Aerobic and Anaerobic Speed Predicts 800-m Running Performance in Young Recreational Runners

Støren, Øyvind; Helgerud, Jan; Johansen, Jan-Michael; Gjerløw, Lars-Erik; Aamlid, Aanund; Støa, Eva Maria

doi:10.3389/fphys.2021.672141

Cited by 8 publications

(31 citation statements)

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“…Middle distance performance such as the sprint event in cross-country skiing or middle-distance running put great demands on both aerobic (~ 80%) and anaerobic (~ 20%) metabolism (Brandon 1995;Losnegard et al 2012;Andersson et al 2017;Støren et al 2021). Accordingly, several studies report that overall sprint performance in cross Communicated by Philip D. Chilibeck.…”

Section: Introductionmentioning

confidence: 99%

“…1998;Nevill et al 2008;Billat et al 2009), with equivocal findings. As suggested in Støren et al (2021), the term anaerobic capacity could be unclear. In a short sprint, it is the maximal velocity of anaerobic energy release that matters, while in a middle-distance event it is the ability to sustain a certain amount of anaerobic energy release over time.…”

Section: Introductionmentioning

confidence: 99%

“…The term anaerobic endurance capacity would perhaps better cover a possible impact of MAOD on middle distance running or sprint cross-country skiing time performance. On the other hand, the term endurance may also be misplaced in relation to anaerobic capacity, as it has been suggested that anaerobic capacity is merely a product of anaerobic sprint reserve (ASR) (Støren et al 2021). Losnegard et al (2012Losnegard et al ( , 2013 suggested that differences in sprint performance among elite skiers are more dependent on anaerobic capacity measured as MAOD, than aerobic capacity, since improved performance in a 1000 m time trial (TT) in elite cross-country skiers were related to an increase in MAOD.…”

Section: Introductionmentioning

confidence: 99%

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Maximal aerobic and anaerobic power and time performance in 800 m double poling ergometer

et al. 2023

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The purpose of this study was to investigate to what extent aerobic power (MAP), maximal anaerobic power (MANP), anaerobic capacity measured as time to exhaustion at 130% MAP (TTE), and maximal accumulated oxygen deficit (MAOD) correlated with 800 m double poling time trial performance (800TT) in a ski ergometer. A second aim was to investigate the relationship between TTE and MAOD, and to what extent TTE and MAOD would relate to anaerobic power reserve (APR). Eighteen cross-country skiers were tested for peak oxygen uptake (VO2peak) and oxygen cost of double poling to assess MAP. Peak power measurements during a 100 m TT were performed to assess MANP. TTE and an 800TT with continuous VO2 measurements were performed to assess time performance and MAOD. All tests were performed on a ski ergometer. Both MAP and MANP correlated strongly (r = − 0.936 and − 0.922, respectively, p < 0.01) with 800TT. Neither TTE nor MAOD correlated with 800TT. TTE correlated moderately with MAOD, both in mL kg−1 and in %VO2peak (r = 0.559, p < 0.05 and 0.621, p < 0.01, respectively). Both TTE and MAOD seemed to be a product of APR. These results suggest focusing on MAP and MANP, but not anaerobic capacity to explain time performance in an event with approximately 3 min duration.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Maximal aerobic and anaerobic power and time performance in 800 m double poling ergometer

et al. 2023

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“…Thus, a soccer match can be defined as an intermittent exercise, while periods of low-to-moderate efforts are interspaced by maximal to near-maximal actions [ 4 , 5 ]. Based on the high-demanding context of soccer, players need to have well-developed aerobic and anaerobic power to be able to sustain 90 min of high-intensity explosive activities such as sprinting, changing directions, accelerations, decelerations, etc., and, in short, to cope with the demands of the game [ 6 – 9 ]. Higher levels of aerobic capacity enhance rapid recovery from explosive high-intensity intermittent movements through the increased aerobic response, improved lactate removal, and enhanced PCr regeneration and may also be a prerequisite for increasing the efficiency of anaerobic capacity when performing these efforts [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

“…The MAS reflects a player’s maximum aerobic power integrated with running economy. PSS, also called maximal anaerobic speed, indicates the highest running speed achieved with maximum anaerobic energy release [ 9 ]. Since the decisive movements in soccer occur in small areas, PSS is essential in locomotor activities that require high power [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Effects of a small-sided games training program in youth male soccer players: variations of the locomotor profile while interacting with baseline level and with the accumulated load

Silva

Oliveira

Saygın

et al. 2022

BMC Sports Sci Med Rehabil

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Purpose This study aimed to (1) analyze the impact of a small-sided game training program in the locomotor profile of youth male soccer players (while interacting with the baseline level – higher and lower level); and (2) test the relationships between variation in locomotor profile and the accumulated demands in 3v3, 5v5 and match over the period of observation. Methods The cohort lasted 3-weeks. Twenty under-17 male amateur soccer players (16.8 ± 0.41 years; experience: 6.35 ± 0.67 years) were assessed twice for their final velocity at 30−15 intermittent fitness test (VIFT), peak speed at 30-m sprint test (PSS) and anaerobic speed reserve (ASR). The PSS was estimated using a Global Positioning System, while the VIFT was estimated using the maximum level attained by the players during the test. Based on the baseline levels, the scores were standardized using the Z-score. The total score of athleticism (TSA) was calculated per player to organize the players into two groups: lower TSA and higher TSA. Over the three weeks of observation, the small-sided games of 3v3 and 5v5 and match demands were monitored using polar team pro. The heart rate responses (mean and peak), distance covered (overall and split by speed thresholds), and peak speed in these games were obtained and summed over the weeks. The repeated measures ANCOVA tested the variations (time) of the locomotor profile of players while considering the baseline as covariable and the group as a factor. The Pearson-product correlation test analyzed the relationships between variations in locomotor profile (Δ, post-baseline) and the accumulated demands in 3v3, 5v5, and match. Results Between-groups analysis (lower TSA vs. higher TSA) revealed no significant differences on VIFT (p = 0.915), PSS (p = 0.269), ASR (p = 0.258) and TSA score (p = 0.138). Within-group (baseline vs. post-observation) analysis revealed significant difference on VIFT (p < 0.001), PSS (p = 0.008), while no significant differences were found on ASR (p = 0.949) and TSA score (p = 0.619). Significant correlations were found between ΔPSS and match total distance (r = 0.444; p = 0.050), match Z2 (r = 0.481; p = 0.032) and match Z3 (r = 0.454; p = 0.044). Significant correlations were found between ΔTSA and match total distance (r = 0.457; p = 0.043), match Z1 (r = 0.451; p = 0.046), match Z2 (r = 0.500; p = 0.025) and match Z3 (r = 0.468; p = 0.037). Conclusion Significant improvements were observed after the period of observation. However, the fitness baseline level and the accumulated training load in the small-sided games seem to have no significant impact on the observed improvements.

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Identifying physiological determinants of 800 m running performance using post-exercise blood lactate kinetics

Watanabe,

Inaba,

van Rassel

et al. 2024

Eur J Appl Physiol

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Purpose The aims of the present study were to investigate blood lactate kinetics following high intensity exercise and identify the physiological determinants of 800 m running performance. Methods Fourteen competitive 800 m runners performed two running tests. First, participants performed a multistage graded exercise test to determine physiological indicators related to endurance performance. Second, participants performed four to six 30-s high intensity running bouts to determine post-exercise blood lactate kinetics. Using a biexponential time function, lactate exchange ability (γ1), lactate removal ability (γ2), and the quantity of lactate accumulated (QLaA) were calculated from individual blood lactate recovery data. Results 800 m running performance was significantly correlated with peak oxygen consumption (r = −0.794), γ1 and γ2 at 800 m race pace (r = −0.604 and −0.845, respectively), and QLaA at maximal running speed (r = −0.657). $${\dot{\text{V}}}$$ V ˙ O2peak and γ2 at 800 m race pace explained 83% of the variance in 800 m running performance. Conclusion Our results indicate that (1) a high capacity to exchange and remove lactate, (2) a high capacity for short-term lactate accumulation and, (3) peak oxygen consumption, are critical elements of 800 m running performance. Accordingly, while lactate has primarily been utilized as a performance indicator for long-distance running, post-exercise lactate kinetics may also prove valuable as a performance determinant in middle-distance running.

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Aerobic and Anaerobic Speed Predicts 800-m Running Performance in Young Recreational Runners

Cited by 8 publications

References 26 publications

Maximal aerobic and anaerobic power and time performance in 800 m double poling ergometer

Maximal aerobic and anaerobic power and time performance in 800 m double poling ergometer

Effects of a small-sided games training program in youth male soccer players: variations of the locomotor profile while interacting with baseline level and with the accumulated load

Identifying physiological determinants of 800 m running performance using post-exercise blood lactate kinetics

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