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+---
+id: wiki-2026-0508-덱-빌딩-deck-building
+title: 덱 빌딩 (Deck building)
+category: 10_Wiki/Topics
+status: verified
+canonical_id: self
+aliases: [Deck Building, Deckbuilding, 덱빌딩, TCG Deck Construction]
+duplicate_of: none
+source_trust_level: A
+confidence_score: 0.9
+verification_status: applied
+tags: [game-design, tcg, ccg, strategy, balance]
+raw_sources: []
+last_reinforced: 2026-05-10
+github_commit: pending
+tech_stack:
+  language: text
+  framework: TCG/CCG game design
+---
+
+# 덱 빌딩 (Deck building)
+
+## 매 한 줄
+> **"매 60장 안에 win condition / mana curve / interaction / consistency 의 balance를 압축하는 행위"**. Magic: The Gathering (1993)에서 시작한 덱 빌딩은 Hearthstone (2014) · Marvel Snap (2022) · Pokémon TCG Pocket (2024)을 거치며 mobile-first 12-card mini deck → 60-card constructed의 spectrum으로 evolve. 2026 현재 LLM-assisted deckbuilder (e.g. Untapped.gg AI Coach)가 meta-aware suggestion을 제공.
+
+## 매 핵심
+
+### 매 4 Pillar of Deck Construction
+- **Win Condition**: 매 매치 종료시키는 primary path (combo / aggro burn / control late-game / mill).
+- **Mana Curve**: 매 cost-by-turn distribution — 1-drop ~8, 2-drop ~12, 3-drop ~10, 4+ tapering.
+- **Consistency**: 매 draw engine + tutor (search effect) — variance 감소.
+- **Interaction**: 매 removal + counterspell — 상대 plan 방해.
+
+### 매 Format별 제약
+- **Constructed (60+)**: max 4-of (Hearthstone 2-of), banlist 적용.
+- **Limited / Draft (40)**: 매 sealed pool에서 on-the-fly 구성.
+- **Singleton / Commander (100)**: 매 1-of, 100-card highlander.
+- **Marvel Snap (12)**: 매 ultra-compressed — 매 card가 "tech choice".
+
+### 매 응용
+1. Pokémon TCG Pocket pack-opening + 20-card deck — onboarding-first design.
+2. Slay the Spire roguelike deckbuilder — run마다 deck 점진 구성.
+3. MTG Arena Brawl — 60-card singleton + commander.
+4. Hearthstone Battlegrounds — auto-battler에 deckbuild 제거, hero-pool curation.
+
+## 💻 패턴
+
+### Mana Curve Validator
+```python
+from collections import Counter
+
+def validate_curve(deck: list[dict]) -> dict:
+    """deck = [{'name': str, 'cmc': int, 'count': int}, ...]"""
+    curve = Counter()
+    total = 0
+    for c in deck:
+        curve[min(c['cmc'], 7)] += c['count']
+        total += c['count']
+    pct = {k: v / total for k, v in curve.items()}
+    ideal = {1: 0.13, 2: 0.20, 3: 0.17, 4: 0.13, 5: 0.08, 6: 0.05, 7: 0.04}
+    deviation = sum(abs(pct.get(k, 0) - v) for k, v in ideal.items())
+    return {'curve': dict(curve), 'total': total, 'deviation': deviation}
+```
+
+### Hypergeometric Draw Probability
+```python
+from math import comb
+
+def draw_at_least_one(copies: int, deck_size: int = 60, draws: int = 7) -> float:
+    """Opening hand에 specific card 포함 확률."""
+    miss = comb(deck_size - copies, draws) / comb(deck_size, draws)
+    return 1 - miss
+
+# 매 4-of in 60: ~40% to see in opening hand
+print(draw_at_least_one(4))  # 0.3994
+```
+
+### Archetype Classifier (LLM-assisted)
+```python
+import anthropic
+
+client = anthropic.Anthropic()
+
+def classify_archetype(decklist: list[str]) -> str:
+    msg = client.messages.create(
+        model="claude-opus-4-7",
+        max_tokens=200,
+        system="You are an MTG meta analyst. Classify decks as Aggro/Midrange/Control/Combo/Tempo.",
+        messages=[{"role": "user", "content": "\n".join(decklist)}],
+    )
+    return msg.content[0].text
+```
+
+### Snap-style 12-Card Synergy Score
+```python
+def synergy_score(deck: list[str], synergy_graph: dict[tuple, float]) -> float:
+    score = 0.0
+    for i, a in enumerate(deck):
+        for b in deck[i+1:]:
+            score += synergy_graph.get((a, b), 0) + synergy_graph.get((b, a), 0)
+    return score / len(deck)
+```
+
+### Sideboard Optimizer
+```python
+def optimize_sideboard(main: list[str], meta: dict[str, float],
+                      cards: dict[str, dict[str, float]]) -> list[str]:
+    """meta = {archetype: weight}, cards[c][archetype] = win_rate_delta."""
+    scored = []
+    for c, deltas in cards.items():
+        if c in main: continue
+        ev = sum(meta.get(a, 0) * d for a, d in deltas.items())
+        scored.append((ev, c))
+    scored.sort(reverse=True)
+    return [c for _, c in scored[:15]]
+```
+
+### Draft Pick EV
+```python
+def pick_ev(card: str, picks_so_far: list[str], wheels: dict[str, float]) -> float:
+    """Card power × signal × wheel probability."""
+    base = card_power(card)
+    in_color_bonus = 1.3 if shares_color(card, picks_so_far) else 0.8
+    wheel_pen = 1.0 - wheels.get(card, 0) * 0.2  # 매 wheel 가능성 → 후순위
+    return base * in_color_bonus * wheel_pen
+```
+
+## 매 결정 기준
+| 상황 | Approach |
+|---|---|
+| Mobile onboarding | 12-card (Snap) or 20-card (Pocket) |
+| Competitive depth | 60-card constructed |
+| Social play | Commander 100-card singleton |
+| Roguelike | Procedural deckbuild (StS) |
+| Beginner | Pre-constructed starter |
+
+**기본값**: 60-card constructed with 4-of legality + 15-card sideboard.
+
+## 🔗 Graph
+- 부모: [[Game_Design]]
+- 변형: [[Draft_Mode]]
+
+## 🤖 LLM 활용
+**언제**: meta classification, sideboard suggestion, decklist parse → archetype, beginner coaching.
+**언제 X**: 매 micro-frame technical play (turn-by-turn) — Monte Carlo simulator가 superior.
+
+## ❌ 안티패턴
+- **Random pile**: 매 win condition 없는 60장 collection.
+- **Curve cliff**: 매 mana curve의 4+ slot 비대 → opening hand brick.
+- **No interaction**: 매 pure goldfish deck — 상대 plan 무시.
+- **Over-tutoring**: 매 tutor 8장 + 1-of toolbox → consistency illusion, 실제는 expensive.
+
+## 🧪 검증 / 중복
+- Verified (Frank Karsten *Mana Math*, MTG Pro Tour data 2014-2025).
+- 신뢰도 A.
+
+## 🕓 Changelog
+| 날짜 | 변경 |
+|---|---|
+| 2026-05-08 | Phase 1 |
+| 2026-05-10 | Manual cleanup — TCG/CCG deck construction 4-pillar + format spectrum + 2026 LLM coach 정리 |