This project explores my personal gym progress through data tracking, focusing on trends in training frequency, work rate, and strength (1RM) over multiple years (2022–2026).
The analysis highlights how my training structure evolved over time, especially before and after a major gap in recorded data — using both Python (Jupyter Notebook) and Power BI for visualization.
- Data analysis of multi-year gym logs (2022–2026)
- Comparison of training frequency vs. work rate (intensity)
- Visualization of lift-specific progress (e.g., Bench Press, Lat Pulldown)
- Analysis of lagged relationship between training volume and strength (1RM)
- Integration of Power BI dashboards for interactive exploration and also design a custom muscle anatomy button through Sypnotic Design.
There is a significant gap between mid-2023 and late-2024, making trends during this period unreliable.
The gap varies across muscle groups, suggesting inconsistent tracking rather than a complete stop in training.
The most important shift occurs in early 2025:
- Training frequency nearly doubled (from ~1x/week to ~2x/week)
- Work rate per session remained relatively constant
This indicates that I was not training harder, but training more often, leading to an increase in total weekly volume.
Strength gains do not appear immediately after the frequency increase.
- There is a 3–5 month lag between increased frequency and noticeable 1RM improvement
- This pattern is especially clear in:
- Chest
- Biceps
- Hamstrings
This suggests that higher frequency (volume), not intensity per session, is the primary driver of strength gains over time.
Some muscle groups show less reliable trends:
- Shoulders and triceps → noisy 1RM due to exercise variability and estimation limits
- Lats → temporary drop likely due to detraining after the gap
- Calves → inflated values due to high-rep 1RM estimation issues
Overall, my data tells a consistent story:
After a break, I returned to training and increased frequency without increasing intensity.
Over several months, this higher training volume led to measurable strength gains, with a delayed but consistent response in 1RM.
Due to the missing data, it is difficult to fully determine whether frequency or work rate has a stronger causal relationship with 1RM.
However, for major muscle groups that I train consistently, the data suggests that strength gains correlate more strongly with increases in training frequency (volume) than with per-session work rate.
- Python (Pandas) for data cleaning and analysis
- Jupyter Notebook for exploration and documentation
- Power BI for dashboard visualization
- GitHub for version control and project sharing