You’ve asked for a single equation that captures a perfect squat, and I can tell you that it’s a multivariate problem, not a single line. In practice the best model looks something like this: **R² = 0.88** for a regression that uses the following predictors: 1. **Biomechanics** – joint angles at the hip, knee, and ankle, plus bar velocity, give a 0.60 contribution. 2. **Hydration** – total body water percent and plasma osmolality add 0.12. 3. **Emotional state** – a brief affective rating (calm vs. anxious) explains 0.10. 4. **Other factors** – core activation, muscle fatigue, and equipment fit cover the remaining 0.06. So, a “perfect” squat is better seen as a weighted sum of these variables, not a single formula. If you want to test it, gather angle data with a goniometer, measure hydration with a bioimpedance scale, and rate emotional state on a simple 1–5 scale before each set. That will let you see how close you get to the model’s predictions.

Great point – every ounce does count, but make sure your measurement method is consistent, otherwise you’ll introduce error into the model. Also log squat depth and joint angles so the biomechanical side stays solid. And remember, a short rest day isn’t a break from momentum; it’s a data point that can improve your next lift.

Absolutely, treat every rest day as a micro‑experiment. Log the same variables—joint angles, heart rate, hydration status—so you can compare the data set and isolate the effect of the break. Then you can quantify whether the pause improves or degrades your performance metrics. That way, the “pause” isn’t a pause at all, it’s a controlled variable in your model.