2nd/10_Wiki/Topics/AI_and_ML/Elite-Sport-Science-Protocols.md

id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack

id	title	category	status	canonical_id	aliases	duplicate_of	source_trust_level	confidence_score	verification_status	tags	raw_sources	last_reinforced	github_commit	tech_stack
wiki-2026-0508-elite-sport-science-protocols	Elite Sport Science Protocols	10_Wiki/Topics	verified	self	sport science elite athlete periodization recovery monitoring GPS HRV	none	A	0.94	applied	sport-science elite-athlete periodization recovery monitoring training-load		2026-05-10	pending	language applicable_to Sport Science Performance Recovery Monitoring

Elite Sport Science Protocols

매 한 줄

"매 elite performance 의 systematic prepare + monitor + recover". 매 periodization (Bondarchuk, block), 매 monitoring (HRV, GPS, RPE), 매 recovery (sleep, nutrition, modality), 매 individualize (genotype, response). 매 modern: 매 wearable + ML.

매 핵심

매 pillar

1. Strength & conditioning (S&C).
2. Nutrition (peri-workout, micronutrient).
3. Recovery (sleep > active recovery > modality).
4. Skill / tactical.
5. Psychology (motivation, focus).
6. Monitoring (objective + subjective).
7. Periodization (macro, meso, micro).

매 monitoring metric

• External load: 매 GPS (TD, HSR, sprint).
• Internal load: 매 HR, RPE, HRV.
• Wellness: 매 sleep, soreness, mood.
• Performance test: 매 jump, sprint, repeat sprint.
• Biomarker: 매 CK, cortisol.

매 periodization

• Linear (Matveyev): 매 prep → comp → transition.
• Block (Issurin): 매 accumulation / transmutation / realization.
• Conjugate (Verkhoshansky): 매 multiple qualities.
• Tapering: 매 2-3 wk pre-comp.

매 recovery hierarchy (modern)

1. Sleep (8-10 h elite).
2. Nutrition + hydration.
3. Active recovery.
4. Modality (cold, compression — 매 evidence weak).

매 응용

1. Endurance: 매 lactate threshold.
2. Power: 매 PAP, complex training.
3. Team sport: 매 small-sided games.
4. Combat sport: 매 weight cut + recovery.
5. eSports / aim: 매 cognitive + visual.

💻 패턴

Acute:Chronic Workload Ratio (Gabbett)

def acwr(daily_loads, acute_days=7, chronic_days=28):
    if len(daily_loads) < chronic_days: return None
    acute = sum(daily_loads[-acute_days:]) / acute_days
    chronic = sum(daily_loads[-chronic_days:]) / chronic_days
    ratio = acute / chronic if chronic > 0 else 0
    risk = 'sweet_spot' if 0.8 <= ratio <= 1.3 else ('high_risk' if ratio > 1.5 else 'detrain')
    return {'ratio': ratio, 'risk': risk}

HRV-guided training

def hrv_decision(today_hrv, baseline_mean, baseline_sd):
    z = (today_hrv - baseline_mean) / baseline_sd
    if z < -1: return 'reduce_intensity_or_rest'
    elif z < 0: return 'maintain'
    elif z < 1: return 'normal'
    else: return 'opportunity_for_high_intensity'

Session RPE (Foster)

def session_rpe_load(rpe_0_10, duration_min):
    return rpe_0_10 * duration_min  # 매 AU (arbitrary units)

def weekly_monotony(daily_loads):
    return np.mean(daily_loads) / max(np.std(daily_loads), 1e-6)

def strain(weekly_load, monotony):
    return weekly_load * monotony  # 매 > 6000 = high illness risk

Bondarchuk periodization (block)

PERIODIZATION = {
    'accumulation': {'duration_wk': 4, 'volume': 'high', 'intensity': 'low-mod', 'focus': 'aerobic_capacity'},
    'transmutation': {'duration_wk': 3, 'volume': 'mod', 'intensity': 'high', 'focus': 'sport_specific'},
    'realization': {'duration_wk': 2, 'volume': 'low', 'intensity': 'peak', 'focus': 'competition'},
}

Sleep tracking

def sleep_quality(records):
    return {
        'duration_h': np.mean([r.duration for r in records]),
        'efficiency': np.mean([r.efficiency for r in records]),  # 매 time_asleep / time_in_bed
        'deep_sleep_pct': np.mean([r.deep / r.total for r in records]),
        'rem_pct': np.mean([r.rem / r.total for r in records]),
    }

GPS load (team sport)

def gps_metrics(trace):
    return {
        'total_distance_m': trace.distance,
        'high_speed_running_m': trace.distance_above(5.5),  # 매 m/s
        'sprints': sum(1 for s in trace.efforts if s.peak_speed > 7),
        'accelerations_high': sum(1 for a in trace.accels if a > 3),  # 매 m/s²
        'player_load_au': sqrt_sum_jerks(trace),
    }

Lactate threshold

def lactate_threshold(test_data):
    """매 LT2 = 매 4 mmol/L OR 매 inflection point."""
    speeds, lactates = zip(*test_data)
    for i, l in enumerate(lactates):
        if l >= 4.0: return speeds[i]
    return None

Tapering protocol

def taper_volume(days_to_comp, peak_volume):
    """매 2-week exponential taper."""
    if days_to_comp > 14: return peak_volume
    return peak_volume * 0.5 ** ((14 - days_to_comp) / 4)

Wellness questionnaire (5-pt)

def daily_wellness(sleep, soreness, fatigue, stress, mood):
    """매 1=worst, 5=best."""
    score = sleep + soreness + fatigue + stress + mood
    return {'score': score, 'flag_red': score < 12, 'flag_yellow': score < 17}

CK (creatine kinase) interpretation

def ck_load_classification(ck_iu_l, baseline=200):
    if ck_iu_l < baseline * 1.5: return 'normal'
    if ck_iu_l < baseline * 3: return 'elevated_typical'
    if ck_iu_l < baseline * 5: return 'high_recovery_priority'
    return 'very_high_consider_rest'

Heat acclimation

def heat_acclimation_protocol():
    """매 10-14 day protocol."""
    return {
        'days': 14,
        'duration_per_day_min': 60,
        'temperature_c': 35,
        'intensity': '50-65% VO2max',
        'expected_adaptations': ['plasma_volume_+12%', 'sweat_rate_+30%', 'core_temp_threshold_-0.4C'],
    }

Genotype-informed (e.g., ACTN3)

def actn3_recommendation(genotype):
    if genotype == 'RR': return 'power-leaning'
    if genotype == 'RX': return 'mixed'
    if genotype == 'XX': return 'endurance-leaning'

매 결정 기준

상황	Protocol
Endurance	Polarized 80/20 + LT
Power	Block + complex
Team sport	Tactical periodization + GPS
Combat	Weight cut + recovery
Pre-comp	Taper
Overreach risk	ACWR + HRV

기본값: 매 ACWR + HRV-guided + sleep priority + RPE log + periodization (block) + individual response.

🔗 Graph

• 부모: Sport-Science · Performance
• 변형: Periodization
• 응용: Strength-Conditioning · Elite-Sport-Science-Protocols
• Adjacent: Recovery · HRV

🤖 LLM 활용

언제: 매 elite athlete prep. 매 team sport S&C. 언제 X: 매 recreational unguided.

❌ 안티패턴

• No load monitor: 매 overtraining.
• Modality before basics: 매 ice bath > sleep is wrong.
• Same plan for all: 매 individual response.
• No taper: 매 peak miss.
• CK only as fatigue marker: 매 multi-marker 의 prefer.

🧪 검증 / 중복

• Verified (NSCA, ACSM, Bondarchuk, Issurin, Gabbett 2016).
• 신뢰도 A.

🕓 Changelog

날짜	변경
2026-04-20	Auto-reinforced
2026-05-08	Phase 1
2026-05-10	Manual cleanup — periodization + ACWR / HRV / GPS / sleep / taper code