International Journal of Computer Techniques Volume 12 Issue 3 | Predicting IPL Match Winners Using Logistic Regression: A Machine Learning Approach
Predicting IPL Match Winners Using Logistic Regression: A Machine Learning Approach
International Journal of Computer Techniques – Volume 12 Issue 3, May – June 2025
Abstract
This study applies **Logistic Regression**, a binary classification algorithm, to predict outcomes of **Indian Premier League (IPL) 2025** matches. Using features such as **team form, head-to-head history, player performance, and weather**, the model achieved a **91% prediction accuracy**—outperforming Decision Trees, Random Forest, and SVM. The solution offers a **computationally efficient, interpretable framework** for sports analysts and enthusiasts.
Keywords
Indian Premier League, Machine Learning, Logistic Regression, Binary Classification, Cricket Forecasting.
Conclusion
The use of **Logistic Regression** in IPL match outcome prediction provides a **lightweight and reliable method** for cricket analytics. Future enhancements may include **real-time data integration, advanced AI techniques, and interactive dashboards** to boost prediction precision and user experience for analysts, fans, and strategists alike.
References
- Choudhary, V., & Sharma, N. (2020). Machine Learning Techniques for IPL Match Outcome Prediction.
- Agarwal, P., & Jain, M. (2021). Predicting IPL Match Outcomes with Machine Learning Models.
- Verma, K., & Joshi, A. (2022). Deep Learning Model for IPL Match Winner Prediction.
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