Statistical modeling portfolio project

Powerlifting Performance Regression Analysis

A reproducible R and Quarto analysis of World University Powerlifting Cup results, modeling how bodyweight, sex, age, and home-country advantage relate to squat, bench press, and deadlift performance.

Project Snapshot

This project analyzes 1,154 lifter results from World University Powerlifting Cup competitions between 2017 and 2025, excluding 2020. The work compares parsimonious generalized least squares models for best squat, bench press, and deadlift outcomes.

1,154 competition results analyzed
3 strength outcomes modeled
8 competition years studied

Research Question

What is the most parsimonious combination of predictors, including bodyweight, sex, age, and home-country advantage, that predicts a lifter's best squat, bench press, and deadlift performance?

Key Findings

Squat

Best squat performance was best described by additive effects for bodyweight, sex, age, and home-country status.

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Bench Press

The most parsimonious bench model included a sex-by-bodyweight interaction, suggesting different strength scaling patterns.

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Deadlift

Best deadlift performance followed the same core additive predictor set used for squat performance.

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Methods And Tools

The analysis uses OpenPowerlifting data, exploratory visualization, model comparison, and generalized least squares regression to account for variance patterns across lifter sex.

Project Files

Final Report

Complete methodology, exploratory analysis, model selection, and conclusions.

Open report.pdf