A Multi-Agentic AI System for Cricket Team Selection

Sriraman, Ravi (2025) A Multi-Agentic AI System for Cricket Team Selection. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (1MB) | Preview
Preview	PDF (Configuration Manual) Download (763kB) | Preview

Abstract

Data Analysis has become an integral part of any international or franchise cricket teams, almost every team have a dedicated data analyst with them. Data Analysts are required as finding insights from the historical data helps in picking players in auction, selecting players 11 for a match from the full squad, and to understand the strengths and weaknesses of both own team and the opponent team to plan how batting and bowling should be approached. However, the data analysts are really expensive, and have limitations as it is humanly really difficult to remember every statistics especially in a complex sport like cricket. This problem can be easily solved with the use of advancements in natural language processing techniques. We have built a multi-agent system with two flows: (1) Data analyst flow, and (2) team selector flow which helps in finding answers to any performance questions on any player, team, or venue, it also helps in finding the best playing 11 by picking the best performers in each role. The system is evaluated on three metrics: (1) Task Success rate, (2) Efficiency Score, (3) Correctness Score. The results show that the system achieves 100 percent task success rate and correctness score while scoring about 90 percent efficiency score.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Basilio, Jorge UNSPECIFIED
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing G Geography. Anthropology. Recreation > GV Recreation Leisure > Sports
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	09 Sep 2026 10:05
Last Modified:	09 Sep 2026 10:05
URI:	https://norma.ncirl.ie/id/eprint/9918

Actions (login required)

View Item