Advanced Valorant Match Winner Prediction System

Advanced Valorant Match Winner Prediction System: Developed a machine learning model to predict professional Valorant match outcomes using over 10,000 historical match records. Performed data preprocessing, feature engineering (including an Elo rating system), and trained multiple models such as Logistic Regression, Random Forest, SVM, and XGBoost. Evaluated model performance using Accuracy, Precision, Recall, F1 Score, Confusion Matrix, and cross-validation, with hyperparameter tuning via GridSearchCV. Improved prediction accuracy from 57% to 65.5% and deployed the final model as an interactive Streamlit web application.