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

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.