international competitions from 2009 to 2012 (World Table Tennis Championships and the Olympic Games) on game temporal structure; c) to compare game temporal structure according to the phase of competition. Comparisons between the three international tournaments demonstrated that rally duration decreased significantly (p < 0.05) during the analyzed period (2009-2012), while the rest time increased (p < 0.05) from 2009 to 2011, but decreased (p < 0.05) from 2011 to 2012. In the competition phase analysis, it was found that rally duration decreased (p < 0.05) in the quarterfinals in relation to the semifinals and finals, while the rest time increased (p < 0.05) from the quarterfinals to semifinals and finals. Based on our findings and previous literature, we concluded that the performance level, game evolution and the competition phase influenced the game temporal structure of table tennis, considering longer rest periods adopted by elite athletes in relation to non-elite athletes, the reduction in rally duration and an increase in rest time over the 2009-2012 period and through the competition phases (quarterfinals to finals).
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