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Predicting a Successful Attempt in Raw Powerlifting. A Nonlinear Mixed Logistic Regression Analysis.

Ian A J Darragh1, Brendan Egan2,3, David Nolan2

  • 1School of Population Health, RCSI University of Medicine and Health Sciences Dublin, Ireland.

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Optimizing jump size in raw powerlifting is key for success. Moderate weight jumps benefit male squat and deadlift attempts, while smaller jumps are crucial for female lifters across all lifts.

Keywords:
competition performancelift successperformance predictionstrength trainingweight selection

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Area of Science:

  • Sports Science
  • Biomechanics
  • Strength and Conditioning

Background:

  • Raw powerlifting involves strategic weight progression between attempts.
  • Understanding factors influencing lift success is crucial for athlete performance.
  • Jump size, the difference between consecutive attempts, is a key variable.

Purpose of the Study:

  • To predict successful raw powerlifting attempts.
  • To analyze the influence of jump size on success rates.
  • To develop sex-specific models for attempt prediction.

Main Methods:

  • Nonlinear mixed logistic regression analysis.
  • Utilized data from 93,333 lifters across 6,979 competitions.
  • Developed sex-specific models with nonlinear splines and random lifter effects.

Main Results:

  • Jump size significantly impacts success rates, varying by lift, attempt, and sex.
  • Optimal jump sizes differ for male and female lifters across squat, bench press, and deadlift.
  • Third attempts consistently show lower success rates than second attempts.

Conclusions:

  • Jump size is a critical, nuanced factor in raw powerlifting attempt success.
  • Findings offer actionable insights for optimizing competition strategy and attempt selection.
  • Coaches and lifters can leverage these results to balance risk and reward.