@article{SaalChaabeneHelmetal.2022,
  author    = {Saal, Christian and Chaabene, Helmi and Helm, Norman and Warnke, Torsten and Prieske, Olaf},
  title     = {Network analysis of associations between anthropometry, physical fitness, and sport-specific performance in young canoe sprint athletes},
  series = {Frontiers in sports and active living},
  volume    = {4},
  journal   = {Frontiers in sports and active living},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {2624-9367},
  doi       = {10.3389/fspor.2022.1038350},
  pages     = {13},
  year      = {2022},
  abstract  = {Introduction Anthropometric and physical fitness data can predict sport-specific performance (e.g., canoe sprint race time) in young athletes. Of note, inter-item correlations (i.e., multicollinearity) may exist between tests assessing similar physical qualities. However, multicollinearity among tests may change across age and/or sex due to age-/sex-specific non-linear development of test performances. Therefore, the present study aimed at analyzing inter-item correlations between anthropometric, physical fitness, and sport-specific performance data as a function of age and sex in young canoe sprint athletes. Methods Anthropometric, physical fitness, and sport-specific performance data of 618 male and 297 female young canoe sprint athletes (discipline: male/female kayak, male canoe) were recorded during a national talent identification program between 1992 and 2019. For each discipline, a correlation matrix (i.e., network analysis) was calculated for age category (U13, U14, U15, U16) and sex including anthropometrics (e.g., standing body height, body mass), physical fitness (e.g., cardiorespiratory endurance, muscle power), and sport-specific performance (i.e., 250 and 2,000-m on-water canoe sprint time). Network plots were used to explore the correlation patterns by visual inspection. Further, trimmed means (mu(trimmed)) of inter-item Pearson's correlations coefficients were calculated for each discipline, age category, and sex. Effects of age and sex were analyzed using one-way ANOVAs. Results Visual inspection revealed consistent associations among anthropometric measures across age categories, irrespective of sex. Further, associations between physical fitness and sport-specific performance were lower with increasing age, particularly in males. In this sense, statistically significant differences for mu(trimmed) were observed in male canoeists (p < 0.01, xi = 0.36) and male kayakers (p < 0.01, xi = 0.38) with lower mu(trimmed) in older compared with younger athletes (i.e., >= U15). For female kayakers, no statistically significant effect of age on mu(trimmed) was observed (p = 0.34, xi = 0.14). Discussion Our study revealed that inter-item correlation patterns (i.e., multicollinearity) of anthropometric, physical fitness, and sport-specific performance measures were lower in older (U15, U16) versus younger (U13, U14) male canoe sprint athletes but not in females. Thus, age and sex should be considered to identify predictors for sport-specific performance and design effective testing batteries for talent identification programs in canoe sprint athletes.},
  language  = {en}
}
@article{SandauGranacher2020,
  author    = {Sandau, Ingo and Granacher, Urs},
  title     = {Effects of the barbell load on the acceleration phase during the snatch in elite Olympic weightlifting},
  series = {Sports},
  volume    = {8},
  journal   = {Sports},
  number    = {5},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2075-4663},
  doi       = {10.3390/sports8050059},
  pages     = {10},
  year      = {2020},
  abstract  = {The load-depended loss of vertical barbell velocity at the end of the acceleration phase limits the maximum weight that can be lifted. Thus, the purpose of this study was to analyze how increased barbell loads affect the vertical barbell velocity in the sub-phases of the acceleration phase during the snatch. It was hypothesized that the load-dependent velocity loss at the end of the acceleration phase is primarily associated with a velocity loss during the 1st pull. For this purpose, 14 male elite weightlifters lifted seven load-stages from 70-100\% of their personal best in the snatch. The load-velocity relationship was calculated using linear regression analysis to determine the velocity loss at 1st pull, transition, and 2nd pull. A group mean data contrast analysis revealed the highest load-dependent velocity loss for the 1st pull (t = 1.85, p = 0.044, g = 0.49 [-0.05, 1.04]) which confirmed our study hypothesis. In contrast to the group mean data, the individual athlete showed a unique response to increased loads during the acceleration sub-phases of the snatch. With the proposed method, individualized training recommendations on exercise selection and loading schemes can be derived to specifically improve the sub-phases of the snatch acceleration phase. Furthermore, the results highlight the importance of single-subject assessment when working with elite athletes in Olympic weightlifting.},
  language  = {en}
}