FanCric : Multi-Agentic Framework for Crafting Fantasy 11 Cricket Teams

TL;DR

FanCric is a multi-agent framework utilizing Large Language Models to improve fantasy cricket team selection, outperforming traditional methods and crowdsourcing approaches in Dream11 IPL contests.

Contribution

This paper introduces FanCric, an innovative multi-agent system that leverages LLMs and orchestration frameworks to enhance fantasy cricket team crafting, surpassing existing strategies.

Findings

FanCric outperforms traditional methods in team selection accuracy.

Analysis of 12.7 million entries demonstrates its effectiveness.

Ablation studies show the impact of generating multiple teams.

Abstract

Cricket, with its intricate strategies and deep history, increasingly captivates a global audience. The Indian Premier League (IPL), epitomizing Twenty20 cricket, showcases talent in a format that lasts just a few hours as opposed to the longer forms of the game. Renowned for its fusion of technology and fan engagement, the IPL stands as the world's most popular cricket league. This study concentrates on Dream11, India's leading fantasy cricket league for IPL, where participants craft virtual teams based on real player performances to compete internationally. Building a winning fantasy team requires navigating various complex factors including player form and match conditions. Traditionally, this has been approached through operations research and machine learning. This research introduces the FanCric framework, an advanced multi-agent system leveraging Large Language Models (LLMs) and a robust orchestration framework to enhance fantasy team selection in cricket. FanCric employs both structured and unstructured data to surpass traditional methods by incorporating sophisticated AI technologies. The analysis involved scrutinizing approximately 12.7 million unique entries from a Dream11 contest, evaluating FanCric's efficacy against the collective wisdom of crowds and a simpler Prompt Engineering approach. Ablation studies further assessed the impact of generating varying numbers of teams. The exploratory findings are promising, indicating that further investigation into FanCric's capabilities is warranted to fully realize its potential in enhancing strategic decision-making using LLMs in fantasy sports and business in general.