> For the complete documentation index, see [llms.txt](https://basketball-fun.gitbook.io/basketball.fun-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://basketball-fun.gitbook.io/basketball.fun-docs/prediction-markets.md). # Prediction Markets Basketball.fun includes a fully on-chain prediction market for every NBA game, designed for fans who want deeper, more exotic, and more granular betting options than traditional sportsbooks or prediction platforms can offer. Unlike standard markets that only offer simple outcomes (Win/Lose, Over/Under), Basketball.fun lets users take positions on **micro-events, player-specific outcomes, and custom spreads** that are usually unavailable elsewhere. These markets run on a transparent, on-chain system that allows BBDF users to capture the most exotic betting odds. ### **What Makes Our Prediction Markets Different** #### **1. Exotic Spreads (Our Core Value Proposition)** Traditional platforms only allow shallow bets: * Straight-line spreads * Simple Over/Under * Basic player props Basketball.fun supports **custom, exotic, admin-designed spreads**, such as: * *“Will Luka score **38+ points** AND win?”* * *“Will Steph make **8+ threes**?”* * *“Will Jokic record a **25/15/12 triple-double**?”* * *“Will there be **3+ lead changes** in the 4th quarter?”* * *“Will the game end within **5 points**?”* * *“Will LeBron have more points than the entire Blazers bench?”* This is impossible (or rarely available) on standard betting sites — and never available on-chain until now. *** ### **2. Admin-Curated Odds with Real Edge** Unlike Polymarket (pure yes/no) or TopShot (no betting), Basketball.fun lets the team create curated betting lines: * Exotic player props * Multi-leg outcomes * Game-flow props * Narrative-based bets * Social-driven “meme markets” **Your team controls odds**, adjusting for risk and reward, letting you craft markets that are fun, unpredictable, and shareable. *** ### **3. PVP Betting With Player Tokens** Users bet **Player Tokens** on admin directed outcomes, player tokens are now: * More utility for tokens * A non-gambling, skill-based staking mechanic * A way to compound their favorite player’s upside * A lightweight alternative to cash betting systems This also reinforces demand for Player Tokens beyond trading. An example for these markets can be the following: * Admin can set up Lebron vs Kawhi for points, players can now stake their Kawhi or Lebron player tokens in the pot for predetermined odds. As the pool closes, its a winner take all pro rata for the result of the bet. *** ### **4. Weekly Admin-Defined Contest Pots** Every market comes with: * **A fixed admin-set pot prize** (e.g., $1,000 worth of tokens) * **Two outcomes** (Side A vs Side B) * **Custom odds** (admin-chosen multipliers) * **A clear expiry time** (game start or quarter end) This ensures: * Clear expected value (EV) * Predictable reward structures * Limited risk of pot imbalance * High user clarity *** ### **5. Fair Settlement & Transparent Mechanics** All outcomes are resolved by: * Official NBA stat feeds powered by Sportsradar * On-chain verification * Public rules per contest * No hidden manipulation You build trust by making everything transparent and immutable. *** ## **Example Markets** #### **Exotic Player Markets** * *Will Ant Edwards dunk on someone tonight?* * *Will Giannis score 20+ points in the paint?* * *Will Kawhi attempt more than 5 midrange shots?* #### **Game Flow Markets** * *Will there be a 10–0 run?* * *Will the winning team lead for the entire game?* * *Will overtime happen?* #### **Narrative/Meme Markets** * *Will Dillon Brooks get a technical?* * *Will Embiid troll on Instagram after the game?* *** --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://basketball-fun.gitbook.io/basketball.fun-docs/prediction-markets.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.