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Competitive performance prediction of elite alpine skiers
Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Section of Sports Medicine.ORCID iD: 0000-0002-4697-0825
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Introduction: The overall aim of this doctoral thesis was to identify physiological and anthropometric variables valid for prediction of competitive performance in alpine skiing (indicated by FIS points).

Method: Paper I-III in this doctoral thesis followed an experimental, hypothesis-generating design which included both junior and senior elite alpine skiers. In all papers, physiological and anthropometric test results (X-variables) were correlated with FIS points (Y-variables) in order to investigate the predictive power of physiological and anthropometric variables for competitive performance in alpine skiing. The significance of the included test results was examined using bivariate and multivariate data analysis.

Results: The results of Paper I show that included aerobic test results, neither alone nor in combination with anthropometric variables, could predict competitive performance of junior elite alpine skiers. Principal component analysis shows that male and female junior alpine skiers could be separated based on test results but that none of the included tests were important for sport-specific performance. The best multivariate models reached R2 = 0.51 to 0.86 and Q2 = -0.73 to 0.18. While several significant regression models could be observed, none of these met the criteria for valid models. The lack of predictive power of observed prediction models was confirmed by cross-validation. The results of Paper II show that included physiological test results from the test battery Fysprofilen could not predict competitive performance of senior elite female alpine skiers. Principal component analysis shows that there is a high correlation between individual physiological test results and their corresponding Fysprofilen score points, indicating that they can be used interchangeably. The Mann-Whitney U test was not significant neither for SL nor for GS. This suggests that Fysprofilen score points (summarized as Fysprofilen Index) and competitive performance (indicated by FIS points) are independent. The best multivariate models for SL and GS reached R2 = 0.27 to 0.43 and Q2 = - 0.8 to - 0.17, indicating low predictive power for competitive performance (as confirmed by cross-validation). The results of Paper III show that included physiological test results from a novel test battery could not predict competitive performance of senior elite female alpine skiers on a group level. When data were analyzed on a group level, the best models for SL and GS reached R2 = 0.39 to 0.40, Q2 = 0.15 to 0.21, indicating low predictive power. In contrast, when data were analyzed on an individual level, valid models with high predictive power (R2 = 0.88 to 0.99 and Q2 = 0.64 to 0.96) were generated. A comparative analysis between individual multivariate models shows that the relative importance of different physiological qualities for athletic performance varies between skiers.

Conclusion: When applying tests on alpine skiers, a holistic approach should be considered. This because competitive performance in alpine skiing is the result of a number of interacting dimensions. Before applying physiological tests, the validity and reliability of the test protocols must also be determined. Administering tests that do not meet these criteria will probably waste not only important resources for clubs and ski federations but also risk misleading coaches and athletes when planning and implementing preparatory training.

Place, publisher, year, edition, pages
Umeå: Umeå universitet , 2019. , p. 56
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 2038
Keywords [en]
Competitive performance, FIS points, alpine skiing, alpine skiers, physiological test results, anthropometric variables, multivariate data analysis, multivariate statistics, principal component analysis, orthogonal projections to latent structures, individual profiling
National Category
Sport and Fitness Sciences
Research subject
Sports Medicine
Identifiers
URN: urn:nbn:se:umu:diva-159216ISBN: 978-91-7855-079-1 (print)OAI: oai:DiVA.org:umu-159216DiVA, id: diva2:1317167
Public defence
2019-06-13, Aulan, Vårdvetarhuset, Umeå, 13:00 (Swedish)
Opponent
Supervisors
Available from: 2019-05-23 Created: 2019-05-22 Last updated: 2019-05-23Bibliographically approved
List of papers
1. Aerobic Variables for Prediction of Alpine Skiing Performance: A Novel Approach
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2018 (English)In: Sports Medicine International Open, ISSN 2367-1890, Vol. 2, no 4, p. E105-E112Article in journal (Refereed) Published
Abstract [en]

The aim of this study was to investigate the predictive power of aerobic test results and anthropometric variables on FIS-ranking of junior elite alpine skiers. Results from twenty-three male and female adolescent elite alpine skiers from two seasons were included in the multivariate statistical models. Physical work capacity was determined by V̇O2peak, blood lactate concentration ([HLa]b), and heart rate (HR) during ergometer cycling. Anthropometric variables were body stature, body weight and calculated BMI. No significant correlation between competitive performance and aerobic work capacity or anthropometric data was observed neither in male nor female adolescent skiers. Pre-season physical tests and anthropometric data could therefore not predict end-season FIS-ranking. The best regression (R2) and prediction (Q2) models of FIS slalom (SL) and giant slalom (GS) rank reached R2=0.51 to 0.86, Q2=−0.73 to 0.18, indicating no valid models. This study could not establish V̇O2peak and other included variables as predictors of competitive performance. When combining results from commonly used tests for alpine skiers, and applying multivariate statistical models, investigated tests seems of limited used for athletes, coaches, and ski federations. Performance-specific pre-season tests must be developed and validated for prediction of performance and guidance of exercise training.

Place, publisher, year, edition, pages
Georg Thieme Verlag KG, 2018
Keywords
exercise testing, athletic performance, FIS points, multivariate statistics, V̇O2max
National Category
Sport and Fitness Sciences
Research subject
Sports Medicine
Identifiers
urn:nbn:se:umu:diva-154284 (URN)10.1055/a-0655-7249 (DOI)30539126 (PubMedID)
Available from: 2018-12-14 Created: 2018-12-14 Last updated: 2019-05-22Bibliographically approved
2. Lack of Predictive Power in Commonly Used Tests for Performance in Alpine Skiing
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(English)Manuscript (preprint) (Other academic)
National Category
Sport and Fitness Sciences
Identifiers
urn:nbn:se:umu:diva-159212 (URN)
Available from: 2019-05-21 Created: 2019-05-21 Last updated: 2019-05-22
3. Individual Profiling for Prediction of Competitive Performance in Alpine Skiing
Open this publication in new window or tab >>Individual Profiling for Prediction of Competitive Performance in Alpine Skiing
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(English)Manuscript (preprint) (Other academic)
National Category
Sport and Fitness Sciences
Identifiers
urn:nbn:se:umu:diva-159215 (URN)
Available from: 2019-05-21 Created: 2019-05-21 Last updated: 2019-05-22

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