---
id: wiki-2026-0508-elite-athletic-development
title: Elite Athletic Development
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [Esports Training, Pro Player Pipeline, Talent Development System]
duplicate_of: none
source_trust_level: A
confidence_score: 0.9
verification_status: applied
tags: [game-design, esports, training-systems, performance]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: training-methodology
  framework: esports-pipeline
---

# Elite Athletic Development

## 매 한 줄
> **"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.

## 매 핵심

### 매 Talent Identification
- 매 reflex/APM/decision-speed 매 baseline test.
- 매 game-IQ 측정 — 매 macro understanding, 매 pattern recognition.
- 매 psychological — tilt resistance, coachability, growth mindset.

### 매 Deliberate Practice (Ericsson 1993)
- 매 specific weakness 에 매 focused drill.
- 매 immediate feedback (coach VOD review).
- 매 stretch zone — 매 current ability 의 매 5-10% 위.

### 매 Cognitive Load Management
- 매 daily scrim cap (매 4-6 시간 — 매 overpractice 회피).
- 매 sleep priority (매 8h+ — Walker 2017 sleep-cognition link).
- 매 stress periodization — 매 peak/recovery cycle.

### 매 응용
1. Korean StarCraft house system (KeSPA era) — 매 prototypical pipeline.
2. T1 (Faker org) — 매 league + academy + 매 trainee tier.
3. G2 Esports — 매 sports science integration (sleep, nutrition, vision training).
4. Sentinels Valorant — 매 mental performance coaching mainstream.

## 💻 패턴

### Pattern 1: Skill Tree per Role
```python
from dataclasses import dataclass, field

@dataclass
class SkillProfile:
    role: str  # "ADC", "Support", "Mid", etc.
    mechanics: float = 0.0      # 0-100 last-hitting, kiting
    macro: float = 0.0          # rotations, vision
    communication: float = 0.0  # callouts, shotcalling
    mental: float = 0.0         # tilt resistance

    def weakness(self, threshold: float = 70.0) -> list[str]:
        return [k for k, v in self.__dict__.items()
                if isinstance(v, float) and v < threshold]

# Coach uses .weakness() to assign drills
```

### Pattern 2: VOD Review Loop
```typescript
interface VodReview {
  matchId: string;
  player: PlayerId;
  timestamps: Array<{ time: number; tag: 'mistake' | 'good' | 'meta' }>;
  followup_drill: DrillId;
}

// Daily flow: scrim → VOD tag → drill → next scrim
async function reviewCycle(player: Player) {
  const match = await scrim();
  const review = await coach.tag(match);
  const drills = generateDrills(review.timestamps);
  await player.practice(drills, durationMin: 60);
}
```

### Pattern 3: Periodization Schedule
```rust
// 4-week macrocycle
enum Phase {
    Accumulation,   // high volume, low intensity (week 1-2)
    Intensification, // lower volume, peak intensity (week 3)
    Realization,    // tournament prep, taper (week 4)
}

struct WeeklySchedule {
    scrim_hours: f32,
    solo_queue_hours: f32,
    review_hours: f32,
    rest_days: u8,
}

fn schedule_for(phase: Phase) -> WeeklySchedule {
    match phase {
        Phase::Accumulation   => WeeklySchedule { scrim_hours: 30.0, solo_queue_hours: 20.0, review_hours: 10.0, rest_days: 1 },
        Phase::Intensification=> WeeklySchedule { scrim_hours: 25.0, solo_queue_hours: 10.0, review_hours: 15.0, rest_days: 2 },
        Phase::Realization    => WeeklySchedule { scrim_hours: 15.0, solo_queue_hours: 5.0,  review_hours: 10.0, rest_days: 3 },
    }
}
```

### Pattern 4: Cognitive Benchmark Test
```python
import time
from typing import Callable

def reaction_time_test(stimuli_count: int = 30) -> dict:
    rts = []
    for _ in range(stimuli_count):
        wait_random_interval()
        start = time.perf_counter()
        await_keypress()
        rts.append(time.perf_counter() - start)
    return {
        "mean_ms": sum(rts) / len(rts) * 1000,
        "p95_ms": sorted(rts)[int(len(rts) * 0.95)] * 1000,
        "consistency_cv": coefficient_of_variation(rts),
    }
# Pro target: mean < 200ms, CV < 0.15
```

### Pattern 5: Mental Performance Tracking
```csharp
public class MentalLog {
    public DateOnly Date;
    public int SleepHours;
    public int TiltEvents;       // count of self-reported tilt
    public int FocusRating;      // 1-10 self-rating
    public string Notes;
}

public class MentalCoach {
    public IEnumerable<string> WeeklyInsights(IEnumerable<MentalLog> logs) {
        var avgSleep = logs.Average(l => l.SleepHours);
        if (avgSleep < 7) yield return "Sleep deficit — performance ceiling lowered.";
        var tiltDays = logs.Count(l => l.TiltEvents > 2);
        if (tiltDays >= 3) yield return "High-tilt week — review trigger pattern.";
    }
}
```

## 매 결정 기준
| 상황 | Approach |
|---|---|
| 매 prospect identification | 매 cognitive benchmark + game-IQ test + psych screen |
| 매 weak point 발견 시 | 매 deliberate practice — 매 isolated drill, 매 immediate feedback |
| 매 plateau 도달 | 매 periodization 변경 — 매 new stimulus |
| 매 tournament prep | 매 taper week — 매 volume 감소, intensity 유지 |
| 매 tilt 빈발 | 매 mental performance coach 의 매 introduction |

**기본값**: 매 deliberate practice + 매 sleep priority + 매 periodization 의 매 3-pillar.

## 🔗 Graph
- Adjacent: [[Deliberate-Practice]] · [[Cognitive Load Theory|Cognitive-Load-Theory]]

## 🤖 LLM 활용
**언제**: 매 esports training program 설계, 매 VOD review automation, 매 player development pipeline 구축.
**언제 X**: 매 casual game design (매 elite training 무관), 매 single-player content.

## ❌ 안티패턴
- **Overtraining**: 매 12시간+ scrim 매 매 매 burnout, 매 plateau 가속.
- **No periodization**: 매 동일 강도 매 매 매 stagnation — 매 stimulus variation 부재.
- **Sleep deprivation**: 매 매 night-shift practice — 매 cognitive ceiling 매 lower.
- **Tilt-as-character**: 매 mental coaching 회피 — 매 career longevity 단축.
- **Random practice**: 매 deliberate-ness 부재 — 매 hours 가 매 improvement 와 매 disconnect.

## 🧪 검증 / 중복
- Verified (Ericsson 1993 deliberate practice, Walker 2017 Why We Sleep, T1/G2 published training methodology).
- 신뢰도 A.

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — Elite athletic development 의 esports 적용 (deliberate practice + periodization) |
