Correlations between body composition, aerobic capacity, speed and distance covered among professional soccer players during official matches

Radzimiński, Łukasz; Szwarc, Andrzej; Padrón-Cabo, Alexis; Jastrzębski, Zbigniew

doi:10.23736/s0022-4707.19.09979-1

Cited by 29 publications

(35 citation statements)

References 27 publications

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“…Although not statistically significant, the correlations of BF% and LBM to YYIR1 indicated a negative association agreeing with previous findings [10,11]. Two possible explanations for these differences between our study and the previous studies [10,11] could be 1) the use of different endurance tests and 2) positional difference in their samples.…”

Section: Discussionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

“…Body composition is another important fitness characteristics in soccer [10][11][12][13][14]. Previous literature [10][11][12]14] indicates that lean body mass (LBM) and body fat percentage (BF%) are related to sprinting and jumping performance in male soccer players. Based on previous literature [13,15,16], competitive senior male soccer players maintain LBM of 63.3 to 71.2 kg, with BF% ranging from 10% to 12%.…”

Section: Introductionmentioning

confidence: 99%

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Associations of Body Composition, Maximum Strength, Power Characteristics with Sprinting, Jumping, and Intermittent Endurance Performance in Male Intercollegiate Soccer Players

Ishida

Travis

Stone

2021

JFMK

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The purpose of this study was to determine the relationships between body composition, strength, power characteristics, sprinting, jumping, and intermittent endurance performance in collegiate male players. Twenty-three players participated (19.7 ± 1.6 yrs; 71.8 ± 7.1 kg; 176.5 ± 5.1 cm). Measurements of interest in body composition included body fat percentage (BF%), lean body mass (LBM), and body mass (BM). Power characteristics were measured with an unloaded squat jump (SJ0) and loaded SJ at 20 kg (SJ20) and 40 kg (SJ40), and unloaded countermovement jump (CMJ0). Power assessments included peak power (PP) and PP allometrically scaled (PPa). Strength characteristics were assessed using isometric mid-thigh pull. Strength assessment included isometric peak force (IPF) and IPF allometrically scaled (IPFa). Performance measures included 10m and 20 m sprint time, CMJ0 jump-height, and Yo-Yo intermittent endurance test level 1 distance. Significant correlations ranging from moderate to very large were found for LBM and CMJ jump height (CM0 JH) (p = 0.01, r = 0.50); BF% and sprint times at 10 m (p = 0.03, r = 0.44) and 20 m (p = 0.02, r = 0.50). PP and PPa from SJ0 and CMJ0 were significantly correlated to 10m sprint time (p < 0.05, r = −0.45 to −0.53) and 20 m sprint time (p < 0.05, r = −0.40 to −0.49). Our findings agree with previous literature in that body composition and power characteristics are directly related to soccer-related performance.

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Section: Discussionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Associations of Body Composition, Maximum Strength, Power Characteristics with Sprinting, Jumping, and Intermittent Endurance Performance in Male Intercollegiate Soccer Players

Ishida

Travis

Stone

2021

JFMK

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“…TRIM68 is associated with ubiquitination [ 67 ] and may potentially play a role in proteolytic activity and exercise induced muscle damage. Body composition has been associated with exercise capacity, including maximal workload and oxygen uptake [ 68 , 69 ]. However, more work is needed to go beyond association and to identify causal variants/genes.…”

Section: Discussionmentioning

confidence: 99%

Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study

Williams

Harvey

et al. 2021

J Biomed Sci

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Background Low cardiorespiratory fitness (V̇O2peak) is highly associated with chronic disease and mortality from all causes. Whilst exercise training is recommended in health guidelines to improve V̇O2peak, there is considerable inter-individual variability in the V̇O2peak response to the same dose of exercise. Understanding how genetic factors contribute to V̇O2peak training response may improve personalisation of exercise programs. The aim of this study was to identify genetic variants that are associated with the magnitude of V̇O2peak response following exercise training. Methods Participant change in objectively measured V̇O2peak from 18 different interventions was obtained from a multi-centre study (Predict-HIIT). A genome-wide association study was completed (n = 507), and a polygenic predictor score (PPS) was developed using alleles from single nucleotide polymorphisms (SNPs) significantly associated (P < 1 × 10–5) with the magnitude of V̇O2peak response. Findings were tested in an independent validation study (n = 39) and compared to previous research. Results No variants at the genome-wide significance level were found after adjusting for key covariates (baseline V̇O2peak, individual study, principal components which were significantly associated with the trait). A Quantile–Quantile plot indicates there was minor inflation in the study. Twelve novel loci showed a trend of association with V̇O2peak response that reached suggestive significance (P < 1 × 10–5). The strongest association was found near the membrane associated guanylate kinase, WW and PDZ domain containing 2 (MAGI2) gene (rs6959961, P = 2.61 × 10–7). A PPS created from the 12 lead SNPs was unable to predict V̇O2peak response in a tenfold cross validation, or in an independent (n = 39) validation study (P > 0.1). Significant correlations were found for beta coefficients of variants in the Predict-HIIT (P < 1 × 10–4) and the validation study (P < × 10–6), indicating that general effects of the loci exist, and that with a higher statistical power, more significant genetic associations may become apparent. Conclusions Ongoing research and validation of current and previous findings is needed to determine if genetics does play a large role in V̇O2peak response variance, and whether genomic predictors for V̇O2peak response trainability can inform evidence-based clinical practice. Trial registration Australian New Zealand Clinical Trials Registry (ANZCTR), Trial Id: ACTRN12618000501246, Date Registered: 06/04/2018, http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374601&isReview=true.

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“…Notably, a study reported that there was an inverse correlation ( r = −0.449) between body fat percentage and functional movement screen scores among college football players (Nicolozakes, Schneider, Roewer, Borchers, & Hewett, 2018). Further, there were inverse correlations between the percentage of body fat and high‐speed movement performance in sprint and distance running (Abe et al, 2020; Alvero‐Cruz et al, 2019; Herrmann et al, 2019), cycling (Schabort, Killian, St Clair Gibson, Hawley, & Noakes, 2000) and soccer matches (Radziminski, Szwarc, Padron‐Cabo, & Jastrzebski, 2019).…”

Section: Introductionmentioning

confidence: 99%

Why is low body fat rarely seen in large‐sized male athletes?

Abe

Bell

Wong

et al. 2020

American J Hum Biol

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Objectives: It is unknown why low body fat is rarely seen in large-sized athletes (>100 kg body mass). The aim of this review was to examine the relationship between body mass and body composition (fat mass and fat-free mass) in elite male athletes, and to discuss the possible reasons why low body fat is rarely seen in large-sized male athletes. Methods: A search using two electronic databases was conducted. Eighteen studies estimated body composition in elite athletes by dual-energy X-ray absorptiometry, totaling 2249 elite male athletes and 72 data points. Results: Our results indicated that low body fat (eg, less than 10% body fat) was rarely seen in large-sized male athletes over 100 kg body mass. The larger the body mass, the higher the fat-free mass, with fat-free mass leveling off when body mass exceeds approximately 120 kg. Conclusion: Possible reasons for this are unknown but we provide some ideas for why this might occur. The two different stages to consider with respect to skeletal muscle growth: the amount of growth during development and the amount of growth as a result of long-term resistance training. In certain sporting events, a large body mass may be favored. However, the large-sized athletes have to balance any potential positive influence of body mass on sports performance with the potential negative factors associated with body fat accumulation. Further research is warranted, as there is currently limited evidence on this topic.

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Correlations between body composition, aerobic capacity, speed and distance covered among professional soccer players during official matches

Cited by 29 publications

References 27 publications

Associations of Body Composition, Maximum Strength, Power Characteristics with Sprinting, Jumping, and Intermittent Endurance Performance in Male Intercollegiate Soccer Players

Associations of Body Composition, Maximum Strength, Power Characteristics with Sprinting, Jumping, and Intermittent Endurance Performance in Male Intercollegiate Soccer Players

Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study

Why is low body fat rarely seen in large‐sized male athletes?

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