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RNG Fairness Simulator for Game Studios
Build a SaaS and engine plugin that lets game teams simulate, compare, and tune true randomness versus player-friendly randomness before shipping. The product would quantify streaks, expected player frustration, displayed-vs-actual odds, and genre-specific fairness profiles so designers can make deliberate tradeoffs instead of guessing.
이것이 중요한 이유
You are designing a system where chance drives excitement, but real randomness keeps producing ugly streaks that players interpret as bugs or bad design. If you secretly smooth outcomes, you risk angry posts, balance confusion, and distrust once dedicated players inspect the numbers. Today you patch this with ad hoc formulas, spreadsheets, and gut feel. That works until a late-stage balance pass or launch exposes that your displayed odds, actual logic, and player experience do not line up. You need a way to test how randomness feels before release, not after community backlash.
- · Indie and mid-size game studios building combat, loot, gacha-lite, or tactics systems where probability strongly affects player sentiment.을(를) 위해 제작되었습니다.
- · 가장 유력한 수익화 모델: SaaS subscription.
고충 · 내러티브
You are designing a system where chance drives excitement, but real randomness keeps producing ugly streaks that players interpret as bugs or bad design. If you secretly smooth outcomes, you risk angry posts, balance confusion, and distrust once dedicated players inspect the numbers. Today you patch this with ad hoc formulas, spreadsheets, and gut feel. That works until a late-stage balance pass or launch exposes that your displayed odds, actual logic, and player experience do not line up. You need a way to test how randomness feels before release, not after community backlash.
점수 세부
시장 신호
시장 진출 전략
Indie strategy and roguelike developers using Unity who expose hit chances, loot chances, or crit rates in their UI.
~30K-80K globally in the initial niche
r/<community> organic
$29/month
20 teams run at least 3 simulations each and 5 convert to paid plans within 30 days of launch
MVP 범위 · 1~2주
- Define 4 RNG models: pure random, streak smoothing, deck-based, and pity timer
- Build a simple simulator API that accepts odds and trial counts
- Create dashboard charts for hit rate distribution and streak length
- Add CSV export for simulation results
- Launch a landing page with a fairness calculator demo
- Add displayed-odds versus actual-odds mismatch alerts
- Implement genre presets for tactics, loot, and mobile progression systems
- Build a basic Unity package to send values into the simulator
- Add shareable report links for team review
- Interview 10 developers and refine top metrics shown in the dashboard
차별화
실패 가능 요인
자가 반박 — 가장 중요한 신뢰 신호
- 1Studios may treat RNG tuning as a one-off design task and resist recurring SaaS pricing.
- 2If the simulator does not map clearly to real player sentiment, teams may see it as interesting but nonessential.
- 3Large studios may prefer internal analytics pipelines, limiting expansion beyond indies and small teams.
근거 요약
AI가 이 인사이트를 합성한 방법 — 직접 인용 없음
The strongest signal is repeated discussion around smoothing streaks, hidden assistance, and the gap between mathematical fairness and emotional fairness. Roughly a dozen comments centered on the idea that true RNG often feels wrong, while several also warned that inaccurate displayed percentages create trust issues. That combination points to a practical need for tooling that helps teams model both outcome quality and player perception.
액션 플랜
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권장 다음 단계
개발 시작
강한 수요 신호 감지. 실제 고통과 지불 의지 확인 — MVP 개발을 시작하세요.
랜딩 페이지 카피 키트
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헤드라인
RNG Fairness Simulator for Game Studios
서브 헤드라인
Build a SaaS and engine plugin that lets game teams simulate, compare, and tune true randomness versus player-friendly randomness before shipping. The product would quantify streaks, expected player frustration, displayed-vs-actual odds, and genre-specific fairness profiles so designers can make deliberate tradeoffs instead of guessing.
대상 사용자
대상: Indie and mid-size game studios building combat, loot, gacha-lite, or tactics systems where probability strongly affects player sentiment.
기능 목록
✓ Monte Carlo simulation of multiple RNG models ✓ Streak and frustration analytics dashboard ✓ Displayed-odds versus actual-odds comparison reports ✓ Unity and Unreal import/plugin support ✓ Preset fairness models such as pity, deck, smoothing, and dynamic bias ✓ Probability copy and UI pattern recommendations ✓ Mismatch detection between exact numbers and hidden modifiers ✓ Disclosure templates for luck bonuses and bad-luck prevention
어디서 검증할까요
r/r/gamedev에 랜딩 페이지 링크를 공유하세요 — 바로 이 고통이 발견된 곳입니다.
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