SPORTS ANALYTICS AI: PLAYER PERFORMANCE PREDICTION AND STRATEGY OPTIMIZATION

Athlon Predict Pro is an advanced sports analytics platform designed for cricket, leveraging machine learning techniques to predict player performance and optimize team strategies. The system processes historical One-Day International (ODI) match data extracted from YAML files, generating structured datasets for batsmen and bowlers that include both aggregate statistics (e.g., batting average, strike rate, centuries) and match-level contextual features (e.g., runs scored, wickets taken, venue, and opposition).The platform employs state-of-the-art machine learning algorithms such as Extreme Gradient Boosting (XGBoost), Random Forest, and Support Vector Machines (SVM) to forecast player performance metrics, including batsman runs and bowler wickets. These predictions are enhanced by incorporating contextual and temporal factors such as player form, match conditions, and opposition strength, consistent with prior research in sports analytics and predictive modeling [1]–[4].A user-friendly interface built using Streamlit enables seamless data uploading, visualization, and performance exploration. Additionally, the system integrates advanced modules for strategic decision-making, including optimal playing XI selection using classification techniques, injury risk prediction based on simulated physiological metrics (e.g., fatigue and fitness scores), and team synergy analysis inspired by performance indicators and sports science methodologies [5], [6]. The framework further incorporates time-series forecasting for performance trends and regression-based models for points estimation, aligning with modern approaches in sports analytics and outcome prediction [7]–[9]. Model performance is evaluated using robust metrics such as R² score for regression tasks and F1-score for classification tasks, demonstrating high predictive reliability.