[G1-Sync] Manual knowledge update

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id: wiki-2026-0508-elite-sport-science-protocols
title: Elite Sport Science Protocols
category: 10_Wiki/Topics
status: needs_review
status: verified
canonical_id: self
aliases: [P-Reinforce-AI-SPORT-SCIENCE]
aliases: [sport science, elite athlete, periodization, recovery, monitoring, GPS, HRV]
duplicate_of: none
source_trust_level: A
confidence_score: 0.97
tags: [SportsScience, Performance, Physiology, Biofeedback]
confidence_score: 0.94
verification_status: applied
tags: [sport-science, elite-athlete, periodization, recovery, monitoring, training-load]
raw_sources: []
last_reinforced: 2026-04-20
last_reinforced: 2026-05-10
github_commit: pending
inferred_by: Claude Opus 4.7 (auto-normalize 2026-05-08)
tech_stack:
language: Sport Science
applicable_to: [Performance, Recovery, Monitoring]
---
# [[Elite-Sport-Science-Protocols|Elite-Sport-Science-Protocols]] (엘리트 스포츠 과학 프로토콜)
# Elite Sport Science Protocols
## 📌 한 줄 통찰 (The Karpathy Summary)
> "0.01초의 승리를 위해 신체를 공학적으로 정밀 튜닝하는 매뉴얼." 단순한 훈련을 넘어 생체 데이터, 영양, 심리, 회복 기술을 통합하여 선수의 퍼포먼스를 극한까지 끌어올리는 체계적인 절차다.
## 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.
## 📖 구조화된 지식 (Synthesized Content)
- **Load Monitoring**: GPS와 가속도계를 통해 선수의 훈련 부하를 실시간 측정하여 부상 위험 점수 산출.
- **Recovery [[Protocols|Protocols]]**:
- **Cryotherapy**: 염증 억제 및 회복 촉진.
- **Sleep [[Optimization|Optimization]]**: 렘수면 단계 분석을 통한 인지 기능 및 근육 회복 관리.
- **Nutritional Timing**: 에너지 대사 주기를 고려한 영양소 섭취(Periodized Nutrition).
- **Biomechanical [[Analysis|Analysis]]**: 3D 모션 캡처를 통한 동작 최적화 및 파워 출력 분석.
## 매 핵심
## ⚠️ 모순 및 업데이트 (Contradictions & Updates)
- 'Over-training' 만큼 위험한 것이 'Over-monitoring'이다. 과도한 데이터 수집이 선수의 심리적 압박으로 작용하여 오히려 경기력을 저하시키는 경우가 발견되고 있다. 따라서 수치(Data)와 선수의 주관적 피로도(RPE) 사이의 균형을 맞추는 것이 현대 스포츠 과학의 핵심 트렌드다.
### 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).
## 🔗 지식 연결 (Graph)
- Related: Exercise-Physiology , Biofeedback-Training
- Field: Kinesiology-Foundations
### 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.
## 🤖 LLM 활용 힌트 (How to Use This Knowledge)
### 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.
**언제 이 지식을 쓰는가:**
- *(TODO)*
### 매 recovery hierarchy (modern)
1. **Sleep** (8-10 h elite).
2. **Nutrition + hydration**.
3. **Active recovery**.
4. **Modality** (cold, compression — 매 evidence weak).
**언제 쓰면 안 되는가:**
- *(TODO)*
### 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.
## 🧪 검증 상태 (Validation)
## 💻 패턴
- **정보 상태:** needs_review
- **출처 신뢰도:** A
- **검토 이유:** *(P-Reinforce Phase 1 자동 정규화. 본문 검증 필요.)*
### Acute:Chronic Workload Ratio (Gabbett)
```python
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}
```
## 🧬 중복 검사 (Duplicate Check)
### HRV-guided training
```python
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'
```
- **기존 유사 문서:** *(TODO: 인덱서 클러스터 리포트 참조)*
- **처리 방식:** UPDATE (자동 정규화)
- **처리 이유:** Phase 1 정규화 — 옛 템플릿/누락 필드 보강.
### Session RPE (Foster)
```python
def session_rpe_load(rpe_0_10, duration_min):
return rpe_0_10 * duration_min # 매 AU (arbitrary units)
## 🕓 변경 이력 (Changelog)
def weekly_monotony(daily_loads):
return np.mean(daily_loads) / max(np.std(daily_loads), 1e-6)
| 날짜 | 변경 내용 | 처리 방식 | 신뢰도 |
|------|-----------|-----------|--------|
| 2026-05-08 | P-Reinforce Phase 1 정규화 (frontmatter + 헤더 표준화) | UPDATE | A |
def strain(weekly_load, monotony):
return weekly_load * monotony # 매 > 6000 = high illness risk
```
### Bondarchuk periodization (block)
```python
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
```python
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)
```python
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
```python
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
```python
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)
```python
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
```python
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
```python
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)
```python
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]] · [[Block-Periodization]] · [[Polarized-Training]]
- 응용: [[Strength-Conditioning]] · [[Endurance-Athletics-Cognition]]
- Adjacent: [[Recovery]] · [[Sleep-Optimization]] · [[GPS-Tracking]] · [[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 |