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@article{176397,
        author = {Adharsh Narayan N and Govindaram R and Surendheran S and Sanjay Sharan S and Buvana M},
        title = {Fantasy Cricket Team Predictor},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5194-5197},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176397},
        abstract = {The Fantasy Cricket Team Predictor is a web-based application designed to help users build an optimal fantasy cricket team for Indian Premier League (IPL) matches by analyzing historical player performance data. Developed using Python and Flask, it processes past match data using libraries like Pandas and NumPy to compute key performance metrics such as batting averages, strike rates, economy rates, and wickets. These metrics are weighted to calculate a performance score for each player, which is then used to recommend the best team combination while adhering to fantasy league rules like credit limits and player roles. The system also includes visual data representation for better insights and a user-friendly interface, offering a transparent, real-time, and data-driven solution for fantasy cricket enthusiasts.},
        keywords = {Fantasy Cricket, Team Prediction, IPL Analytics, Sports Data Analytics, Player Performance Metrics, Web-Based Application, Python Flask, Statistical Modeling, Fantasy League Strategy, Data-Driven Sports Tools, Real-Time Team Selector, Cricket Data Processing, Role-Based Player Selection, Fantasy Credits Management, Interactive Sports Platform},
        month = {April},
        }