Myotypes - The relevance of muscle fiber typology in sports

... Based on these findings assessment anaerobic parameters could be used to make careful assumptions on muscle typology. Furthermore, new non-invasive methods for the assessment of muscle physiology such as near-infrared spectroscopy (Azevedo et al., 2022;Batterson et al., 2020;Ferrari et al., 2011;Hovorka et al., 2021;Neary et al., 1992;Sako et al., 2001;van der Zwaard et al., 2016) or proton magnetic resonance spectroscopy (Baguet et al., 2011;Bellinger et al., 2021aBellinger et al., , 2021bLievens, 2021;Lievens et al., 2020) (Huber, 2016;Smyth et al., 2022;Smyth & Muniz-Pumares, 2020). ...
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Purpose: Aim of this thesis was the identification and critical review of traditional and novel physiological and performance parameters for different threshold concepts and 1-, 2-, 3-km time-trial (TT) running. Methods: Physiological tests and TTs were carried out in a group of sprinters (n = 6), middle- and long-distance (n = 16) and ultra-runners (n = 3). Relationship between TT performance and physiological (V̇O2max, RE, %V̇O2max, MFO, V̇Lamax, dLa100) as well as performance parameters (vV̇O2max, vMLSS, CV, Fatmax, D’, ASR, SRR) was assessed, Additionally, correlations between all investigated parameters and agreement between velocity at different threshold concepts (vOBLA, vMLSS and CV) was analyzed. Results: V̇O2max and CV presented the strongest positive relationship with 2- (r = 0.81, r = 0.84) and 3-km (r = 0.89, r = 0.98) TT performance among physiological and performance parameters respectively. V̇Lamax, La100, D’, ASR and SRR were positively correlated with sprint performance (r = 0.73, r = 0.54, r = 0.69, r = 0.56, r = 0.43) and negatively with 2- (r = -0.41, r = -0.46, r = -0.37, r = -0.71, r = -0.81) an 3-km (r = -0.50, r = -0.53, r = -0.62, r = -0.85, r = -0.91) TT performance and vMLSS r = -0.48, r = -0.51, r = -0.62, r = -0.79, r = -0.86). Correlations coefficients for 1-km TT were lower compared to 2- and 3-km. Strong agreement was found between threshold concepts (vMLSS – vOBLA: R2 = 0.94; vMLSS – CV: R2 = 0.83) and mean differences amounted to -0.08 and -0.49 m·s-1. Conclusion: Parameters linked to aerobic metabolism displayed the strongest relationship with TTs. While anaerobic variables correlated positively with sprint performance the relationships became increasingly negative with increasing distance of TT. It can be hypothesized that influence of anaerobic metabolism is in balance for maximal running efforts around three minutes. Efforts slower than this balance point might tend to benefit from anaerobic metabolism while longer efforts might be affected in a detrimental way. Prediction of TT and threshold velocity was more accurate through performance than physiological parameters. Based on these findings, novel parameters can complement traditional test variables in running. Deliberate and differential selection of test parameters is advised for performance prediction or physiological training prescription in running and depending on race distance.
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