ATHLETICA | Science & Methodology

Nutrition Science

FORMULAS &
CITATIONS

Every number shown on the Nutrition tab is computed from these formulas. None of it is generated by AI.

Calorie Target

TDEE & DAILY CALORIE GOAL

Your daily calorie target is computed from your Basal Metabolic Rate (BMR) — the energy your body needs at rest — scaled by an activity multiplier derived from your actual training schedule, then adjusted for your goal.

Formulas Used

BMR — MaleBMR = 88.362 + (13.397 × weight_kg) + (4.799 × height_cm) − (5.677 × age)

BMR — FemaleBMR = 447.593 + (9.247 × weight_kg) + (3.098 × height_cm) − (4.330 × age)

TDEETDEE = BMR × Activity Multiplier

< 90 min/wkMultiplier = 1.375 (lightly active)

< 180 min/wkMultiplier = 1.550 (moderately active)

< 300 min/wkMultiplier = 1.725 (very active)

≥ 300 min/wkMultiplier = 1.900 (extremely active)

CutTarget = TDEE − 500 kcal/day → ~0.5 kg/week fat loss

BulkTarget = TDEE + 300 kcal/day

MaintainTarget = TDEE

Safety range1,200 – 4,500 kcal/day

Harris & Benedict (1918); Mifflin et al. (1990)

A Biometric Study of Human Basal Metabolism / A new predictive equation for resting energy expenditure

PNAS · American Journal of Clinical Nutrition, 51(2)

doi.org/10.1093/ajcn/51.2.241 ↗

Hall et al. (2011)

Quantification of the effect of energy imbalance on bodyweight

The Lancet, 378(9793)

doi.org/10.1016/S0140-6736(11)60812-X ↗

ACSM Guidelines for Exercise Testing and Prescription, 11th Ed. (2022)

Activity multiplier classifications for TDEE

American College of Sports Medicine

acsm.org ↗

Protein

PROTEIN TARGET

Protein is calculated from lean body mass at 2.2g per kg — at the upper end of the evidence-based range, appropriate for individuals in a caloric deficit engaged in resistance training.

Formula Used

Lean massLean mass (kg) = weight_kg × (1 − body_fat_pct ÷ 100)

Default bf%15% male / 22% female (if no body scan)

ProteinProtein (g) = lean mass × 2.2

Safety range120 – 250 g/day

Helms et al. (2014)

Dietary protein during caloric restriction in resistance trained lean athletes

International Journal of Sport Nutrition and Exercise Metabolism, 24(2)

doi.org/10.1123/ijsnem.2013-0054 ↗

EFSA Panel on Dietetic Products (2012)

Scientific Opinion on Dietary Reference Values for protein

EFSA Journal, 10(2)

doi.org/10.2903/j.efsa.2012.2557 ↗

Fat

FAT TARGET

Fat is set at 25% of total daily calorie target — within the 20–35% range recommended for active adults by ACSM and USDA.

Formula Used

FatFat (g) = (Target kcal × 0.25) ÷ 9

Atwater factorFat = 9 kcal/g

Safety range40 – 100 g/day

Thomas et al. (2016) — ACSM/AND/DC Joint Position Statement

Nutrition and Athletic Performance

Medicine & Science in Sports & Exercise, 48(3)

doi.org/10.1249/MSS.0000000000000852 ↗

Carbohydrates

CARBOHYDRATE TARGET

Carbohydrates fill the remaining calories after protein and fat are allocated. This prioritises protein and fat targets while keeping carbs flexible and aligned to energy needs.

Formula Used

CarbsCarbs (g) = (Target kcal − Protein kcal − Fat kcal) ÷ 4

Protein kcalProtein (g) × 4

Fat kcalFat (g) × 9

Atwater factorsProtein = 4 kcal/g · Fat = 9 kcal/g · Carbs = 4 kcal/g

Safety range50 – 400 g/day

USDA Dietary Guidelines for Americans 2020–2025

Recommends 45–65% of calories from carbohydrate for healthy adults

U.S. Department of Agriculture & U.S. Dept. of Health and Human Services

dietaryguidelines.gov ↗

Safety Rule

48-HOUR MUSCLE RECOVERY LOCK

No muscle group trained in the previous 48 hours is assigned as a primary mover. Enforced in code before the AI is called — cannot be overridden by any instruction or conversation.

Rule Logic

BLOCKED ifhours_since_last_session < 48 OR muscle ∈ lastMusclesHit

ELIGIBLE ifhours_since_last_session ≥ 48 AND muscle ∉ lastMusclesHit

Phillips & Van Loon (2011)

Dietary protein for athletes: From requirements to optimum adaptation

Journal of Sports Sciences, 29(S1)

doi.org/10.1080/02640414.2011.619204 ↗

Progression Rule

RPE-DRIVEN PROGRESSIVE OVERLOAD

After every session, the student rates their exertion (RPE 1–10). The engine computes the next load target from this — not the AI. The AI receives it as a directive it cannot deviate from.

Load Targets by RPE

RPE ≤ 6.0Next load = last load × 1.05 [or +3 reps if bodyweight]

RPE ≤ 7.5Next load = last load + 2.5 kg [or +1 rep if bodyweight]

RPE ≤ 8.5Next load = last load, reps + 1

RPE > 8.5Next load = last load, reps unchanged [consolidate]

1RM estimate1RM ≈ load × (1 + reps ÷ 30) (Epley formula)

Zourdos et al. (2016)

Novel Resistance Training–Specific RPE Scale Measuring Repetitions in Reserve

Journal of Strength and Conditioning Research, 30(1)

doi.org/10.1519/JSC.0000000000001049 ↗

Fatigue Rule

FATIGUE SCORE & AUTOMATIC DELOAD

Systemic fatigue accumulates from session RPE, volume and density. When it exceeds a threshold, a deload is automatically mandated — 40% volume reduction, no load increase. The AI cannot cancel it.

Fatigue & Deload Logic

AccumulationfatigueScore += session_RPE × volume_factor × density_factor

RangefatigueScore clamped to 1.0 – 10.0

IntermediateDeload mandated if fatigueScore > 7.5

AdvancedDeload mandated if fatigueScore > 8.0

Deload volumenormal volume × 0.60 (40% reduction)

Meeusen et al. (2013) — ECSS/ACSM Joint Consensus Statement

Prevention, diagnosis and treatment of the overtraining syndrome

European Journal of Sport Science, 13(1)

doi.org/10.1080/17461391.2012.730061 ↗

Volume Rule

WEEKLY VOLUME — MEV & MAV

Athletica tracks weekly sets per muscle group and enforces a floor (Minimum Effective Volume) and a ceiling (Maximum Adaptive Volume). Below MEV the muscle is under-stimulated. Above MAV the body cannot adapt positively — additional volume becomes junk volume that increases injury risk.

Volume Tracking & Enforcement

AccumulationweeklyMuscleSets[muscle] += sets_assigned_this_session

Below MEVMuscle flagged as priority → engine increases assignment

MEV ≤ sets ≤ MAVNormal zone — standard assignment

Above MAVMuscle blocked from additional sets this week

Major musclesMEV ≈ 6–10 sets/wk · MAV ≈ 16–22 sets/wk

Minor musclesMEV ≈ 4–6 sets/wk · MAV ≈ 12–16 sets/wk

ResetweeklyMuscleSets = 0 at start of each training week

Schoenfeld et al. (2017)

Dose-response relationship between weekly resistance training volume and increases in muscle mass

Journal of Strength and Conditioning Research, 31(12)

doi.org/10.1519/JSC.0000000000002200 ↗

Israetel et al. (2019) — Renaissance Periodization

Scientific Principles of Strength Training — MEV / MAV / MRV framework

Renaissance Periodization

rpstrength.com ↗

Structure Rule

SPLIT ROTATION

Today's target muscles are determined by a structured training split that rotates automatically after each session. The split is assigned by the engine — the AI receives it as a directive and cannot reorder or skip days.

Split Assignment Logic

Day indexsplitDayIndex = (splitDayIndex + 1) mod split.length after each session

3 days/wkFull Body × 3

3–4 days/wkUpper / Lower

4 days/wkPush / Pull / Legs / Core

Fat loss goalFat Loss Circuit — metabolic conditioning format

Mobility goalMobility Flow — low intensity, controlled movement

AI receives"Today is a Push day" — as unbreakable directive

Schoenfeld et al. (2015)

Influence of Resistance Training Frequency on Muscular Adaptations in Well-Trained Men

Journal of Strength and Conditioning Research, 29(7)

doi.org/10.1519/JSC.0000000000000970 ↗

Periodisation Rule

8-WEEK PERIODISATION BLUEPRINT

A complete 8-week macro training plan is generated at program start and stored as a structured blueprint. Each week has a defined block type, volume percentage, intensity percentage and priority muscles. The engine reads this blueprint every session and injects the current week's directives. The AI cannot jump weeks, skip deload weeks or operate outside the current block type.

Blueprint Structure per Week

Week blueprint{ block_type, volume_pct, intensity_pct, priority_muscles, coach_note }

Block sequenceFoundation → Hypertrophy → Strength → Power → Deload

Foundationvolume_pct = 60% · intensity_pct = 55%

Hypertrophyvolume_pct = 85% · intensity_pct = 70%

Strengthvolume_pct = 75% · intensity_pct = 85%

Powervolume_pct = 65% · intensity_pct = 95%

Deloadvolume_pct = 40% · intensity_pct = 60% · no load increase

Sets this sessionmax_sets = base_sets × (volume_pct ÷ 100)

Rhea & Alderman (2004)

A meta-analysis of periodized versus nonperiodized strength and power training programs

Research Quarterly for Exercise and Sport, 75(4)

doi.org/10.1080/02701367.2004.10609174 ↗

ACSM Position Stand (2009)

Progression Models in Resistance Training for Healthy Adults

Medicine & Science in Sports & Exercise, 41(3)

doi.org/10.1249/MSS.0b013e3181915670 ↗

Onboarding Rule

GOAL FEASIBILITY ENGINE

When a student declares a weight-loss goal, Athletica runs a pure mathematical assessment of what is achievable with their stated plan and presents three honest options. This is computed deterministically — not generated by AI. The student sees the maths, not just the answer.

Feasibility Computation

Weekly lossweekly_fat_loss_kg = (daily_deficit × 7) ÷ 7,700

Weeks to goalweeks_to_goal = fat_to_lose_kg ÷ weekly_fat_loss_kg

Option ASolve for sessions/week needed to hit goal in target weeks

Option BProject actual result with current plan and timeline

Option CSolve for weeks needed at current commitment level

Energy density7,700 kcal/kg adipose tissue (EFSA reference value)

Hall (2008)

What is the Required Energy Deficit per unit Weight Loss?

International Journal of Obesity, 32(3)

doi.org/10.1038/sj.ijo.0803720 ↗

Jensen et al. (2013) — AHA/ACC/TOS Clinical Guideline

Guideline for the Management of Overweight and Obesity in Adults

Circulation, 129(25 Suppl 2) · Establishes 0.5–1.0 kg/week as safe and sustainable

doi.org/10.1161/01.cir.0000437739.71477.ee ↗

Session Metric

CALORIE EXPENDITURE ESTIMATION

Session calorie burn is estimated from exercise-specific MET-derived coefficients scaled to the student's actual body weight. Each exercise in the library carries three coefficients computed at creation time. These are estimates — individual metabolic rates vary.

Per-Exercise Calorie Estimation

Rep-basedkcal = caloriesPerRep × reps_completed × (bodyweight_kg ÷ 75)

Timedkcal = caloriesPerSecond × duration_s × (bodyweight_kg ÷ 75)

Distancekcal = caloriesPerMetre × distance_m × (bodyweight_kg ÷ 75)

Session totalsession_kcal = Σ (kcal per exercise across all sets)

Reference body75 kg (WHO/EFSA standard reference)

Ainsworth et al. (2011)

Compendium of Physical Activities: a second update of codes and MET values

Medicine & Science in Sports & Exercise, 43(8) · The standard reference for exercise energy expenditure

doi.org/10.1249/MSS.0b013e31821ece12 ↗

Daily Adaptation

READINESS ASSESSMENT

Before each session, students report sleep quality, soreness and energy on a 1–5 scale. These are assembled into a ReadinessSnapshot that influences session intensity. Subjective readiness metrics are validated by the literature as reliable training load management tools — this is how Athletica adapts to the student's actual day, not just their program week.

Readiness Computation

Inputssleep (1–5) · soreness (1–5) · energy (1–5)

Averagereadiness_avg = (sleep + soreness + energy) ÷ 3

avg ≥ 4.0High readiness → standard or increased session volume

3.0 ≤ avg < 4.0Moderate readiness → standard session

avg < 3.0Low readiness → volume reduced · AI notified via SessionConstraints

DefaultModerate assumed if readiness not reported

Saw et al. (2016)

Subjective measures of recovery and well-being: a meta-analysis of criterion validity

British Journal of Sports Medicine, 51(3) · Validates subjective well-being as a reliable readiness marker

doi.org/10.1136/bjsports-2015-094758 ↗

COMPLETE REFERENCE LIST

All citations alphabetically. Click any link to access the source.

ACSM (2022). Guidelines for Exercise Testing and Prescription, 11th Ed. acsm.org ↗

Ainsworth et al. (2011). Compendium of Physical Activities: a second update. Med Sci Sports Exerc, 43(8). doi.org ↗

EFSA (2012). Scientific Opinion on Dietary Reference Values for protein. EFSA Journal, 10(2). doi.org ↗

Hall et al. (2011). Quantification of the effect of energy imbalance on bodyweight. The Lancet, 378(9793). doi.org ↗

Harris & Benedict (1918); Mifflin et al. (1990). Harris-Benedict BMR / New predictive equation for resting energy expenditure. PNAS; AJCN 51(2). doi.org ↗

Helms et al. (2014). Dietary protein during caloric restriction in resistance trained lean athletes. IJSNEM, 24(2). doi.org ↗

Jensen et al. (2013). AHA/ACC/TOS Guideline for the Management of Overweight and Obesity. Circulation, 129(25 Suppl 2). doi.org ↗

Meeusen et al. (2013). Prevention, diagnosis and treatment of the overtraining syndrome (ECSS/ACSM). Eur J Sport Sci, 13(1). doi.org ↗

Phillips & Van Loon (2011). Dietary protein for athletes: From requirements to optimum adaptation. J Sports Sci, 29(S1). doi.org ↗

10.

Schoenfeld et al. (2017). Dose-response between weekly resistance training volume and muscle mass. J Strength Cond Res, 31(12). doi.org ↗

11.

Thomas et al. (2016). ACSM/AND/DC Joint Position Statement: Nutrition and Athletic Performance. Med Sci Sports Exerc, 48(3). doi.org ↗

12.

USDA (2020). Dietary Guidelines for Americans 2020–2025. dietaryguidelines.gov ↗

13.

Rhea & Alderman (2004). A meta-analysis of periodized versus nonperiodized strength and power training programs. Res Q Exerc Sport, 75(4). doi.org ↗

14.

Saw et al. (2016). Subjective measures of recovery and well-being: a meta-analysis of criterion validity. Br J Sports Med, 51(3). doi.org ↗

15.

Schoenfeld et al. (2015). Influence of Resistance Training Frequency on Muscular Adaptations in Well-Trained Men. J Strength Cond Res, 29(7). doi.org ↗

16.

Schoenfeld et al. (2017). Dose-response between weekly resistance training volume and muscle mass. J Strength Cond Res, 31(12). doi.org ↗

17.

Zourdos et al. (2016). Novel Resistance Training–Specific RPE Scale Measuring Repetitions in Reserve. J Strength Cond Res, 30(1). doi.org ↗

THE SCIENCE
BEHIND ATHLETICA

THE ATHLETICA
BRAIN

FREEDOM INSIDE AN
UNBREAKABLE CAGE.

FORMULAS &
CITATIONS

TDEE & DAILY CALORIE GOAL

PROTEIN TARGET

FAT TARGET

CARBOHYDRATE TARGET

ENGINE RULES &
SPORT SCIENCE

48-HOUR MUSCLE RECOVERY LOCK

RPE-DRIVEN PROGRESSIVE OVERLOAD

FATIGUE SCORE & AUTOMATIC DELOAD

WEEKLY VOLUME — MEV & MAV

SPLIT ROTATION

8-WEEK PERIODISATION BLUEPRINT

GOAL FEASIBILITY ENGINE

CALORIE EXPENDITURE ESTIMATION

READINESS ASSESSMENT

COMPLETE REFERENCE LIST

THE SCIENCEBEHIND ATHLETICA

THE ATHLETICABRAIN

FREEDOM INSIDE ANUNBREAKABLE CAGE.

FORMULAS &CITATIONS

TDEE & DAILY CALORIE GOAL

PROTEIN TARGET

FAT TARGET

CARBOHYDRATE TARGET

ENGINE RULES &SPORT SCIENCE

48-HOUR MUSCLE RECOVERY LOCK

RPE-DRIVEN PROGRESSIVE OVERLOAD

FATIGUE SCORE & AUTOMATIC DELOAD

WEEKLY VOLUME — MEV & MAV

SPLIT ROTATION

8-WEEK PERIODISATION BLUEPRINT

GOAL FEASIBILITY ENGINE

CALORIE EXPENDITURE ESTIMATION

READINESS ASSESSMENT

COMPLETE REFERENCE LIST

THE SCIENCE
BEHIND ATHLETICA

THE ATHLETICA
BRAIN

FREEDOM INSIDE AN
UNBREAKABLE CAGE.

FORMULAS &
CITATIONS

ENGINE RULES &
SPORT SCIENCE