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Analysing expertise through data mining: an example based on treading water.

Christophe Schnitzler1, Chris Button, Ludovic Seifert

  • 1a LISEC, EA 2310, ESPÉ , Université de Strasbourg , Strasbourg , France.

Journal of Sports Sciences
|March 22, 2014
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Summary
This summary is machine-generated.

Researchers classified treading water techniques by analyzing forces and limb coordination. This study identified three distinct coordination patterns, offering a framework for analyzing sports expertise.

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Area of Science:

  • Biomechanics
  • Motor Control
  • Sports Science

Background:

  • Treading water is a fundamental aquatic skill requiring complex coordination.
  • Existing classifications of treading water lack empirical validation.
  • Understanding coordination patterns can differentiate skill levels.

Purpose of the Study:

  • To establish and empirically verify a conceptual typology for treading water.
  • To identify distinct inter-limb coordination patterns used in treading water.
  • To explore the relationship between coordination patterns and treading water expertise.

Main Methods:

  • A conceptual typology was developed based on force generation and inter-limb coordination.
  • Thirty-eight participants were videotaped while treading water.
  • Multivariate statistics and support vector machine analysis were employed.

Main Results:

  • Three distinct groups of coordination patterns were identified.
  • The data mining process provided a methodological framework for analyzing sports expertise.
  • A taxonomy of coordination solutions for stabilizing forces in water was suggested.

Conclusions:

  • A valid classification system for treading water techniques can be established.
  • Distinct coordination patterns exist in treading water, related to expertise.
  • The methodology offers a framework for analyzing expertise in various sports activities.