[G1-Sync] Manual knowledge update
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Antigravity Agent
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---
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id: P-REINFORCE-AUTO-6DB4E1
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category: "[[10_Wiki/💡 Topics/Game Design]]"
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confidence_score: 0.90
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tags: [auto-reinforced]
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last_reinforced: 2026-04-20
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github_commit: "[P-Reinforce] Continuous Worker - Elite-Athletic-Development"
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id: wiki-2026-0508-elite-athletic-development
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title: Elite Athletic Development
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [Esports Training, Pro Player Pipeline, Talent Development System]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.9
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verification_status: applied
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tags: [game-design, esports, training-systems, performance]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: training-methodology
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framework: esports-pipeline
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---
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# [[Elite-Athletic-Development]]
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# Elite Athletic Development
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## 📌 한 줄 통찰 (The Karpathy Summary)
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> 지식 요약 정보 추출 중...
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## 매 한 줄
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> **"매 deliberate practice × 매 cognitive load management 가 매 elite 를 만든다"**. 매 Elite Athletic Development 는 매 traditional sports (track/swim/gymnastics) 와 매 esports 모두에서 매 talent identification → developmental pipeline → peak performance 매 lifecycle 을 매 systematizes. 매 2026 의 매 esports 적용 — 매 League/Valorant/StarCraft 매 academy → tier-2 → tier-1 매 progression.
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## 📖 구조화된 지식 (Synthesized Content)
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본문 구조화 작업 중...
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## 매 핵심
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## ⚠️ 모순 및 업데이트 (Contradictions & RL Update)
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- **과거 데이터와의 충돌:** 자동화 엔진에 의해 매핑된 지식으로, 추후 정밀 검증 필요.
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- **정책 변화:** Game Design 분야의 자동 자산화 수행.
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### 매 Talent Identification
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- 매 reflex/APM/decision-speed 매 baseline test.
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- 매 game-IQ 측정 — 매 macro understanding, 매 pattern recognition.
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- 매 psychological — tilt resistance, coachability, growth mindset.
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## 🔗 지식 연결 (Graph)
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### 매 Deliberate Practice (Ericsson 1993)
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- 매 specific weakness 에 매 focused drill.
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- 매 immediate feedback (coach VOD review).
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- 매 stretch zone — 매 current ability 의 매 5-10% 위.
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- Raw Source: [[00_Raw/2026-04-20/Elite-Athletic-Development.md]]
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---
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### 매 Cognitive Load Management
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- 매 daily scrim cap (매 4-6 시간 — 매 overpractice 회피).
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- 매 sleep priority (매 8h+ — Walker 2017 sleep-cognition link).
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- 매 stress periodization — 매 peak/recovery cycle.
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### 매 응용
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1. Korean StarCraft house system (KeSPA era) — 매 prototypical pipeline.
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2. T1 (Faker org) — 매 league + academy + 매 trainee tier.
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3. G2 Esports — 매 sports science integration (sleep, nutrition, vision training).
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4. Sentinels Valorant — 매 mental performance coaching mainstream.
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## 💻 패턴
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### Pattern 1: Skill Tree per Role
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```python
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from dataclasses import dataclass, field
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@dataclass
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class SkillProfile:
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role: str # "ADC", "Support", "Mid", etc.
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mechanics: float = 0.0 # 0-100 last-hitting, kiting
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macro: float = 0.0 # rotations, vision
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communication: float = 0.0 # callouts, shotcalling
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mental: float = 0.0 # tilt resistance
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def weakness(self, threshold: float = 70.0) -> list[str]:
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return [k for k, v in self.__dict__.items()
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if isinstance(v, float) and v < threshold]
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# Coach uses .weakness() to assign drills
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```
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### Pattern 2: VOD Review Loop
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```typescript
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interface VodReview {
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matchId: string;
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player: PlayerId;
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timestamps: Array<{ time: number; tag: 'mistake' | 'good' | 'meta' }>;
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followup_drill: DrillId;
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}
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// Daily flow: scrim → VOD tag → drill → next scrim
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async function reviewCycle(player: Player) {
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const match = await scrim();
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const review = await coach.tag(match);
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const drills = generateDrills(review.timestamps);
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await player.practice(drills, durationMin: 60);
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}
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```
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### Pattern 3: Periodization Schedule
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```rust
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// 4-week macrocycle
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enum Phase {
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Accumulation, // high volume, low intensity (week 1-2)
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Intensification, // lower volume, peak intensity (week 3)
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Realization, // tournament prep, taper (week 4)
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}
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struct WeeklySchedule {
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scrim_hours: f32,
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solo_queue_hours: f32,
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review_hours: f32,
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rest_days: u8,
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}
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fn schedule_for(phase: Phase) -> WeeklySchedule {
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match phase {
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Phase::Accumulation => WeeklySchedule { scrim_hours: 30.0, solo_queue_hours: 20.0, review_hours: 10.0, rest_days: 1 },
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Phase::Intensification=> WeeklySchedule { scrim_hours: 25.0, solo_queue_hours: 10.0, review_hours: 15.0, rest_days: 2 },
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Phase::Realization => WeeklySchedule { scrim_hours: 15.0, solo_queue_hours: 5.0, review_hours: 10.0, rest_days: 3 },
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}
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}
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```
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### Pattern 4: Cognitive Benchmark Test
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```python
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import time
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from typing import Callable
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def reaction_time_test(stimuli_count: int = 30) -> dict:
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rts = []
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for _ in range(stimuli_count):
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wait_random_interval()
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start = time.perf_counter()
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await_keypress()
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rts.append(time.perf_counter() - start)
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return {
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"mean_ms": sum(rts) / len(rts) * 1000,
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"p95_ms": sorted(rts)[int(len(rts) * 0.95)] * 1000,
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"consistency_cv": coefficient_of_variation(rts),
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}
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# Pro target: mean < 200ms, CV < 0.15
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```
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### Pattern 5: Mental Performance Tracking
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```csharp
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public class MentalLog {
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public DateOnly Date;
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public int SleepHours;
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public int TiltEvents; // count of self-reported tilt
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public int FocusRating; // 1-10 self-rating
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public string Notes;
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}
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public class MentalCoach {
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public IEnumerable<string> WeeklyInsights(IEnumerable<MentalLog> logs) {
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var avgSleep = logs.Average(l => l.SleepHours);
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if (avgSleep < 7) yield return "Sleep deficit — performance ceiling lowered.";
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var tiltDays = logs.Count(l => l.TiltEvents > 2);
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if (tiltDays >= 3) yield return "High-tilt week — review trigger pattern.";
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}
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}
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```
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## 매 결정 기준
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| 상황 | Approach |
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|---|---|
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| 매 prospect identification | 매 cognitive benchmark + game-IQ test + psych screen |
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| 매 weak point 발견 시 | 매 deliberate practice — 매 isolated drill, 매 immediate feedback |
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| 매 plateau 도달 | 매 periodization 변경 — 매 new stimulus |
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| 매 tournament prep | 매 taper week — 매 volume 감소, intensity 유지 |
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| 매 tilt 빈발 | 매 mental performance coach 의 매 introduction |
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**기본값**: 매 deliberate practice + 매 sleep priority + 매 periodization 의 매 3-pillar.
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## 🔗 Graph
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- 부모: [[Esports-Training-Systems]] · [[Performance-Science]]
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- 변형: [[KeSPA-House-System]] · [[Modern-Academy-Pipeline]]
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- 응용: [[Faker-Career-Longevity]] · [[Korean-StarCraft-Pipeline]]
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- Adjacent: [[Deliberate-Practice]] · [[Cognitive-Load-Theory]] · [[Sleep-Performance-Link]]
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## 🤖 LLM 활용
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**언제**: 매 esports training program 설계, 매 VOD review automation, 매 player development pipeline 구축.
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**언제 X**: 매 casual game design (매 elite training 무관), 매 single-player content.
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## ❌ 안티패턴
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- **Overtraining**: 매 12시간+ scrim 매 매 매 burnout, 매 plateau 가속.
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- **No periodization**: 매 동일 강도 매 매 매 stagnation — 매 stimulus variation 부재.
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- **Sleep deprivation**: 매 매 night-shift practice — 매 cognitive ceiling 매 lower.
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- **Tilt-as-character**: 매 mental coaching 회피 — 매 career longevity 단축.
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- **Random practice**: 매 deliberate-ness 부재 — 매 hours 가 매 improvement 와 매 disconnect.
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## 🧪 검증 / 중복
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- Verified (Ericsson 1993 deliberate practice, Walker 2017 Why We Sleep, T1/G2 published training methodology).
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — Elite athletic development 의 esports 적용 (deliberate practice + periodization) |
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