Chapter 1: Introduction — Why Gaming Needs Its Own Large Model

Over the past two decades, the gaming industry has undergone massive transformation — from offline to online, from PC to mobile, and from pay-to-play to free-to-play. Today, it stands as one of the largest digital entertainment sectors in the world. According to Newzoo, the global game market surpassed $200 billion in 2024, with over 3 billion players worldwide. Gaming is no longer a niche hobby; it is a global cultural and economic phenomenon.

Yet, beneath this booming surface lies a clear contradiction: The industry keeps growing rapidly, but the player experience is becoming increasingly complicated. This problem manifests in several ways:

1. Information Overload and Fragmentation Most mainstream games — especially competitive ones like League of Legends, Valorant, or DOTA 2 — release patches every few weeks. Each patch adjusts hero stats, item attributes, or map mechanics, dramatically reshaping the meta. However, players have to rely on scattered sources — patch notes, Reddit threads, Bilibili videos, or pro-player streams. The information is inconsistent and overwhelming, forcing players to spend hours verifying and learning.

2. Complex Mechanics and High Entry Barriers Modern games are far beyond the “press a few buttons to win” era. In Genshin Impact, players must understand character skills, artifact sets, and elemental reactions; in Elden Ring, a single boss fight can have a dozen phase changes, each requiring distinct strategies. For newcomers, these layers of complexity can feel impenetrable.

3. Lack of Transparency and Liquidity in Digital Assets With the dominance of “free-to-play + in-app purchase” models, virtual items have become integral assets. Skins, weapons, and cards represent identity and rarity. For example, the CS2 skin market alone generates billions in annual volume. Yet, pricing remains opaque, markets are fragmented, and players often make poor decisions due to asymmetric information.

4. Absence of Truly Intelligent Assistants Although AI tools like ChatGPT or Claude can answer general questions, they often fail in gaming contexts — giving irrelevant or outdated responses. They lack domain-specific training, cannot interpret live patch updates, and do not provide actionable gameplay advice. What players need is not a generalist assistant that “knows a bit of everything,” but a vertical large model — one that deeply understands games and actually helps players win.

5. Gaming = Entertainment + Economy With the rise of Web3, more games are integrating blockchain to tokenize in-game assets as NFTs or tradable tokens. “Play-to-earn” has become reality. However, the ecosystem remains fragmented, valuation systems inconsistent, and regulations unclear — making it difficult for ordinary players to assess risk and opportunity.

In short, the gaming world today is richer in content but poorer in clarity. That’s why we created the Real Player Model (RPM) — a vertical large model dedicated to gaming, designed to reduce information costs, enhance player experience, and empower rational decision-making in the era of digital assets.

Chapter 2: Vision — Play Smarter, Own Fairer

The role of players in the gaming universe is transforming. In the past, they were content consumers — buying games, spending money, clearing levels. Now, as games grow in complexity and economic depth, players have become co-creators, community builders, and asset holders.

The vision of the Real Player Model (RPM) can be summarized in eight words: “Play smarter, own fairer.”

1. Play Smarter — The Intelligent Game Assistant

The essence of gaming is play — yet modern games demand tremendous learning effort:

• After each patch, players must analyze reworked stats and study hours of guides.

• Boss fights have layered mechanics that require repeated trial and error.

• In competitive games, new “metas” emerge every few days, exhausting even veterans.

Most players spend more time researching than enjoying the game.

RPM’s mission is to make AI a natural companion for every player:

• When a new patch drops, RPM instantly analyzes all changes and delivers clear insights: “In Patch 13.5, X is the strongest ADC because Y.”

• When a player gets stuck, they can ask: “How do I beat this boss with only free gear?” RPM gives the optimal, step-by-step strategy.

• For competitive players, RPM reviews match data and provides personalized improvement tips: “Your Flash usage rate is 20% lower than top players — that’s the key factor reducing your win rate.”

In essence, RPM lowers the information barrier and lets every player truly enjoy the fun of gaming.

1. Own Fairer — Transparent Digital Asset Ecosystem

Virtual assets now mirror real-world economics. Skins, weapons, and collectible cards hold real value through rarity and demand. Yet today’s markets suffer from:

1. Opaque Valuation: the same item may be priced wildly differently across platforms.

2. Fragmented Liquidity: players must jump between multiple exchanges or gray markets.

3. Uncontrollable Risk: newcomers often fall victim to misinformation or predatory pricing.

The solution lies in AI-driven valuation and trading assistance:

• RPM aggregates multi-market data to build cross-platform pricing models.

• It evaluates scarcity, trade volume, and volatility to suggest fair price ranges.

• It tailors buy/sell recommendations to player intent — whether collecting, investing, or competing.

Moreover, RPM bridges RWA (Real-World Assets) with gaming assets — allowing physical items (e.g., collectible cards, game merchandise) to be traded alongside NFTs and digital skins in one interface.

This cross-domain fusion finally creates a fair market for gamers:

• No more hidden information asymmetry.

• No more reliance on gray-market middlemen.

• Every trade becomes transparent and traceable.

1. Player-First — The DAO Principle

The founding spirit of Real Player DAO is to turn players from passive participants into active decision-makers.

Under RPM’s DAO governance model:

• Players can submit game data, test strategies, and contribute to model improvement.

• They can share in ecosystem revenue — from trading commissions to RWA investment returns.

• Most importantly, their collective voice guides RPM’s evolution.

Our ambition is not merely to build a product, but to create an ecosystem where:

• Players are both users and contributors.

• The model is both a tool and a companion.

• Gaming becomes not just entertainment, but a network of value creation and fair sharing.

1. Vision Summary

“Play smarter, own fairer” is not just a slogan — it’s our blueprint for the next era of gaming:

• AI lowers the cost of learning and mastery, restoring the joy of play.

• RWA + AI ensures transparency and liquidity for digital assets.

• DAO governance gives power back to players, making them the true Real Players.

That is the purpose of the Real Player Model (RPM) — not merely a model, but a bridge to the next generation of the gaming ecosystem.

Chapter 3: Product Positioning

3.1 What Is the Real Player Model (RPM)

The Real Player Model (RPM) is a vertical large model dedicated to the gaming domain. Its mission is not to be a general-purpose AI that “knows a little bit about everything,” but rather to deeply understand the language, logic, and asset systems of the gaming ecosystem — and to provide players with truly valuable assistance.

RPM serves as both a personal assistant for players and a collaborative partner for game studios and platforms. It can provide real-time strategic support during gameplay, and offer accurate valuation and trading guidance for virtual assets outside of the game.

Compared with general-purpose AIs like ChatGPT, RPM’s core strengths lie in its depth and precision:

• Depth — It comprehends patch mechanisms, tactical logic, card synergies, and asset valuation models specific to games.

• Precision — It provides actionable, verifiable insights rather than vague or fabricated responses.

In short, RPM is a large model built for players.

3.2 How RPM Differs from General Large Models

Mainstream general models face three key limitations when applied to gaming:

1. Lack of Real-Time Updates

   • ChatGPT can answer general knowledge questions, but struggles with time-sensitive ones like “Who is the strongest ADC in League of Legends patch 14.2?” because it lacks access to live patch data.

2. Lack of Domain Depth

   • A general model might know a character’s skill names, but not how their stats interact or how to optimize tactical compositions. For example, in Genshin Impact, elemental reactions involve complex numerical interactions — something generic models can’t meaningfully analyze to give optimal team suggestions.

3. Lack of Asset Awareness

   • A general model can describe how a skin looks, but not assess its fair market price or compare listings across trading platforms.

RPM is designed precisely to solve these shortcomings:

• It connects directly to live patch data and market feeds to ensure real-time accuracy.

• It is trained on dedicated gaming knowledge graphs and player behavior datasets to ensure depth and expertise.

• It integrates valuation and trading logic to ensure fairness and transparency.

3.3 The Three Core Roles of RPM

1. Strategy & Knowledge Assistant

   • Provides instant, version-specific tactical recommendations.

   • Explains the deeper impact of patch updates.

   • Translates complex game mechanics into clear, actionable guidance.

2. Script & Action Generator

   • Converts natural language into compliant in-game operations.

   • Enables players to issue voice or text commands to generate battle plans or assistive automation.

   • Reduces learning curves and allows more players to get started faster.

3. Asset & Market Advisor

   • Offers fair valuations for items, cards, and skins.

   • Supports cross-platform price comparison and transaction recommendations.

   • Protects players from losses due to information asymmetry.

Together, these three roles form RPM’s closed-loop value chain — from “how to play” → “how to play better” → “how to own fairly.”

3.4 Value for Different User Groups

For Players:

• Beginners: Quickly learn game mechanics and lower entry barriers.

• Intermediate Players: Improve skills and increase win rates.

• Veterans / Pros: Analyze tactics and save research time.

• Asset Holders / Collectors: Access transparent and fair price benchmarks.

For the Industry:

• Game Developers: Integrate RPM via APIs to enable narrative generation, NPC intelligence, or gameplay balancing tools.

• Platforms: Use RPM’s valuation engine to enhance market liquidity and fairness.

• Communities: Contribute to data curation and validation through DAO mechanisms.

3.5 Product Positioning Summary

Real Player Model (RPM) = Strategy Assistant + Script Generator + Asset Advisor

It is not merely an AI tool — it is a new bridge between players and games:

• Helping players enjoy games with less friction.

• Making virtual asset trading transparent and trustworthy.

• Creating new collaboration opportunities between studios and communities.

If a general large model is like an encyclopedia, then RPM is the player’s personal strategist — a true “Game Master AI.”

Chapter 4: Core Feature Modules

The Real Player Model (RPM) is not designed as a “general-purpose chatbot.” It targets the three core needs of players:

1. How do I play? (Strategy & Knowledge Assistant)

2. How do I execute? (Script Generation & Assist)

3. How do I own? (Assets & RWA System)

Around these needs, RPM’s core features are organized into four modules:

4.1 Module One: AI Game Assistant

This is RPM’s most immediate value. Today, nearly all popular games update regularly; a single stat tweak can invalidate old guides overnight. To stay current, players often must:

• Read tens of thousands of words of official patch notes;

• Sift through community threads to separate signal from noise;

• Watch hours-long guide videos.

The experience is inefficient and discourages many casual players.

RPM’s solution:

• Automatic Patch Parsing: Extracts numeric changes within minutes of release and flags which adjustments materially impact the meta.

• Instant Strategy Generation: Combines historical match data with pro play insights to produce clear tactical recommendations.

• Personalized Recommendations: Tailors playstyles to a player’s habits and character preferences.

Use cases:

• League of Legends: Ask, “Who’s the strongest mid laner in patch 14.2?” RPM returns the latest picks with reasons.

• Genshin Impact: Say, “Build me a budget-friendly Pyro team,” and RPM outputs the lineup, artifacts, and rotation.

Result: players spend less time hunting information and more time enjoying the game.

4.2 Module Two: Script Generation & Assist

Modern games demand high operational complexity. In CS2, a single match can require hundreds of precise actions; in Elden Ring, a boss may demand dozens of perfect dodges and combos. For many, that’s stamina and reflex tax, not pure fun.

RPM’s solution:

• Natural Language → Actions: Speak or type commands—e.g., “Write a flash-entry combo script”—and AI generates the corresponding key sequence.

• Compliance Guardrails: A built-in whitelist of publisher APIs and rules outputs only permitted macros and assist actions, avoiding “cheatware.”

• Layered Assistance: From teaching scripts (instructional, step-by-step) to execution scripts (automated assist), adjustable by game and user context.

Use cases:

• Valorant: “Generate a timed flash + push flow for Haven A site,” and RPM returns a time-stamped playbook.

• Monster Hunter: RPM produces a “3-minute speedhunt” action plan and explains it step by step.

Through scripting, RPM becomes both operations coach and execution assistant.

4.3 Module Three: Assets & RWA System

Game assets have evolved from cosmetic to digital wealth. From purely aesthetic skins and mounts to financially flavored cards, gear, and items, in-game assets are now investment and collectible vehicles—carrying emotional value and powering real market activity.

Yet today’s markets remain opaque and fragmented:

• The same asset can differ by 30%+ in price across platforms.

• Rare items are overhyped, with scant reliable data on fills and liquidity.

• Players lack cross-market pricing and valuation tools, relying on gut feel.

• In some Web3 games (e.g., NFT cards), issuer control or data silos erode trust.

RPM’s answer: give virtual assets a real-world price anchor.

1. Valuation Engine Build dynamic pricing models from dimensions such as historical trades, scarcity, level, stat strength, and market depth, producing fair price bands and volatility alerts.

• For traditional markets (CS2, Dota 2, PUBG skins/cosmetics): analyze historical fills and volumes.

• For on-chain assets (e.g., Cards, Parallel, Gods Unchained, Sorare): track on-chain trades and holder distribution in real time.

• Generate asset-specific valuation curves and scarcity indices.

1. Cross-Market Aggregation Aggregate major marketplaces for unified quotes and smart comparison:

• Support Cards, OpenSea, Immutable, Steam Market, Magic Eden, Blur, etc.

• Show consolidated quotes, trend lines, and liquidity scores.

• Visualize buy–sell spreads and potential profit windows.

1. Natural-Language Trading (AI Voice/NLP Trading) Query and trade by voice or text:

• “Buy me a Messi card under $200.”

• “Show the latest trend for Parallel ‘Tesseract’ rares.”

• “Sell my Legendary Nikola Jokić NFT at 5% under market.”

RPM translates these into cross-market API operations for one-tap orders or listings.

Use cases:

• Case 1: CS2 Skin Market A player wants an AK-47 “Redline.” RPM fetches quotes from Steam, Buff, CSMoney, analyzes liquidity and fees, and recommends the best venue and timing.

• Case 2: NBA 2K Card Mode “Is LeBron’s Legendary card a buy now?” RPM synthesizes 30-day trade trends, issuance, and usage rates into investment advice with risk flags.

• Case 3: On-Chain Card Games (Cards / Parallel / Gods Unchained)

  • On Cards, RPM monitors each NFT’s historical appreciation, holder concentration, and depth.

  • In Parallel, it forecasts upward potential for rares based on deck meta, season updates, and new releases.

  • In Gods Unchained, it provides on-chain valuations and deck ROI simulations to optimize configurations.

RWA Mapping Mechanism

RPM links in-game assets to real-world asset logic, creating a virtual–real value mapping layer:

• RWA-ization of Game Assets: Rare skins, limited cards, and equipment NFTs are standardized into on-chain “digital RWAs” via RPM. These can be staked, fractionalized, and traded—forming a genuine financialization channel for game assets.

• Reverse Mapping of Real Assets: Tokens, card funds, or team revenue in gaming ecosystems can map to real financial claims (e.g., fund shares, IP rights), closing the Game–RWA loop.

Core Values

• Transparency: Unified pricing and on-chain provenance reduce manipulation.

• Fairness: Cross-market aggregation eliminates “info-gap harvesting.”

• Intelligence: AI-driven trading and recommendations boost capital efficiency.

• Scalability: Future integrations for on-chain finance (staking, collateral, yield sharing) to realize “Game Asset = Digital RWA.”

4.4 Module Four: Knowledge Graph & Data Engine

RPM’s intelligence stems not only from “the model,” but from its data backbone. We build a 3D knowledge graph for games:

1. Mechanics Graph

   • Game → Character → Skill → Equipment → Map → Boss

   • Relations include counters, synergies, drop rates, cooldowns, etc.

2. Version Graph

   • Every patch change is recorded and bound to related characters and mechanics.

   • Players can trace why “ADC got stronger in 13.5.”

3. Asset Graph

   • Each item/skin/card has a unique ID linked to price, issuance, and scarcity.

   • Combined with cross-market data to form a panoramic asset view.

Purpose:

• Make AI answers verifiable (sources, versions, logic).

• Avoid the “hallucinations” common to general LLMs.

• Feed reliable data into scripting and asset modules.

4.5 Feature Summary

RPM = the all-round gaming assistant:

• Strategy Assistant: Answers “how to play,” anytime.

• Script Generator: Solves “how to execute.”

• Asset Advisor: Explains “how to own.”

• Knowledge Graph: Ensures every answer is grounded.

These four modules reinforce each other to form a complete loop, delivering intelligence across both entertainment and asset dimensions.

Chapter 5: Technical Architecture

The goal of RPM is to deliver real-time, accurate, transparent, and secure intelligence to players and studios within a complex gaming ecosystem. To achieve this, we designed a four-layer architecture: Data Layer → Model Layer → Interaction Layer → Compliance & Security Layer.

5.1 Data Layer: A Digital Mirror of the Game World

Data is RPM’s core fuel. Unlike general LLMs that rely on broad internet corpora, RPM’s data sources are vertical and specialized:

1. Official Mechanics Data

   • Dev patch notes, change logs, official wikis.

   • Skills, item attributes, map mechanics, quest logic.

   • Parsed via NLP pipelines to extract numeric diffs and compare with prior versions.

2. Player Knowledge Data

   • Community guides, match analyses, curated Reddit/Bilibili/Twitter threads, pro stream transcripts.

   • Tactics, team comps, counterplay.

   • Dual curation (human + AI) to ensure high quality, low noise.

3. Asset & Market Data

   • APIs from major marketplaces (e.g., Cards, OpenSea, Steam Market).

   • Prices, volumes, scarcity, liquidity.

   • Stored in time-series databases for trend prediction and cross-market comparison.

4. User Interaction Data

   • Questions and usage logs within RPM (with user consent and after anonymization).

   • Improves the model’s grasp of real user needs.

Additionally, we maintain versioned archives: all data is timestamped and versioned. So when answering “How should ADC be played in 13.5?”, the system cites that version’s data, not a mix with the latest.

5.2 Model Layer: A Vertical Large Model Built for Games

RPM’s intelligence foundation is a vertical LLM, optimized in three stages:

1. Pretraining & Fine-Tuning

   • Start from open-source LLMs (e.g., LLaMA, Qwen) for general language capability.

   • Instruction-tune with domain corpora (patch notes, guides, market data) to boost expertise.

2. Retrieval-Augmented Generation (RAG)

   • Store patches, guides, and market intel in a vector database.

   • On query, retrieve first, then generate—ensuring timeliness and traceability.

3. Knowledge Graph & Logical Reasoning

   • Build a game knowledge graph (skills, gear, bosses, counters, drops).

   • Use a graph DB (e.g., Neo4j) to enable reasoning:

     • Example: If a patch nerfs a skill → the hero’s win rate drops → related item usage may also decline.

Future Multimodality:

• Upload a map screenshot → RPM recognizes it and outputs tactical advice.

• Upload an item icon → RPM identifies rarity and optimal synergies.

5.3 Interaction Layer: Natural Language as a Service

Design principle: let players use AI like chatting.

• Text: Mobile app, mini programs, PC extensions.

• Voice: In-game voice queries, e.g., “Recommend a dragon-slaying comp.”

• Wallet Integration: Bind on-chain wallets; support natural-language trading (buy/sell).

• Multi-Platform: PC, console, mobile—future VR/AR support.

Goal: a “play-anywhere” game assistant with seamless interactions in any context.

5.4 Compliance & Security Layer: Safeguarding Long-Term Growth

The biggest risk of AI in games is being flagged as a cheat. RPM is built with compliance and security first:

1. Whitelist Mechanism

   • Per-game compliance scopes embedded.

   • Example: allow hotkey tips and macro assists; disallow unfair exploit scripts.

2. Transparent Traceability

   • Every answer links to data sources (e.g., patch URLs, market snapshots).

   • One-click verification to avoid AI hallucinations.

3. Trading Compliance

   • Partnerships with marketplaces; adherence to KYC/AML.

   • Risk prompts for high-risk assets.

4. User Privacy Protection

   • Local anonymized storage; sensitive data excluded from training.

   • One-click personal data purge.

These measures position RPM as a trusted ecosystem partner—accepted by studios and trusted by players—rather than a gray-market tool.

5.5 Architecture Summary

RPM’s architecture forms a four-layer closed loop:

• Data Layer: Comprehensive coverage with versioned storage for freshness.

• Model Layer: Fine-tuning + RAG + knowledge graph for expertise and reasoning.

• Interaction Layer: Multi-end, natural-language-first for great UX.

• Compliance Layer: Whitelists, traceability, and compliant trading for safety.

This architecture not only satisfies players’ instant needs (tactics, scripts, asset trading) but also lays a solid foundation for long-term collaboration with studios and platforms.

Chapter 6: Market & Use Cases

Gaming is not only an entertainment industry—it’s a super-sector spanning culture, economics, and technology. The Real Player Model (RPM) serves both players and industry stakeholders, delivering tangible value across the board.

6.1 Global Market Potential

The global gaming market is rapidly expanding and increasingly diversified:

• Massive scale: In 2024, global gaming output exceeded $200B and is projected to approach $250B by 2027.

• User base: Over 3 billion players worldwide; nearly 60% are aged 16–35, the most consumption-ready cohort.

• Rich subgenres: MOBA, FPS, RPG, card, sports simulation—each with thriving ecosystems.

• Assetization: According to DappRadar, blockchain gaming asset volumes surpassed $3B in 2024, with strong growth expected.

In short, AI × Gaming × Assets is not just cutting-edge—it’s a sector with enduring economic value.

6.2 Player-Facing Use Cases

1. Fast Learning & Advancement

• Newcomers: Clear, concise onboarding via RPM lowers the learning barrier.

• Intermediate players: Personalized analytics improve win rates and efficiency.

• Veterans & pros: Patch parsing and tactical advice save research time and accelerate meta adaptation.

1. Operational Assist & Experience Optimization

• Provide compliant scripts and automation for high-intensity tasks.

• Accessibility: Custom interaction modes for players with disabilities, converting complex inputs into voice commands to boost playability and inclusion.

1. Fair & Transparent Asset Experience

• On-demand true value checks reduce information-asymmetry “taxation.”

• Cross-platform price comparison and auto-ordering minimize middlemen.

• AI risk alerts flag bubbles and thin liquidity.

6.3 Studio-Facing Use Cases

1. Content Generation & Cost Reduction

• Use RPM’s NLG to auto-generate side quests, dialogue, and NPC behaviors.

• Reduce repetitive content costs; refocus resources on core gameplay design.

1. Player Behavior Insights

• RPM’s analytics reveal behavior shifts across versions.

• Example: A sudden spike in an item’s win rate may signal balance issues.

• Enables precise balance changes and improved retention.

1. Compliance Assistance

• RPM’s whitelist scripting helps studios define “permitted assist” vs. “cheat,” curbing gray-market tools and protecting the ecosystem.

6.4 Marketplace-Facing Use Cases

1. Valuation & Price Transparency

• Integrate RPM’s valuation engine for more transparent pricing.

• Credible references increase trading activity.

1. Cross-Market Aggregation

• Unify multiple platforms for cross-market comparisons and liquidity analysis.

• Creates a “Kayak/Skyscanner for game assets” effect to attract users.

1. Risk Control & Security

• AI flags anomalous trades and potential wash trading / fraud.

• Smart risk services enhance platform compliance.

6.5 Esports & Content Industry Use Cases

1. Esports Tactical Analysis

• RPM acts as a virtual analyst, generating opponent scouting reports.

• Example: From the last 50 matches, analyze a player’s most-used heroes and skill patterns and propose counters.

1. Real-Time Match Explanations

• Viewers get intuitive explanations like “why this tactic worked right now.”

• Streamers level up professionalism with RPM-powered breakdowns.

1. Content Production Tools

• Guide writers draft faster with RPM and then refine manually.

• Video creators script quicker, improving throughput.

6.6 Differentiated Advantages

Compared with existing solutions, RPM offers unique benefits:

• More specialized than general AI: domain focus yields precise, reliable answers.

• More real-time than traditional guides: new strategies generated as patches drop.

• Fairer than single-market venues: AI valuation + cross-market aggregation reduces monopolistic distortions.

• More compliant than cheats: whitelist mechanisms earn studio recognition and support sustainable use.

6.7 Market & Scenario Summary

• For players: RPM = Time saved + Skill uplift + Asset protection.

• For studios: RPM = Lower cost + Better balance + Enhanced experience.

• For platforms: RPM = Transparent prices + Market aggregation + Risk control.

• For esports & creators: RPM = Pro-grade analysis + Better commentary + Faster production.

In the new era where AI, Web3, and gaming converge, the Real Player Model (RPM) will become infrastructure for the entire industry.

Chapter 7: Roadmap

A successful vertical large model needs more than technical breakthroughs—it needs a clear path and an executable plan. RPM’s roadmap spans three phases + long-term planning, evolving from MVP to a global ecosystem to maximize player value and industry impact.

7.1 Phase I: Minimum Viable Product (2025 Q4 – 2026 Q1)

Goal: Build the core feature loop

Focus on feasibility and shipping the MVP.

• Cover 20 top games

  • League of Legends, Valorant, CS2, Genshin Impact, Elden Ring, NBA 2K, FIFA, etc.

  • Build base knowledge graphs (characters, skills, gear, patches).

• Feature development

  • AI Game Assistant: patch parsing, tactics, team comps.

  • Basic script generation: whitelist macros & teaching scripts only (no cheats).

  • Initial asset valuation: start with platforms like Cards (sports cards).

• Technical validation

  • Automate the data pipeline (patch → cleaning → KG → training).

  • Establish vector DB + RAG for traceable Q&A.

• Community pilot

  • Recruit 500–1000 core players for closed beta.

  • Launch Discord/DAO; involve players in data labeling and strategy validation.

KPIs (Phase I):

• Daily interactions: 10,000+

• Strategy Q&A accuracy: ≥ 85%

• Asset valuation deviation: ≤ 10%

7.2 Phase II: Ecosystem Expansion (2026 Q2 – 2026 Q4)

Goal: From point features → multi-platform ecosystem

• Trading system upgrade

  • Integrate more platforms (OpenSea, Steam Market).

  • Enable cross-market comparison and auto-ordering.

  • Ship natural-language trading: “Buy me a rare card, $200 budget.”

• Enhanced scripting & assist

  • Personalized teaching scripts tailored to player skill levels.

  • Accessibility modules for players with disabilities.

• Studio partnerships

  • Collaborate with 3+ game studios to release officially endorsed RPM modules (NPC dialogue, narrative generation).

  • Gain broader acceptance as a compliance-first assistant.

• DAO governance

  • Token-holder voting on game-integration priorities.

  • Token incentives for data contribution/strategy validation.

  • Launch RPM Token for governance and rewards.

KPIs (Phase II):

• Games covered: 50+

• Supported marketplaces: 5+

• Active DAO users: 10,000+

• Valuation accuracy: ≥ 90%

7.3 Phase III: Global Scale (2027 – 2028)

Goal: Become industry infrastructure

• Multimodal capabilities

  • Map-screenshot recognition → tactical suggestions.

  • Video analysis for automated match review.

• Esports & events support

  • Tactical services for pro teams.

  • Real-time AI commentary for broadcasts.

  • Partnerships with pro leagues as official data analysis partner.

• Global go-to-market

  • Multi-language rollout across NA, EU, JP/KR, SEA.

  • Localized DAO nodes via regional communities.

• Asset financialization

  • Issue select high-value game assets as RWA.

  • Build indices, funds, and other products to standardize game-asset finance.

KPIs (Phase III):

• Global users: 10M+

• DAO participation rate: ≥ 30%

• Partner studios/platforms: 20+

• Annual GMV: $1B+

7.4 Long-Term Vision: Fusion of AI × Gaming × Reality

Over the next 5–10 years, RPM will evolve from an AI tool into the core infrastructure of the player ecosystem.

• Game-as-Economy

  • All virtual assets gain real value and liquidity through RPM.

  • Players shift from mere “spenders” to investors and participants.

• Player-as-Creator

  • With RPM, players generate quests, narratives, and scripts—co-producing game content.

• Bridge between reality and virtuality

  • Through RWA, connect sports cards, designer toys, and IP merch with in-game assets.

  • Hold “skins + physical collectibles” in the same wallet.

Ultimately, RPM enables a future where every player is a participant, an owner, and a creator.

Chapter 8: Conclusion — A New Era for Players

Over decades, gaming has grown from a living-room pastime into a global super-industry—both a universal cultural activity and a vanguard of the digital economy. Players have evolved from consumers into community members, content creators, and asset holders. Yet pain points persist: information complexity, high learning costs, and opaque assets.

RPM exists to change this.

1. From “Playing the Game” to “Being Played by the Game”

Common frustrations:

• Spending hours on guides just to find a best build.

• Patch updates invalidating hard-earned routines.

• Buying skins/cards at inflated prices across fragmented markets.

Players end up chasing the game instead of enjoying it. Asymmetrical information, skill barriers, and asset chaos distort the essence of fun.

1. RPM’s Mission: Put Players Back in Control

AI’s purpose is not replacement—it’s empowerment. In gaming, that means:

• Information transparency: real-time patch and market parsing for clear, first-minute conclusions.

• Strategic intelligence: distill complex mechanics into simple, effective advice for faster mastery.

• Asset fairness: valuation + cross-market comparison to flip the script from passive to proactive.

• Operational assistance: compliant scripts and personalized aids so more people—especially players with disabilities—enjoy the full experience.

This is the true meaning of “Play smarter, own fairer.”

1. Why Real Player DAO

Unlike traditional centralized companies, Real Player DAO believes players are not just users—they are builders.

• Players, via DAO, guide RPM’s roadmap (which games to prioritize, how to share value).

• Data contributors and validators earn tokens, becoming co-producers of the ecosystem.

• DAO governance ensures RPM remains fair and transparent, not captured by a single entity.

In short, RPM is for players—and built with players.

1. The Industry Bridge: AI × Gaming × Web3

We stand at the convergence of three waves:

• AI: LLMs are reshaping human–information interaction.

• Gaming: 3B players are forging new cultural and economic paradigms.

• Web3: Digital ownership and decentralization are redefining property.

RPM bridges all three:

• AI tackles info overload and mechanical complexity.

• Web3 brings asset transparency and fair trading.

• DAO guarantees player rights and voice.

This is a rare opportunity to transform gaming into an open, fair, and transparent value network.

1. A Call to Players

To every player:

• Tired of chasing patches? RPM is your personal strategist.

• Want easier mastery? RPM is your on-the-go assistant.

• Care about fair, transparent assets? RPM is your market advisor.

• Want real player voice? Real Player DAO is your home.

This is your era:

• Players are no longer just consumers, but participants, owners, and creators.

• Games are not just entertainment, but the frontier of economy and culture.

• AI is not just a tool, but a partner and bridge.

1. Closing Words

Real Player Model (RPM) is more than a product—it’s a promise:

• A promise to help players play smarter.

• A promise to help players own fairer.

• A promise to return power and value to the players themselves.

This is our vision—and our invitation to 3 billion players worldwide.

Join us and help build a future that truly belongs to players.

Chapter 1: Introduction — Why Gaming Needs Its Own Large Model

Over the past two decades, the gaming industry has undergone massive transformation — from offline to online, from PC to mobile, and from pay-to-play to free-to-play. Today, it stands as one of the largest digital entertainment sectors in the world. According to Newzoo, the global game market surpassed $200 billion in 2024, with over 3 billion players worldwide. Gaming is no longer a niche hobby; it is a global cultural and economic phenomenon.

Yet, beneath this booming surface lies a clear contradiction: The industry keeps growing rapidly, but the player experience is becoming increasingly complicated. This problem manifests in several ways:

1. Information Overload and Fragmentation Most mainstream games — especially competitive ones like League of Legends, Valorant, or DOTA 2 — release patches every few weeks. Each patch adjusts hero stats, item attributes, or map mechanics, dramatically reshaping the meta. However, players have to rely on scattered sources — patch notes, Reddit threads, Bilibili videos, or pro-player streams. The information is inconsistent and overwhelming, forcing players to spend hours verifying and learning.

2. Complex Mechanics and High Entry Barriers Modern games are far beyond the “press a few buttons to win” era. In Genshin Impact, players must understand character skills, artifact sets, and elemental reactions; in Elden Ring, a single boss fight can have a dozen phase changes, each requiring distinct strategies. For newcomers, these layers of complexity can feel impenetrable.

3. Lack of Transparency and Liquidity in Digital Assets With the dominance of “free-to-play + in-app purchase” models, virtual items have become integral assets. Skins, weapons, and cards represent identity and rarity. For example, the CS2 skin market alone generates billions in annual volume. Yet, pricing remains opaque, markets are fragmented, and players often make poor decisions due to asymmetric information.

4. Absence of Truly Intelligent Assistants Although AI tools like ChatGPT or Claude can answer general questions, they often fail in gaming contexts — giving irrelevant or outdated responses. They lack domain-specific training, cannot interpret live patch updates, and do not provide actionable gameplay advice. What players need is not a generalist assistant that “knows a bit of everything,” but a vertical large model — one that deeply understands games and actually helps players win.

5. Gaming = Entertainment + Economy With the rise of Web3, more games are integrating blockchain to tokenize in-game assets as NFTs or tradable tokens. “Play-to-earn” has become reality. However, the ecosystem remains fragmented, valuation systems inconsistent, and regulations unclear — making it difficult for ordinary players to assess risk and opportunity.

In short, the gaming world today is richer in content but poorer in clarity. That’s why we created the Real Player Model (RPM) — a vertical large model dedicated to gaming, designed to reduce information costs, enhance player experience, and empower rational decision-making in the era of digital assets.

Chapter 2: Vision — Play Smarter, Own Fairer

The role of players in the gaming universe is transforming. In the past, they were content consumers — buying games, spending money, clearing levels. Now, as games grow in complexity and economic depth, players have become co-creators, community builders, and asset holders.

The vision of the Real Player Model (RPM) can be summarized in eight words: “Play smarter, own fairer.”

1. Play Smarter — The Intelligent Game Assistant

The essence of gaming is play — yet modern games demand tremendous learning effort:

• After each patch, players must analyze reworked stats and study hours of guides.

• Boss fights have layered mechanics that require repeated trial and error.

• In competitive games, new “metas” emerge every few days, exhausting even veterans.

Most players spend more time researching than enjoying the game.

RPM’s mission is to make AI a natural companion for every player:

• When a new patch drops, RPM instantly analyzes all changes and delivers clear insights: “In Patch 13.5, X is the strongest ADC because Y.”

• When a player gets stuck, they can ask: “How do I beat this boss with only free gear?” RPM gives the optimal, step-by-step strategy.

• For competitive players, RPM reviews match data and provides personalized improvement tips: “Your Flash usage rate is 20% lower than top players — that’s the key factor reducing your win rate.”

In essence, RPM lowers the information barrier and lets every player truly enjoy the fun of gaming.

1. Own Fairer — Transparent Digital Asset Ecosystem

Virtual assets now mirror real-world economics. Skins, weapons, and collectible cards hold real value through rarity and demand. Yet today’s markets suffer from:

1. Opaque Valuation: the same item may be priced wildly differently across platforms.

2. Fragmented Liquidity: players must jump between multiple exchanges or gray markets.

3. Uncontrollable Risk: newcomers often fall victim to misinformation or predatory pricing.

The solution lies in AI-driven valuation and trading assistance:

• RPM aggregates multi-market data to build cross-platform pricing models.

• It evaluates scarcity, trade volume, and volatility to suggest fair price ranges.

• It tailors buy/sell recommendations to player intent — whether collecting, investing, or competing.

Moreover, RPM bridges RWA (Real-World Assets) with gaming assets — allowing physical items (e.g., collectible cards, game merchandise) to be traded alongside NFTs and digital skins in one interface.

This cross-domain fusion finally creates a fair market for gamers:

• No more hidden information asymmetry.

• No more reliance on gray-market middlemen.

• Every trade becomes transparent and traceable.

1. Player-First — The DAO Principle

The founding spirit of Real Player DAO is to turn players from passive participants into active decision-makers.

Under RPM’s DAO governance model:

• Players can submit game data, test strategies, and contribute to model improvement.

• They can share in ecosystem revenue — from trading commissions to RWA investment returns.

• Most importantly, their collective voice guides RPM’s evolution.

Our ambition is not merely to build a product, but to create an ecosystem where:

• Players are both users and contributors.

• The model is both a tool and a companion.

• Gaming becomes not just entertainment, but a network of value creation and fair sharing.

1. Vision Summary

“Play smarter, own fairer” is not just a slogan — it’s our blueprint for the next era of gaming:

• AI lowers the cost of learning and mastery, restoring the joy of play.

• RWA + AI ensures transparency and liquidity for digital assets.

• DAO governance gives power back to players, making them the true Real Players.

That is the purpose of the Real Player Model (RPM) — not merely a model, but a bridge to the next generation of the gaming ecosystem.

Chapter 3: Product Positioning

3.1 What Is the Real Player Model (RPM)

The Real Player Model (RPM) is a vertical large model dedicated to the gaming domain. Its mission is not to be a general-purpose AI that “knows a little bit about everything,” but rather to deeply understand the language, logic, and asset systems of the gaming ecosystem — and to provide players with truly valuable assistance.

RPM serves as both a personal assistant for players and a collaborative partner for game studios and platforms. It can provide real-time strategic support during gameplay, and offer accurate valuation and trading guidance for virtual assets outside of the game.

Compared with general-purpose AIs like ChatGPT, RPM’s core strengths lie in its depth and precision:

• Depth — It comprehends patch mechanisms, tactical logic, card synergies, and asset valuation models specific to games.

• Precision — It provides actionable, verifiable insights rather than vague or fabricated responses.

In short, RPM is a large model built for players.

3.2 How RPM Differs from General Large Models

Mainstream general models face three key limitations when applied to gaming:

1. Lack of Real-Time Updates

   • ChatGPT can answer general knowledge questions, but struggles with time-sensitive ones like “Who is the strongest ADC in League of Legends patch 14.2?” because it lacks access to live patch data.

2. Lack of Domain Depth

   • A general model might know a character’s skill names, but not how their stats interact or how to optimize tactical compositions. For example, in Genshin Impact, elemental reactions involve complex numerical interactions — something generic models can’t meaningfully analyze to give optimal team suggestions.

3. Lack of Asset Awareness

   • A general model can describe how a skin looks, but not assess its fair market price or compare listings across trading platforms.

RPM is designed precisely to solve these shortcomings:

• It connects directly to live patch data and market feeds to ensure real-time accuracy.

• It is trained on dedicated gaming knowledge graphs and player behavior datasets to ensure depth and expertise.

• It integrates valuation and trading logic to ensure fairness and transparency.

3.3 The Three Core Roles of RPM

1. Strategy & Knowledge Assistant

   • Provides instant, version-specific tactical recommendations.

   • Explains the deeper impact of patch updates.

   • Translates complex game mechanics into clear, actionable guidance.

2. Script & Action Generator

   • Converts natural language into compliant in-game operations.

   • Enables players to issue voice or text commands to generate battle plans or assistive automation.

   • Reduces learning curves and allows more players to get started faster.

3. Asset & Market Advisor

   • Offers fair valuations for items, cards, and skins.

   • Supports cross-platform price comparison and transaction recommendations.

   • Protects players from losses due to information asymmetry.

Together, these three roles form RPM’s closed-loop value chain — from “how to play” → “how to play better” → “how to own fairly.”

3.4 Value for Different User Groups

For Players:

• Beginners: Quickly learn game mechanics and lower entry barriers.

• Intermediate Players: Improve skills and increase win rates.

• Veterans / Pros: Analyze tactics and save research time.

• Asset Holders / Collectors: Access transparent and fair price benchmarks.

For the Industry:

• Game Developers: Integrate RPM via APIs to enable narrative generation, NPC intelligence, or gameplay balancing tools.

• Platforms: Use RPM’s valuation engine to enhance market liquidity and fairness.

• Communities: Contribute to data curation and validation through DAO mechanisms.

3.5 Product Positioning Summary

Real Player Model (RPM) = Strategy Assistant + Script Generator + Asset Advisor

It is not merely an AI tool — it is a new bridge between players and games:

• Helping players enjoy games with less friction.

• Making virtual asset trading transparent and trustworthy.

• Creating new collaboration opportunities between studios and communities.

If a general large model is like an encyclopedia, then RPM is the player’s personal strategist — a true “Game Master AI.”

Chapter 4: Core Feature Modules

The Real Player Model (RPM) is not designed as a “general-purpose chatbot.” It targets the three core needs of players:

1. How do I play? (Strategy & Knowledge Assistant)

2. How do I execute? (Script Generation & Assist)

3. How do I own? (Assets & RWA System)

Around these needs, RPM’s core features are organized into four modules:

4.1 Module One: AI Game Assistant

This is RPM’s most immediate value. Today, nearly all popular games update regularly; a single stat tweak can invalidate old guides overnight. To stay current, players often must:

• Read tens of thousands of words of official patch notes;

• Sift through community threads to separate signal from noise;

• Watch hours-long guide videos.

The experience is inefficient and discourages many casual players.

RPM’s solution:

• Automatic Patch Parsing: Extracts numeric changes within minutes of release and flags which adjustments materially impact the meta.

• Instant Strategy Generation: Combines historical match data with pro play insights to produce clear tactical recommendations.

• Personalized Recommendations: Tailors playstyles to a player’s habits and character preferences.

Use cases:

• League of Legends: Ask, “Who’s the strongest mid laner in patch 14.2?” RPM returns the latest picks with reasons.

• Genshin Impact: Say, “Build me a budget-friendly Pyro team,” and RPM outputs the lineup, artifacts, and rotation.

Result: players spend less time hunting information and more time enjoying the game.

4.2 Module Two: Script Generation & Assist

Modern games demand high operational complexity. In CS2, a single match can require hundreds of precise actions; in Elden Ring, a boss may demand dozens of perfect dodges and combos. For many, that’s stamina and reflex tax, not pure fun.

RPM’s solution:

• Natural Language → Actions: Speak or type commands—e.g., “Write a flash-entry combo script”—and AI generates the corresponding key sequence.

• Compliance Guardrails: A built-in whitelist of publisher APIs and rules outputs only permitted macros and assist actions, avoiding “cheatware.”

• Layered Assistance: From teaching scripts (instructional, step-by-step) to execution scripts (automated assist), adjustable by game and user context.

Use cases:

• Valorant: “Generate a timed flash + push flow for Haven A site,” and RPM returns a time-stamped playbook.

• Monster Hunter: RPM produces a “3-minute speedhunt” action plan and explains it step by step.

Through scripting, RPM becomes both operations coach and execution assistant.

4.3 Module Three: Assets & RWA System

Game assets have evolved from cosmetic to digital wealth. From purely aesthetic skins and mounts to financially flavored cards, gear, and items, in-game assets are now investment and collectible vehicles—carrying emotional value and powering real market activity.

Yet today’s markets remain opaque and fragmented:

• The same asset can differ by 30%+ in price across platforms.

• Rare items are overhyped, with scant reliable data on fills and liquidity.

• Players lack cross-market pricing and valuation tools, relying on gut feel.

• In some Web3 games (e.g., NFT cards), issuer control or data silos erode trust.

RPM’s answer: give virtual assets a real-world price anchor.

1. Valuation Engine Build dynamic pricing models from dimensions such as historical trades, scarcity, level, stat strength, and market depth, producing fair price bands and volatility alerts.

• For traditional markets (CS2, Dota 2, PUBG skins/cosmetics): analyze historical fills and volumes.

• For on-chain assets (e.g., Cards, Parallel, Gods Unchained, Sorare): track on-chain trades and holder distribution in real time.

• Generate asset-specific valuation curves and scarcity indices.

1. Cross-Market Aggregation Aggregate major marketplaces for unified quotes and smart comparison:

• Support Cards, OpenSea, Immutable, Steam Market, Magic Eden, Blur, etc.

• Show consolidated quotes, trend lines, and liquidity scores.

• Visualize buy–sell spreads and potential profit windows.

1. Natural-Language Trading (AI Voice/NLP Trading) Query and trade by voice or text:

• “Buy me a Messi card under $200.”

• “Show the latest trend for Parallel ‘Tesseract’ rares.”

• “Sell my Legendary Nikola Jokić NFT at 5% under market.”

RPM translates these into cross-market API operations for one-tap orders or listings.

Use cases:

• Case 1: CS2 Skin Market A player wants an AK-47 “Redline.” RPM fetches quotes from Steam, Buff, CSMoney, analyzes liquidity and fees, and recommends the best venue and timing.

• Case 2: NBA 2K Card Mode “Is LeBron’s Legendary card a buy now?” RPM synthesizes 30-day trade trends, issuance, and usage rates into investment advice with risk flags.

• Case 3: On-Chain Card Games (Cards / Parallel / Gods Unchained)

  • On Cards, RPM monitors each NFT’s historical appreciation, holder concentration, and depth.

  • In Parallel, it forecasts upward potential for rares based on deck meta, season updates, and new releases.

  • In Gods Unchained, it provides on-chain valuations and deck ROI simulations to optimize configurations.

RWA Mapping Mechanism

RPM links in-game assets to real-world asset logic, creating a virtual–real value mapping layer:

• RWA-ization of Game Assets: Rare skins, limited cards, and equipment NFTs are standardized into on-chain “digital RWAs” via RPM. These can be staked, fractionalized, and traded—forming a genuine financialization channel for game assets.

• Reverse Mapping of Real Assets: Tokens, card funds, or team revenue in gaming ecosystems can map to real financial claims (e.g., fund shares, IP rights), closing the Game–RWA loop.

Core Values

• Transparency: Unified pricing and on-chain provenance reduce manipulation.

• Fairness: Cross-market aggregation eliminates “info-gap harvesting.”

• Intelligence: AI-driven trading and recommendations boost capital efficiency.

• Scalability: Future integrations for on-chain finance (staking, collateral, yield sharing) to realize “Game Asset = Digital RWA.”

4.4 Module Four: Knowledge Graph & Data Engine

RPM’s intelligence stems not only from “the model,” but from its data backbone. We build a 3D knowledge graph for games:

1. Mechanics Graph

   • Game → Character → Skill → Equipment → Map → Boss

   • Relations include counters, synergies, drop rates, cooldowns, etc.

2. Version Graph

   • Every patch change is recorded and bound to related characters and mechanics.

   • Players can trace why “ADC got stronger in 13.5.”

3. Asset Graph

   • Each item/skin/card has a unique ID linked to price, issuance, and scarcity.

   • Combined with cross-market data to form a panoramic asset view.

Purpose:

• Make AI answers verifiable (sources, versions, logic).

• Avoid the “hallucinations” common to general LLMs.

• Feed reliable data into scripting and asset modules.

4.5 Feature Summary

RPM = the all-round gaming assistant:

• Strategy Assistant: Answers “how to play,” anytime.

• Script Generator: Solves “how to execute.”

• Asset Advisor: Explains “how to own.”

• Knowledge Graph: Ensures every answer is grounded.

These four modules reinforce each other to form a complete loop, delivering intelligence across both entertainment and asset dimensions.

Chapter 5: Technical Architecture

The goal of RPM is to deliver real-time, accurate, transparent, and secure intelligence to players and studios within a complex gaming ecosystem. To achieve this, we designed a four-layer architecture: Data Layer → Model Layer → Interaction Layer → Compliance & Security Layer.

5.1 Data Layer: A Digital Mirror of the Game World

Data is RPM’s core fuel. Unlike general LLMs that rely on broad internet corpora, RPM’s data sources are vertical and specialized:

1. Official Mechanics Data

   • Dev patch notes, change logs, official wikis.

   • Skills, item attributes, map mechanics, quest logic.

   • Parsed via NLP pipelines to extract numeric diffs and compare with prior versions.

2. Player Knowledge Data

   • Community guides, match analyses, curated Reddit/Bilibili/Twitter threads, pro stream transcripts.

   • Tactics, team comps, counterplay.

   • Dual curation (human + AI) to ensure high quality, low noise.

3. Asset & Market Data

   • APIs from major marketplaces (e.g., Cards, OpenSea, Steam Market).

   • Prices, volumes, scarcity, liquidity.

   • Stored in time-series databases for trend prediction and cross-market comparison.

4. User Interaction Data

   • Questions and usage logs within RPM (with user consent and after anonymization).

   • Improves the model’s grasp of real user needs.

Additionally, we maintain versioned archives: all data is timestamped and versioned. So when answering “How should ADC be played in 13.5?”, the system cites that version’s data, not a mix with the latest.

5.2 Model Layer: A Vertical Large Model Built for Games

RPM’s intelligence foundation is a vertical LLM, optimized in three stages:

1. Pretraining & Fine-Tuning

   • Start from open-source LLMs (e.g., LLaMA, Qwen) for general language capability.

   • Instruction-tune with domain corpora (patch notes, guides, market data) to boost expertise.

2. Retrieval-Augmented Generation (RAG)

   • Store patches, guides, and market intel in a vector database.

   • On query, retrieve first, then generate—ensuring timeliness and traceability.

3. Knowledge Graph & Logical Reasoning

   • Build a game knowledge graph (skills, gear, bosses, counters, drops).

   • Use a graph DB (e.g., Neo4j) to enable reasoning:

     • Example: If a patch nerfs a skill → the hero’s win rate drops → related item usage may also decline.

Future Multimodality:

• Upload a map screenshot → RPM recognizes it and outputs tactical advice.

• Upload an item icon → RPM identifies rarity and optimal synergies.

5.3 Interaction Layer: Natural Language as a Service

Design principle: let players use AI like chatting.

• Text: Mobile app, mini programs, PC extensions.

• Voice: In-game voice queries, e.g., “Recommend a dragon-slaying comp.”

• Wallet Integration: Bind on-chain wallets; support natural-language trading (buy/sell).

• Multi-Platform: PC, console, mobile—future VR/AR support.

Goal: a “play-anywhere” game assistant with seamless interactions in any context.

5.4 Compliance & Security Layer: Safeguarding Long-Term Growth

The biggest risk of AI in games is being flagged as a cheat. RPM is built with compliance and security first:

1. Whitelist Mechanism

   • Per-game compliance scopes embedded.

   • Example: allow hotkey tips and macro assists; disallow unfair exploit scripts.

2. Transparent Traceability

   • Every answer links to data sources (e.g., patch URLs, market snapshots).

   • One-click verification to avoid AI hallucinations.

3. Trading Compliance

   • Partnerships with marketplaces; adherence to KYC/AML.

   • Risk prompts for high-risk assets.

4. User Privacy Protection

   • Local anonymized storage; sensitive data excluded from training.

   • One-click personal data purge.

These measures position RPM as a trusted ecosystem partner—accepted by studios and trusted by players—rather than a gray-market tool.

5.5 Architecture Summary

RPM’s architecture forms a four-layer closed loop:

• Data Layer: Comprehensive coverage with versioned storage for freshness.

• Model Layer: Fine-tuning + RAG + knowledge graph for expertise and reasoning.

• Interaction Layer: Multi-end, natural-language-first for great UX.

• Compliance Layer: Whitelists, traceability, and compliant trading for safety.

This architecture not only satisfies players’ instant needs (tactics, scripts, asset trading) but also lays a solid foundation for long-term collaboration with studios and platforms.

Chapter 6: Market & Use Cases

Gaming is not only an entertainment industry—it’s a super-sector spanning culture, economics, and technology. The Real Player Model (RPM) serves both players and industry stakeholders, delivering tangible value across the board.

6.1 Global Market Potential

The global gaming market is rapidly expanding and increasingly diversified:

• Massive scale: In 2024, global gaming output exceeded $200B and is projected to approach $250B by 2027.

• User base: Over 3 billion players worldwide; nearly 60% are aged 16–35, the most consumption-ready cohort.

• Rich subgenres: MOBA, FPS, RPG, card, sports simulation—each with thriving ecosystems.

• Assetization: According to DappRadar, blockchain gaming asset volumes surpassed $3B in 2024, with strong growth expected.

In short, AI × Gaming × Assets is not just cutting-edge—it’s a sector with enduring economic value.

6.2 Player-Facing Use Cases

1. Fast Learning & Advancement

• Newcomers: Clear, concise onboarding via RPM lowers the learning barrier.

• Intermediate players: Personalized analytics improve win rates and efficiency.

• Veterans & pros: Patch parsing and tactical advice save research time and accelerate meta adaptation.

1. Operational Assist & Experience Optimization

• Provide compliant scripts and automation for high-intensity tasks.

• Accessibility: Custom interaction modes for players with disabilities, converting complex inputs into voice commands to boost playability and inclusion.

1. Fair & Transparent Asset Experience

• On-demand true value checks reduce information-asymmetry “taxation.”

• Cross-platform price comparison and auto-ordering minimize middlemen.

• AI risk alerts flag bubbles and thin liquidity.

6.3 Studio-Facing Use Cases

1. Content Generation & Cost Reduction

• Use RPM’s NLG to auto-generate side quests, dialogue, and NPC behaviors.

• Reduce repetitive content costs; refocus resources on core gameplay design.

1. Player Behavior Insights

• RPM’s analytics reveal behavior shifts across versions.

• Example: A sudden spike in an item’s win rate may signal balance issues.

• Enables precise balance changes and improved retention.

1. Compliance Assistance

• RPM’s whitelist scripting helps studios define “permitted assist” vs. “cheat,” curbing gray-market tools and protecting the ecosystem.

6.4 Marketplace-Facing Use Cases

1. Valuation & Price Transparency

• Integrate RPM’s valuation engine for more transparent pricing.

• Credible references increase trading activity.

1. Cross-Market Aggregation

• Unify multiple platforms for cross-market comparisons and liquidity analysis.

• Creates a “Kayak/Skyscanner for game assets” effect to attract users.

1. Risk Control & Security

• AI flags anomalous trades and potential wash trading / fraud.

• Smart risk services enhance platform compliance.

6.5 Esports & Content Industry Use Cases

1. Esports Tactical Analysis

• RPM acts as a virtual analyst, generating opponent scouting reports.

• Example: From the last 50 matches, analyze a player’s most-used heroes and skill patterns and propose counters.

1. Real-Time Match Explanations

• Viewers get intuitive explanations like “why this tactic worked right now.”

• Streamers level up professionalism with RPM-powered breakdowns.

1. Content Production Tools

• Guide writers draft faster with RPM and then refine manually.

• Video creators script quicker, improving throughput.

6.6 Differentiated Advantages

Compared with existing solutions, RPM offers unique benefits:

• More specialized than general AI: domain focus yields precise, reliable answers.

• More real-time than traditional guides: new strategies generated as patches drop.

• Fairer than single-market venues: AI valuation + cross-market aggregation reduces monopolistic distortions.

• More compliant than cheats: whitelist mechanisms earn studio recognition and support sustainable use.

6.7 Market & Scenario Summary

• For players: RPM = Time saved + Skill uplift + Asset protection.

• For studios: RPM = Lower cost + Better balance + Enhanced experience.

• For platforms: RPM = Transparent prices + Market aggregation + Risk control.

• For esports & creators: RPM = Pro-grade analysis + Better commentary + Faster production.

In the new era where AI, Web3, and gaming converge, the Real Player Model (RPM) will become infrastructure for the entire industry.

Chapter 7: Roadmap

A successful vertical large model needs more than technical breakthroughs—it needs a clear path and an executable plan. RPM’s roadmap spans three phases + long-term planning, evolving from MVP to a global ecosystem to maximize player value and industry impact.

7.1 Phase I: Minimum Viable Product (2025 Q4 – 2026 Q1)

Goal: Build the core feature loop

Focus on feasibility and shipping the MVP.

• Cover 20 top games

  • League of Legends, Valorant, CS2, Genshin Impact, Elden Ring, NBA 2K, FIFA, etc.

  • Build base knowledge graphs (characters, skills, gear, patches).

• Feature development

  • AI Game Assistant: patch parsing, tactics, team comps.

  • Basic script generation: whitelist macros & teaching scripts only (no cheats).

  • Initial asset valuation: start with platforms like Cards (sports cards).

• Technical validation

  • Automate the data pipeline (patch → cleaning → KG → training).

  • Establish vector DB + RAG for traceable Q&A.

• Community pilot

  • Recruit 500–1000 core players for closed beta.

  • Launch Discord/DAO; involve players in data labeling and strategy validation.

KPIs (Phase I):

• Daily interactions: 10,000+

• Strategy Q&A accuracy: ≥ 85%

• Asset valuation deviation: ≤ 10%

7.2 Phase II: Ecosystem Expansion (2026 Q2 – 2026 Q4)

Goal: From point features → multi-platform ecosystem

• Trading system upgrade

  • Integrate more platforms (OpenSea, Steam Market).

  • Enable cross-market comparison and auto-ordering.

  • Ship natural-language trading: “Buy me a rare card, $200 budget.”

• Enhanced scripting & assist

  • Personalized teaching scripts tailored to player skill levels.

  • Accessibility modules for players with disabilities.

• Studio partnerships

  • Collaborate with 3+ game studios to release officially endorsed RPM modules (NPC dialogue, narrative generation).

  • Gain broader acceptance as a compliance-first assistant.

• DAO governance

  • Token-holder voting on game-integration priorities.

  • Token incentives for data contribution/strategy validation.

  • Launch RPM Token for governance and rewards.

KPIs (Phase II):

• Games covered: 50+

• Supported marketplaces: 5+

• Active DAO users: 10,000+

• Valuation accuracy: ≥ 90%

7.3 Phase III: Global Scale (2027 – 2028)

Goal: Become industry infrastructure

• Multimodal capabilities

  • Map-screenshot recognition → tactical suggestions.

  • Video analysis for automated match review.

• Esports & events support

  • Tactical services for pro teams.

  • Real-time AI commentary for broadcasts.

  • Partnerships with pro leagues as official data analysis partner.

• Global go-to-market

  • Multi-language rollout across NA, EU, JP/KR, SEA.

  • Localized DAO nodes via regional communities.

• Asset financialization

  • Issue select high-value game assets as RWA.

  • Build indices, funds, and other products to standardize game-asset finance.

KPIs (Phase III):

• Global users: 10M+

• DAO participation rate: ≥ 30%

• Partner studios/platforms: 20+

• Annual GMV: $1B+

7.4 Long-Term Vision: Fusion of AI × Gaming × Reality

Over the next 5–10 years, RPM will evolve from an AI tool into the core infrastructure of the player ecosystem.

• Game-as-Economy

  • All virtual assets gain real value and liquidity through RPM.

  • Players shift from mere “spenders” to investors and participants.

• Player-as-Creator

  • With RPM, players generate quests, narratives, and scripts—co-producing game content.

• Bridge between reality and virtuality

  • Through RWA, connect sports cards, designer toys, and IP merch with in-game assets.

  • Hold “skins + physical collectibles” in the same wallet.

Ultimately, RPM enables a future where every player is a participant, an owner, and a creator.

Chapter 8: Conclusion — A New Era for Players

Over decades, gaming has grown from a living-room pastime into a global super-industry—both a universal cultural activity and a vanguard of the digital economy. Players have evolved from consumers into community members, content creators, and asset holders. Yet pain points persist: information complexity, high learning costs, and opaque assets.

RPM exists to change this.

1. From “Playing the Game” to “Being Played by the Game”

Common frustrations:

• Spending hours on guides just to find a best build.

• Patch updates invalidating hard-earned routines.

• Buying skins/cards at inflated prices across fragmented markets.

Players end up chasing the game instead of enjoying it. Asymmetrical information, skill barriers, and asset chaos distort the essence of fun.

1. RPM’s Mission: Put Players Back in Control

AI’s purpose is not replacement—it’s empowerment. In gaming, that means:

• Information transparency: real-time patch and market parsing for clear, first-minute conclusions.

• Strategic intelligence: distill complex mechanics into simple, effective advice for faster mastery.

• Asset fairness: valuation + cross-market comparison to flip the script from passive to proactive.

• Operational assistance: compliant scripts and personalized aids so more people—especially players with disabilities—enjoy the full experience.

This is the true meaning of “Play smarter, own fairer.”

1. Why Real Player DAO

Unlike traditional centralized companies, Real Player DAO believes players are not just users—they are builders.

• Players, via DAO, guide RPM’s roadmap (which games to prioritize, how to share value).

• Data contributors and validators earn tokens, becoming co-producers of the ecosystem.

• DAO governance ensures RPM remains fair and transparent, not captured by a single entity.

In short, RPM is for players—and built with players.

1. The Industry Bridge: AI × Gaming × Web3

We stand at the convergence of three waves:

• AI: LLMs are reshaping human–information interaction.

• Gaming: 3B players are forging new cultural and economic paradigms.

• Web3: Digital ownership and decentralization are redefining property.

RPM bridges all three:

• AI tackles info overload and mechanical complexity.

• Web3 brings asset transparency and fair trading.

• DAO guarantees player rights and voice.

This is a rare opportunity to transform gaming into an open, fair, and transparent value network.

1. A Call to Players

To every player:

• Tired of chasing patches? RPM is your personal strategist.

• Want easier mastery? RPM is your on-the-go assistant.

• Care about fair, transparent assets? RPM is your market advisor.

• Want real player voice? Real Player DAO is your home.

This is your era:

• Players are no longer just consumers, but participants, owners, and creators.

• Games are not just entertainment, but the frontier of economy and culture.

• AI is not just a tool, but a partner and bridge.

1. Closing Words

Real Player Model (RPM) is more than a product—it’s a promise:

• A promise to help players play smarter.

• A promise to help players own fairer.

• A promise to return power and value to the players themselves.

This is our vision—and our invitation to 3 billion players worldwide.

Join us and help build a future that truly belongs to players.