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TRACK30 PUBLIC METHODOLOGY

TRACK30 Calorie Budget, Lifestyle & Exercise Methodology

Engine V2.1.0 • September 2026

How TRACK30 uses body composition, resting-energy equations, lifestyle activity, planned exercise, workout history, goal intensity, and protein needs to calculate a personalized Calorie Budget and related program metrics.
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Important scope1. Scientific foundation2. Engine philosophy — Personalization with conservatism3. Inputs4. Body composition5. Protein goal6. Resting energy estimates7. TRACK30 blended BMR8. Lifestyle activity9. Planned exercise10. Historical workout credit11. Maintenance estimates12. Goal multipliers13. Issued calories and 50-kcal adherence buffer14. Dynamic energy balance and metabolic adaptation15. 30-day projections16. Consecutive-participant rollover17. Limitations18. Scientific references

Important scope

TRACK30 Engine V2.1.0 is a fitness-program estimation methodology, not medical diagnosis or treatment. It estimates a Calorie Budget, Protein Goal, maintenance energy needs, and related program metrics from participant-provided information and predictive equations; it does not directly measure an individual's metabolism or guarantee a specific result.

1. Scientific foundation

Changes in body energy stores are governed by the relationship between energy intake and energy expenditure. For fat-loss goals, a sustained energy deficit is therefore foundational. However, total energy expenditure is dynamic: body size changes, food intake changes, activity can change, and adaptive thermogenesis may occur during weight loss. TRACK30 therefore uses estimates and ranges rather than treating a static calorie calculation as a guaranteed outcome.

Resting-energy prediction equations are useful but imperfect at the individual level. Mifflin-St Jeor has performed well in validation studies, but prediction error remains meaningful. TRACK30's blended method is a program-design response to uncertainty; it is not itself a universally validated clinical equation.

2. Engine philosophy — Personalization with conservatism

A target should reflect meaningful differences among participants without allowing optimistic assumptions to inflate the Calorie Budget. TRACK30 separates ordinary lifestyle activity from planned exercise and distinguishes established workout behavior from newly promised workout behavior.

3. Inputs

  • Body weight
  • Body-fat percentage
  • Height
  • Age
  • Sex used in the BMR equation
  • Body-composition measurement source
  • Daily lifestyle activity
  • Exercise type/intensity/duration
  • Historical workout frequency
  • Challenge workout commitment
  • Goal and goal intensity

4. Body composition

Fat Mass (lb) = Body Weight × Body-Fat Percentage

Lean Body Mass (lb) = Body Weight − Fat Mass

5. Protein goal

Protein Goal = 1.2 grams × Lean Body Mass in pounds.

The 1.2 g/lb lean-mass value is TRACK30's program prescription, not a universal medical requirement. Higher protein intakes than the basic RDA can be useful for lean-mass retention under energy restriction and training stress, but appropriate intake varies by person and context.

6. Resting energy estimates

Katch-McArdle: BMR = 370 + (21.6 × Lean Body Mass in kg).

Mifflin-St Jeor — Male: BMR = (10 × weight kg) + (6.25 × height cm) − (5 × age) + 5.

Mifflin-St Jeor — Female: BMR = (10 × weight kg) + (6.25 × height cm) − (5 × age) − 161.

7. TRACK30 blended BMR

SourceKatch weightMifflin weight
DEXA85%15%
InBody65%35%
Home Smart Scale45%55%

Blended BMR = (Katch BMR × Katch weight) + (Mifflin BMR × Mifflin weight).

The weighting is a TRACK30 design choice intended to give lean-mass-based estimation more influence when the body-composition source is treated as more controlled, while reducing reliance on a potentially noisy body-fat estimate from consumer devices.

TRACK30 displays DEXA, InBody, and Home Smart Scale as its program source categories. A participant whose available clinic-style device is Evolt may select InBody; TRACK30 treats Evolt and InBody as the same program category for this purpose.

8. Lifestyle activity

Daily activityMultiplier
Sedentary1.00
Lightly Active1.10
Moderate1.20
Very Active1.30

Lifestyle Calories = Blended BMR × Lifestyle Activity Multiplier.

9. Planned exercise

Net Exercise Calories per Workout = (MET − 1) × Body Weight in kg × Workout Duration in Hours. Subtracting 1 MET is intended to avoid double-counting the resting component already represented in the BMR/lifestyle calculation.

10. Historical workout credit

Calculation Workout Days = MIN(Committed Workout Days, Historical Workout Days + 2).

This allows a new commitment to influence the estimate without immediately assuming that a large increase in training frequency is already established.

11. Maintenance estimates

Conservative Exercise Calories per Day = (Net Exercise Calories per Workout × Calculation Workout Days) ÷ 7.

Maintenance Calories = Lifestyle Calories + Conservative Exercise Calories per Day.

Projected Maintenance uses all committed workout days and is used as a separate projection scenario rather than the primary Calorie Budget.

12. Goal multipliers

GoalMild/LeanModerateAggressive
Maintenance1.001.001.00
Fat Loss0.850.800.75
Bulk1.051.101.15

Calculated Calories = Maintenance Calories × Goal Multiplier.

13. Issued calories and 50-kcal adherence buffer

Issued Calorie Budget = Calculated Calories + 50 kcal.

The buffer is a TRACK30 behavioral-design feature. Because the challenge penalizes exceeding the issued ceiling, participants may otherwise intentionally undershoot the calculated amount to create a safety margin. The buffer is intended to reduce that systematic undershooting; it is not described as 'bonus calories.'

14. Dynamic energy balance and metabolic adaptation

TRACK30 does not assume maintenance expenditure stays perfectly fixed throughout a diet. During negative energy balance and weight loss, expenditure can decline from changes in body mass and composition, lower thermic effect of food, changes in non-exercise activity, and adaptive thermogenesis. A systematic review found adaptive thermogenesis in many studies but also substantial heterogeneity and smaller or nonsignificant effects in some higher-quality designs. This supports treating adaptation as real and variable—not as a universal 'metabolic crash.'

For verification, the relevant question is therefore whether an observed result is reasonably consistent with documented behavior and a plausible physiological response, not whether the participant hit an exact static 3,500-kcal arithmetic prediction.

15. 30-day projections

Current engine projection: Projected Change = (Daily Calorie Difference × 30) ÷ 3,500.

This is a communication estimate, not a promise. The static 3,500-kcal conversion does not fully model dynamic expenditure or short-term scale-weight variability. Water, glycogen, sodium, digestion, menstrual-cycle effects, medication, adherence error, body-composition error, and metabolic adaptation can all affect observed results.

16. Consecutive-participant rollover

  • If the newly calculated Calorie Budget is lower than the prior issued Calorie Budget, the lower recalculated value is issued.
  • If the recalculated Calorie Budget is not lower, the previous Calorie Budget is retained.
  • The previous Protein Goal is retained under current rollover logic.
  • Projections are recalculated using the calorie amount actually issued.

17. Limitations

Engine V2.1.0 does not directly measure resting metabolic rate, true total daily energy expenditure, exact exercise expenditure, metabolic adaptation, hormone status, nutrient absorption, or every factor affecting body weight. Body-fat measurements, MET estimates, food labels, and self-reported behavior also contain error.

18. Scientific references

  • Nunes CL, et al. Does adaptive thermogenesis occur after weight loss in adults? A systematic review. Br J Nutr. 2022. PMID: 33762040.
  • Frankenfield D, et al. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc. 2005. PMID: 15883556.
  • Frankenfield DC. Bias and accuracy of resting metabolic rate equations in non-obese and obese adults. Clin Nutr. 2013. PMID: 23631843.
  • Müller MJ, et al. Adaptive thermogenesis with weight loss in humans. Obesity. 2013. PMID: 23404923.
  • Hudson JL, et al. Protein Intake Greater than the RDA Differentially Influences Whole-Body Lean Mass Responses to Purposeful Catabolic and Anabolic Stressors: A Systematic Review and Meta-analysis. Adv Nutr. 2020. PMID: 31794597.
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