Streamlining performance prediction: data-driven KPIs in all swimming strokes.

ABSTRACT:

Objective

This study aimed to identify Key Performance Indicators (KPIs) for men's swimming strokes using Principal Component Analysis (PCA) and Multiple Regression Analysis to enhance training strategies and performance optimization. The analyses included all men's individual 100 m races of the 2019 European Short-Course Swimming Championships.

Results

Duration from 5 m prior to wall contact (In5) emerged as a consistent KPI for all strokes. Free Swimming Speed (FSS) was identified as a KPI for 'continuous' strokes (Breaststroke and Butterfly), while duration from wall contact to 10 m after (Out10) was a crucial KPI for strokes with touch turns (Breaststroke and Butterfly). The regression model accurately predicted swim times, demonstrating strong agreement with actual perf

SUBMITTER: Staunton CA 

PROVIDER: S-EPMC10877752 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature