AI Article Synopsis

  • The study investigates the physical qualities that influence the ability to repeatedly perform maximal ballistic efforts, specifically through the repeat power ability (RPA) assessment involving loaded countermovement jumps.
  • Ten trained male field hockey players participated in multiple tests, including speed and strength assessments, to analyze the relationships between these physical qualities and the RPA performance.
  • Results show a strong correlation between repeated speed ability (RSA) and RPA, with RSA being the primary predictor of performance, suggesting RSA training may enhance repeated power output in athletes.

Article Abstract

Background: The repeat power ability (RPA) assessment is used to test the ability to repeatedly produce maximal ballistic efforts with an external load. The underpinning physical qualities influencing RPA are undetermined. This study aimed to gain further insight into the physical qualities that determine RPA by analysing the association between physical qualities and an assessment of RPA.

Materials And Methods: Ten well-trained male field hockey players performed an RPA assessment consisting of 20 repetitions of loaded countermovement jumps (LCMJ20), with a percent decrement score of peak power output calculated. Over a two-week period, each participant performed the YoYo Intermittent Recovery Test 2 (IRT2), a repeated speed ability assessment incorporating a 180° change of direction (RSA), a 40-meter linear speed test (40 mST), an isometric mid-thigh pull (IMTP), a countermovement jump (CMJ), and a 3-repetition maximum half squat (HS) assessment. Pearson's correlation analysis was used to determine the strength of relationships between each assessment variable and the LCMJ20. The assessment variables with the strongest relationships within each assessment were used in a stepwise multiple linear regression analysis to determine the best predictor model of LCMJ20.

Results: RSApercent decrement score (RSA% had a very strong, significant relationship with LCMJ20 ( = 0.736:  < 0.05). HS relative strength (HSrel) was found to have a significant and very strong, negative relationship with LCMJ20 ( =  - 0.728:  < 0.05). Stepwise multiple linear regression analysis showed RSA180 to explain 48.4% of LCMJ20 variance (Adjusted = 0.484) as the only covariate included in the model.

Conclusion: The findings indicate that RSA as a repeated high intensity effort (RHIE) task is strongly related to LCMJ20 and is also the best predictor of LCMJ20. This may suggest that RPA can provide practitioners with information on RHIE performance. The variance between assessment methods indicates that RPA may be a distinct physical quality, future research should assess other physical capacities to better understand the factors contributing to RPA.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10812577PMC
http://dx.doi.org/10.7717/peerj.16788DOI Listing

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