Predictive Analysis in T-20 Cricket: Estimation and Prediction of fantasy points for IPL Players

Gogate, Pratheek (2023) Predictive Analysis in T-20 Cricket: Estimation and Prediction of fantasy points for IPL Players. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research investigates the utilisation of machine learning (ML) and deep learning (DL) models to estimate and forecast the performance of specific cricket players participating in the Indian Premier League (IPL). The study focuses on the estimation of their fantasy points from the batting perspective only. The study initially utilized ML methodologies, including Support Vector Machines (SVM), Linear Regression. Even though we got a good result with high R² value and low root mean square error (RMSE) values there were some drawbacks such as it used to compare with single predicted data point for evaluation and it used to consider current match data as well to estimate the fantasy points. So, the research is transitioned towards rolling window technique with integration of the DL techniques. By exclusively utilising historical data, this approach effectively eradicated both the drawbacks of previous approach. Although the outcomes of this methodological shift were not preferable to those of the initial ML models, it was still deemed more suitable for the predictive task. Potential factors that may have contributed to the subpar performance of DL models in this scenario include inadequate data volume or the requirement for a more features.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Jain, Mayank UNSPECIFIED
Uncontrolled Keywords:	Machine Learning; IPL Data; Fantasy Point Prediction; Linear Regression; SVM; Player Performance; LSTM; BiLSTM
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning 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:	08 May 2025 11:53
Last Modified:	08 May 2025 11:54
URI:	https://norma.ncirl.ie/id/eprint/7517

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