Search

Aim of the study was to analyze the metabolic profile of badminton matches and training drills. Therefore, 11 male (23.2 ± 3.8 years, 182 ± 7 cm, 74.4 ± 8.4 kg) and five female (19.3 ± 1.5 years, 170 ± 6 cm, 62.6 ± 9.2 kg) elite badminton players participated in either a training match (TM; n = 7) and/or three protocols of multifeeding drills (T10, T30,T50;n = 13), that varied in interval and rest durations (10 s/10 s, 30 s/30 s, 50 s/50 s). Absolute and relative energetic costs (Wtot and Etot) and contribution to oxidative (WOxid), phosphagen (WPCr), and anaerobic glycolytic (WLa) metabolism were calculated by the three‐component PCr‐La‐O2‐method based on an indirect calorimetric approach from oxygen consumption during exercise, post exercise, and net blood lactate concentration. A novel intermittent approach was used to consider replenishment of phosphocreatine during each resting phase. Results show that during TM, Etot was 676 ± 98J·kg−1 min−1, while metabolic pathways contributed by 56.9 ± 8.6% (WOxid), 42.7 ± 8.7% (WPCr), and 0.4 ± 0.6% (WLa). In the multifeeding drills Etot was comparable between T10 (1020 ± 160J·kg−1 min−1) and T30 (985 ± 173 J·kg−1 min−1) but higher in T50 (1266 ± 194J·kg−1 min−1) (p < 0.001). Relative contribution of WOxid was lower in T10 (47.3 ± 7.7%) but similar in T30 (56.5 ± 6.2%) and T50 (57.3 ± 6.0%) (p < 0.001). WPCr was highest in T10 (51.1 ± 8.3%) followed by T30 (42.2 ± 6.9%) and lowest in T50 (31.2 ± 7.7%) (p < 0.001). WLa was similar between T10 (1.6 ± 1.0%) and T30 (2.1 ± 1.0%) but higher in T50 (11.6 ± 4.8%) (p < 0.001). Concludingly, metabolic costs in badminton are predominantly covered by oxidative and phosphagen energetic pathways. Metabolic profiles of the multifeeding drills differ depending on rally/interval duration, with increasing contribution of anaerobic glycolysis and decreasing phosphagen contribution in case of longer intervals. Plain Language Summary: Badminton stands out as a high‐paced and exceptionally demanding sport, necessitating a very complex interaction between the aerobic and anaerobic metabolic systems. Using an innovative approach of indirect caloric measurement, the main aim of the investigation was to determine the metabolic profiles of elite badminton match play and badminton‐specific training drills. Therefore, 16 elite players conducted either a training match and/or three different protocols of a multifeeding drill (with varying interval/rest durations). The study underscores a pivotal role of anaerobic alactic energy supply in badminton, highlighting the critical need for rapid phosphocreatine (PCr) replenishment to prevent performance decline attributed to increasing acidosis. While aerobic capacity remains vital for PCr replenishment, occasional reliance on lactic metabolism may be important in certain probable match deciding situations. The multifeeding drills exhibit variations in the metabolic profile depending on rally and rest durations. As the interval length increases, the dominance of aerobic and lactic metabolism rises, while the proportion of anaerobic alactic contribution decreases. Emphasizing that in on‐court drills different interval durations address different metabolic pathways, training content should be chosen wisely to accurately address individual training goals and to align with a long‐term training periodization perspective. Highlights: This is the first study using an intermittent approach of the three‐component PCr‐La‐O2‐method, to determine the metabolic profile of elite badminton match play and the impact of drill prescription on metabolic stress in badminton‐specific training drills.The present findings reveal that energy in badminton generally is predominantly derived from oxidative and phosphagen energetic pathways, with the anaerobic glycolytic system contributing only minimally.Multifeeding drills essentially mirror the metabolic demands of matches but exhibit variations depending on rally and rest periods. These findings underscore the need to select training protocols thoughtfully, tailor training according to individualized goals and to structure those goals within a long‐term training periodization. [ABSTRACT FROM AUTHOR]

The study explores the validity of the nonlinear index alpha 1 of detrended fluctuation analysis (DFAa1) of heart rate (HR) variability for exercise prescription in prolonged constant load running bouts of different intensities. 21 trained endurance athletes (9 w and 12 m) performed a ramp test for ventilatory threshold (vVT1 and vVT2) and DFAa1‐based (vDFAa1‐1 at 0.75 and vDFAa1‐2 at 0.5) running speed detection as well as two 20‐min running bouts at vDFAa1‐1 and vDFAa1‐2 (20‐vDFAa1‐1 and 20‐vDFAa1‐2), in which HR, oxygen consumption (VO2), respiratory frequency (RF), DFAa1, and blood lactate concentration [La‐] were assessed. 20‐vDFAa1‐2 could not be finished by all participants (finisher group (FG), n = 15 versus exhaustion group (EG), n = 6). Despite similar mean external loads of vDFAa1‐1 (10.6 ± 1.9 km/h) and vDFAa1‐2 (13.1 ± 2.4 km/h) for all participants compared to vVT1 (10.8 ± 1.7 km/h) and vVT2 (13.2 ± 1.9 km/h), considerable differences were present for 20‐vDFAa1‐2 in EG (15.2 ± 2.4 km/h). 20‐vDFAa1‐1 and 20‐DFAa1‐2 yielded significant differences in FG for HR (76.2 ± 5.7 vs. 86.4 ± 5.9 %HRPEAK), VO2 (62.1 ± 5.0 vs. 77.5 ± 8.6 %VO2PEAK), RF (40.6 ± 11.3 vs. 46.1 ± 9.8 bpm), DFA‐a1 (0.86 ± 0.23 vs. 0.60 ± 0.15), and [La‐] (1.41 ± 0.45 vs. 3.34 ± 2.24 mmol/L). Regarding alterations during 20‐vDFAa1‐1, all parameters showed small changes for all participants, while during 20‐vDFAa1‐2 RF and DFAa1 showed substantial alterations in FG (RF: 15.6% and DFAa1: −12.8%) and more pronounced in EG (RF: 20.1% and DFAa1: −35.9%). DFAa1‐based exercise prescription from incremental testing could be useful for most participants in prolonged running bouts, at least in the moderate to heavy intensity domain. In addition, an individually different increased risk of overloading may occur in the heavy to severe exercise domains and should be further elucidated in the light of durability and decoupling assessment. Highlights: DFAa1‐based exercise prescription from incremental testing shows potential for prolonged constant load exercise, at least in the moderate to heavy intensity domains for most trained runners.Caution is advised for the heavy to severe exercise domains as individual overload may occur.The relationship of DFAa1 and vDFAa1 seems to be highly individual as well as perspectives for the durability and decoupling assessment and should be further elucidated during longer exercise bouts. [ABSTRACT FROM AUTHOR]

Purpose: To assess the test–retest reliability of the continuous (PCr-LA-O2) and intermittent (PCr-LA-O2int) version of the 3-component model of energy distribution in an applied setting. Methods: Sixteen male handball players (age 23 [3] y, height 185 [7] cm, weight 85 [14] kg) completed the 30–15 Intermittent Fitness Test (30–15IFT) twice. Performance was assessed by peak speed (speed of the last successfully completed stage of the 30–15IFT [VIFT], in kilometers per hour) and time to exhaustion (in seconds). Oxygen uptake (in milliliters per kilogram per minute) and blood lactate concentrations (in millimoles per liter) were obtained before, during, and until 15 minutes after exercise. Total metabolic energy (in joules per kilogram), total metabolic power (in watts per kilogram), and energy shares (in joules per kilogram and percentage) of the aerobic (energy contribution of the aerobic system [WAERint]), anaerobic lactic, and anaerobic alactic (anaerobic alactic energy [WPCrint]) systems were calculated using both model versions, respectively. Results: Test–retest reliability was very good for VIFT (limits of agreement [LoA]: −1.13 to 0.63 km·h−1, coefficient of variation [CV%] 1.68), time to exhaustion (LoA: −101 to 38 s, CV% 2.92), peak oxygen uptake (LoA: −2.68 to 4.04 mL·min−1·kg−1, CV% 1.48), and peak heart rate (−6.9 to 7.7 beats·min−1, CV% 1.1), but moderate for change in blood lactate concentration (LoA: −3.84 to 4.07 mmol·L−1, CV% 11.43). Reliability of the modeled total energy and its fractions were high for total metabolic energy (LoA: −1489 to 1177 J·kg−1, CV% 2.88), total metabolic power (LoA: −2.0 to 1.9 W·kg−1, CV% 3.58), contribution of aerobic (LoA: −1673 to 1283 J·kg−1, CV% 3.62), WAERint (LoA: −1760 to 2160 J·kg−1, CV% 6.04), and moderate for anaerobic alactic (LoA: −368 to 439 J·kg−1, CV% 14.85), WPCrint (LoA: −1707 to 988 J·kg−1, CV% 9.98), and energy share of anaerobic lactic concentration (LoA: −229 to 235 J·kg−1, CV% 11.43). Conclusion: Considering the inherent fluctuations of the underlying energetics, the reliabilities of both versions of the 3-component model of energy distribution are acceptable for applied settings. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the metabolic relevance of type of locomotion in anaerobic testing by analyzing and comparing the metabolic profile of the Bosco Continuous Jumping Test (CJ30) with the corresponding profile of the Wingate Anaerobic Test (WAnT). Methods: A total of 11 well-trained, male team-sport athletes (age = 23.7 [2.2] y, height = 184.1 [2.8] cm, weight = 82.4 [6.4] kg) completed a CJ30 and WAnT each. During the WAnT, power data and revolutions per minute were recorded, and during the CJ30, jump height and jumping frequency were recorded. In addition, oxygen uptake and blood lactate concentration were assessed, and metabolic profiles were determined via the PCr-LA-O2 method. Results: In the CJ30, metabolic energy was lower (109.3 [18.0] vs 143.0 [13.1] kJ, P <.001, d = −2.302), while peak power (24.8 [4.4] vs 11.8 [0.5] W·kg−1, P <.001, d = 3.59) and mean power (20.8 [3.6] vs 9.1 [0.5] W·kg−1, P <.001, d = 4.14) were higher than in the WAnT. The metabolic profiles of the CJ30 (aerobic energy = 20.00% [4.7%], anaerobic alactic energy [WPCr] = 45.6% [4.5%], anaerobic lactic energy = 34.4% [5.2%]) and the WAnT (aerobic energy = 16.0% [3.0%], anaerobic alactic WPCr = 34.5% [5.0%], anaerobic lactic energy = 49.5% [3.3%]) are highly anaerobic. Absolute energy contribution for the CJ30 and WAnT was equal in WPCr (49.9 [11.1] vs 50.2 [11.2] kJ), but anaerobic lactic energy (37.7 [7.7] vs 69.9 [5.3] kJ) and aerobic energy (20.6 [5.7] vs 23.0 [4.0] kJ) were higher in the WAnT. Mechanical efficiency was substantially higher in the CJ30 (37.9% [4.5%] vs 15.6% [1.0%], P <.001, d = 6.86), while the fatigue index was lower (18.5% [3.8%] vs 23.2% [3.1%], P <.001, d = −1.38) than in the WAnT. Conclusions: Although the anaerobic share in both tests is similar and predominant, the CJ30 primarily taxes the WPCr system, while the WAnT more strongly relies on the glycolytic pathway. Thus, the 2 tests should not be used interchangeably, and the type of locomotion seems crucial when choosing an anaerobic test for a specific sport. [ABSTRACT FROM AUTHOR]

Purpose: To elucidate the role of inter-effort recovery in shuttle running by comparing the metabolic profiles of the 30-15 Intermittent Fitness Test (30-15IFT) and the corresponding continuous version (30-15IFT-CONT). Methods: Sixteen state-level handball players (age = 23 [3] y, height = 185 [7] cm, weight = 85 [14] kg) completed the 30-15IFT and 30-15IFT-CONT, and speed at the last completed stage (in kilometers per hour) and time to exhaustion (in seconds) were assessed. Furthermore, oxygen uptake (in milliliters per kilogram per minute) and blood lactate were obtained preexercise, during exercise, and until 15 minutes postexercise. Metabolic energy (in kilojoules), metabolic power (in Watts per kilogram), and relative (in percentage) energy contribution of the aerobic (WAER, WAERint), anaerobic lactic (WBLC, WBLCint), and anaerobic alactic (WPCr, WPCrint) systems were calculated by PCr-La-O2 method for 30-15IFT-CONT and 30-15IFT. Results: No difference in peak oxygen uptake was found between 30-15IFT and 30-15IFT-CONT (60.6 [6.6] vs 60.5 [5.1] mL·kg−1·min−1, P =.165, d = 0.20), whereas speed at the last completed stage was higher in 30-15IFT (18.3 [1.4] vs 16.1 [1.0] km·h−1, P <.001, d = 1.17). Metabolic energy was also higher in 30-15IFT (1224.2 [269.6] vs 772.8 [63.1] kJ, P <.001, d = 5.60), and metabolic profiles differed substantially for aerobic (30-15IFT = 67.2 [5.2] vs 30-15IFT-CONT = 85.2% [2.5%], P <.001, d = −4.01), anaerobic lactic (30-15IFT = 4.4 [1.4] vs 30-15IFT-CONT = 6.2% [1.8%], P <.001, d = −1.04), and anaerobic alactic (30-15IFT = 28.4 [4.7] vs 30-15IFT-CONT = 8.6% [2.1%], P <.001, d = 5.43) components. Conclusions: Both 30-15IFT and 30-15IFT-CONT are mainly fueled by aerobic energy, but their metabolic profiles differ substantially in both aerobic and anaerobic alactic energy contribution. Due to the presence of inter-effort recovery, intermittent shuttle runs rely to a higher extent on anaerobic alactic energy and a fast, aerobic replenishment of PCr during the short breaks between shuttles. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the energetic profiles of the Yo-Yo Intermittent Recovery Tests 1 and 2 (YYIR1 and YYIR2). Methods: Intermittent running distance (IR1D and IR2D), time to exhaustion (IR1T and IR2T), and total recovery time between shuttles (IR1R and IR2R) were measured in 10 well-trained male athletes (age 24.4 [2.0] y, height 182 [1] cm, weight 75.8 [7.9] kg). Respiratory gases and blood lactate (BLC) were obtained preexercise, during exercise, and until 15 min postexercise. Metabolic energy, average metabolic power , and energy share (percentage of aerobic [WAER], anaerobic lactic [WBLC], and anaerobic alactic energy system [WPCr]) were calculated using the PCr-La-O2 method. Results: Peak oxygen consumption was possibly higher in YYIR2 (60.3 [5.1] mL·kg−1·min−1) than in YYIR1 (P =.116, 57.7 [4.5] mL·kg−1·min−1, d = −0.58). IR1D, IR1T, and IR1R were very likely higher than IR2D, IR2T, and IR2R, respectively (P <.001, 1876 [391] vs 672 [132] m, d = −2.83; P <.001, 916 [175] vs 304 [57] s, d = −3.03; and P <.001, 460 [100] vs 150 [40] s, d = −2.83). Metabolic energy was most likely lower in YYIR2 than in YYIR1 (P <.001, 493.5 [118.1] vs 984.8 [171.7] kJ, d = 3.24). Average metabolic power was most likely higher in YYIR2 than in YYIR1 (P <.001, 21.5 [1.7] vs 14.5 [2.2] W·kg−1, d = 3.54). When considering aerobic phosphocreatine restoration during breaks between shuttles, WAER (P =.693, 49% [10%] vs 48% [5%], d = −0.16) was similar, WPCr (P =.165, 47% [11%] vs 42% [6%], d = −0.54) possibly higher, and WBLC (P <.001, 4% [1%] vs 10% [3%], d = 1.95) almost certainly lower in YYIR1 than in YYIR2. Conclusions:WAER and WPCr are predominant in YYIR1 and YYIR2 with almost identical WAER. Higher IR1D and IR1T in YYIR1 result in higher metabolic energy but lower average metabolic power and slightly lower peak oxygen consumption. Higher IR1R allows for higher reliance on WPCr in YYIR1, while YYIR2 requires a higher fraction of WBLC. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the energetic profile of the Basketball Exercise Simulation Test (BEST). Methods: Ten male elite junior basketball players (age 15.5 [0.6] y, height 180 [9] cm, and body mass 66.1 [11.2] kg) performed a modified BEST (20 circuits consisting of jumping, sprinting, jogging, shuffling, and short breaks) simulating professional basketball game play. Circuit time, sprint time, sprint decrement, oxygen uptake (VO2), heart rate, and blood lactate concentration (blc) were obtained. Metabolic energy and metabolic power above rest (Wtot and Ptot), as well as energy share in terms of aerobic (Waer), glycolytic (Wblc), and high-energy phosphates (WPCr), were calculated from VO2 during exercise, net lactate production, and the fast component of postexercise VO2 kinetics, respectively. Results:Waer, Wblc, and WPCr reflect 89% (2%), 5% (1%), and 6% (1%) of total energy needed, respectively. Assuming an aerobic replenishment of PCr energy stores during short breaks, the adjusted energy share yielded Waer 66% (4%), Wblc 5% (1%), and WPCr 29% (1%). Waer and WPCr were negatively correlated (−0.72 and −0.59) with sprint time, which was not the case for Wblc. Conclusions: Consistent with general findings on energy system interaction during repeated high-intensity exercise bouts, the intermittent profile of the BEST relies primarily on aerobic energy combined with repetitive supplementation by anaerobic utilization of high-energy phosphates. [ABSTRACT FROM AUTHOR]

Purpose: To analyze time-domain, spectral, and fractal properties of speed regulation during half-marathon racing. Methods: In 21 male experienced runners, high-resolution data on speed (V), stride frequency (SF), and stride length (SL) were assessed during half-marathon competition (21,098 m). Performance times, time-and frequency-domain variability, spectral-scaling exponent (beta), and fractal dimension (FD) of V, SF, and SL were analyzed. Results: V of 3.65 ± 0.41 m/s, SF of 1.41 ± 0.05 Hz, and SL of 2.58 ± 0.25 m occurred with higher (P < .05) individual variability in V and SL than in SF. Beta and FD were always 1.04-1.88 and 1.56-1.99, respectively. Beta and FD differed (P < .05) in SF and SL compared with V and were correlated in V and SL (r = .91, P < .05). Spectral peaks of V, SF, and SL occurred at wavelengths of 3-35 min, and those of V and SL were interrelated (r = .56, P < .05). Mean SF and mean SL were significantly correlated with performance (r = .59 and r = .95, P < .05). SL accounted for 84% ± 6% and SF for 16% ± 6% of speed variability. Conclusions: The observed nonrandom fluctuations in V, SF, and SL correspond to nonstationary fractional Brownian motion with inherent long-range correlations. This indicates a similar complex regulation process in experienced runners that is primarily mediated via SL. [ABSTRACT FROM AUTHOR]

Within the last years complex models of cardiovascular regulation and exercise fatigue have implemented heart rate variability (HRV) as a measure of autonomic nervous system. Using detrended fluctuation analysis (DFA) to assess heart rate correlation properties, the present study examines the influence of exercise intensity on total variability and complexity in non-linear dynamics of HRV. Sixteen cyclists performed a graded exercise test on a bicycle ergometer. HRV time domain measures and fractal correlation properties were analyzed using short-term scaling exponent alpha1 of DFA. Amplitude and complexity of HRV parameters decreased significantly. DFA-alpha1 increased from rest to low exercise intensity and showed an almost linear decrease from higher intensities until exhaustion. These findings support a qualitative change in self-organized heart rate regulation from a complex autonomic control at rest and low intensities towards a breakdown of the interaction in control mechanisms with non-autonomic heart rate control dominating at high intensities. [ABSTRACT FROM AUTHOR]

There is only very limited data examining cardiovascular responses in real-world endurance training/competition. The present study examines the influence of a marathon race on non-linear dynamics of heart rate (HR) variability (HRV). Eleven male recreational runners performed a self-paced marathon road race on an almost flat profile. During the race, heart rate and beat-to-beat (RR) intervals were recorded continuously. Besides HRV time-domain measurements, fractal correlation properties using short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA-alpha1) were calculated. The mean finishing time was 3:10:22 ± 0:17:56 h:min:s with a blood lactate concentration of 4.04 ± 1.12 mmol/L at the end of the race. Comparing the beginning to the end segment of the marathon race (Begin vs. End) significant increases could be found for km split time (p < .001, d = .934) and for HR (p = .010, d = .804). Significant decreases could be found for mean RR (p = .013, d = .798) and DFA-alpha1 (p = .003, d = 1.132). DFA-alpha1 showed an appropriate dynamic range throughout the race consisting of both uncorrelated and anti-correlated values. Lactate was consistent with sustained high intensity exercise when measured at the end of the event. Despite the runners slowing after halfway, DFA-alpha1 continued to fall to values seen in the highest intensity domain during incremental exercise testing in agreement with lactate assessment. Therefore, the discrepancy between the reduced running pace with that of the decline of DFA-alpha1, demonstrate the benefit of using this dimensionless HRV index as a biomarker of internal load during exercise over the course of a marathon race. [ABSTRACT FROM AUTHOR]