Summary of Fancric : Multi-agentic Framework For Crafting Fantasy 11 Cricket Teams, by Mohit Bhatnagar
FanCric : Multi-Agentic Framework for Crafting Fantasy 11 Cricket Teams
by Mohit Bhatnagar
First submitted to arxiv on: 2 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces FanCric, an advanced multi-agent system that leverages Large Language Models (LLMs) and a robust orchestration framework to enhance fantasy team selection in cricket. The study focuses on Dream11, India’s leading fantasy cricket league for the Indian Premier League (IPL), where participants craft virtual teams based on real player performances. FanCric employs both structured and unstructured data to surpass traditional methods by incorporating sophisticated AI technologies. The analysis evaluates FanCric’s efficacy against the collective wisdom of crowds and a simpler Prompt Engineering approach, using approximately 12.7 million unique entries from a Dream11 contest. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about how computers can help people pick winning fantasy teams in cricket games. Fantasy sports are popular, and this study shows that machines like Large Language Models (LLMs) can make good choices if they use the right data. The research looks at a big contest with millions of entries to see how well a new system called FanCric works. It compares FanCric to other ways of picking teams, and the results are promising. |
Keywords
» Artificial intelligence » Prompt
