Author:
Banasode Praveen,Patil Minal,SupriyaVerma
Abstract
Abstract
The craze of Indian Premier League (IPL) is always there in millions of people including Indian and our work is about the analysis of the data and prediction of the IPL matches. IPL Data Analysis is all about the analysing the data that is al- ready present in data set using data science, machine learning and python. This is an application design for the purpose of analysing the data by fetching the attribute from the data set and predicting the future of the match and as well as of the players. This will help in the selection of the IPL team that the team should perform good and win the match. Prediction is done for anything like which player will play well in tomorrow’s match, which team will win toss and even match etc. The prediction can be done with the help of the analysis on that data set collected and by displaying proper data that is useful for the future prediction. The algorithms have given accuracy over 95%.
Reference13 articles.
1. The IPL Model: Sports Marketing and Product Placement Sponsorship;Mittal;International Journal of Humanities and Social Science Invention,2017
2. CricAI: A classification based tool to predict the outcome in ODI cricket;Kaluarachchi
3. India and the IPL: Cricket’s Globalized Empire;Gupta
4. Predicting the Winner in One DayInternationalCricket;Bandulasiri;Journal of Mathematical Sciences & Mathematics Education
5. Data Analytics based Deep Mayo Predictor for IPL-9;Prakash
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Data-Driven Strategies for Enhancing Performance in Indian Premier League: A Case Study of Royal Challengers Bangalore;2024 International Conference on Emerging Technologies in Computer Science for Interdisciplinary Applications (ICETCS);2024-04-22
2. A Structured Analysis on IPL 2022 matches by approaching various Data Visualization and Analytics;2023 International Conference on Computer Communication and Informatics (ICCCI);2023-01-23
3. IPL Analysis and Match Prediction;Lecture Notes in Networks and Systems;2022-10-28